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Application of chemical acoustic emission to industrial processes Crowther, Timothy Guy 1991

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Application of Chemical Acoustic Emission to Industrial Processes by Timothy Guy Crowther B.Sc(Hons), Kings College, London, 1988. A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES, DEPARTMENT OF CHEMISTRY. We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA APRIL 1991 Copyright, Timothy G. Crowther, 1991 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of CZ23C\QJN^ >JS ^ "^A^ The University of British Columbia Vancouver, Canada Date Ho^ , DE-6 (2/88) ABSTRACT This thesis reports on two chemical acoustic emission studies of importance to Canadian Industry. The first demonstrated that the rate of evolution of hydrogen and oxygen from electrodes in an electrolysis cell may be conveniently monitored via its ultrasonic acoustic emission, in a non-intrusive manner. The apparatus used in this work consisted of a nickel anode, a stainless steel cathode, and a saturated calomel reference electrode, all situated in a three-chamber cell containing sodium hydroxide electrolyte solutions of various concentrations. The potential necessary for evolution of both hydrogen and oxygen was conclusively determined by the onset of bursts of acoustic emission. Individual acoustic emission signals, captured using a broadband transducer mounted on the working electrode, contained frequencies from 16 kHz to as high as 800 kHz. These were correlated with the release of streams of bubbles from the electrode's surface, both visually and via a chart recorder trace of peak acoustic intensity vs. time. Trends in several time-domain signal descriptors were observed with an increase in the applied voltage. Acoustic power spectra were obtained by averaging spectra from many acoustic signals. Estimates of rate of emission were made by integration of the peak acoustic level. The effects of applied potential and electrolyte concentration on the multiple bursts of acoustic emission were characterized and are presented as a system response surface. Increasing the applied potential resulted in greater rates of bubble emission, which increased the intensity of acoustic emission, but produced, essentially, an identical acoustic power spectrum. The extent of acoustic emission at high concentrations (2.0 M) and high applied potentials (3.0 - 4.0 V) was less than expected, which suggested a decrease in efficiency under these conditions. Evolution of gas from the electrolysis was compared with the root mean square (RMS) voltage of the acoustic signal. The acoustic RMS was found to correlate linearly with gas volume produced, and consequently it correlated linearly with current measurements. Further studies indicate that the formation of oxides on a clean electrode surface was accompanied by limited acoustic i i i activity, but no such emissions were found for electrodes in which the oxide coating was already present. The second study sought to improve the method that industry uses to determine the sensitivity of compounds to impact. This method is particularly important in measuring the safety of handling explosive compounds in transport, and in storage. The apparatus used presently involves the dropping of a weight from a height onto a small sample, which is confined in a specially designed enclosure. A positive result only occurs when enough energy was supplied to cause an explosion. Whether a result is positive or negative is somewhat open to the interpretation of the operator. Signs of a positive result include smoke, piercing of a diaphragm, or the formation of a dark residue within the sample enclosure. The amount of potential energy (height x weight) required to cause a positive result in at least 50% of tests is termed the sensitivity value. Used in this conventional fashion, the instrument produced a single YES/NO decision per experiment. Many experiments were required to characterize each sample, in what is a very tedious procedure. In this present work it is shown that acoustic emission can be used to effectively monitor controlled explosive reactions occurring within the drop weight tester sample cavity. The acoustic emission resulting from the impact was captured using a broadband transducer mounted on a clip, which rested on the sample holder. Frequencies from 100 kHz to 1 MHz were captured. This has resulted in an automatic method for distinguishing between a positive and a negative result in calibration and solid sample tests. Spectrogram (plots time vs. frequency emission) analysis suggests that acoustic emission may be used to probe the mechanism of the explosion within the sample container. The high irrepeatability of results for the nitromethane samples was due to the piercing of the "O-ring" surrounding the sample, rather than the expected rupture of the diaphragm situated above it. The results show that better design of the present drop weight apparatus must be undertaken to improve the reproducibility. Acoustic emission will provide a useful means to quantify that improvement. i v TABLE OF CONTENTS Page Abstract » Table of contents iv List of Tables vii List of Figures . viii Glossary . xl Acknowledgement • xiv I. Chemical Acoustic Emission 1 1 Introduction 1 2 Principles of Acoustic Emission 3 3 Acoustic Wave Types 8 4 Detection of Acoustic Emission 9 5 Factors Affecting the Signal 12 6 Acoustic Emission Instrumentation 12 7 Signal Analysis 15 II. Industrial Electrolysis 18 1 Introduction 18 1.1 Industrial Electrolysis of Water 19 V 11.2 Experimental 22 2.1 Reagents 22 2.2 Apparatus 22 2.2.1 Transducer and Signal Conditioning Electronics 27 2.2.2 Data Acquisition Systems 27 2.2.3 Software 28 2.3 Method 29 2.3.1 Confirmation of Frequency Response Curve :....29 2.3.2 Calculation of the Decomposition Voltage of Water Electrolysis 29 2.3.3 Measurement of Steady-state Emission Rates..... 30 2.3.4 Capture of Individual Emissions During Steady-state Operation 30 2.3.5 Monitoring Possible Oxide Coating at Start of Electrolysis 31 2.3.6 Direct Volumetric Measurements of Gas Evolution 31 11.3 Results and Discussion 33 3.1 Decomposition Voltage Determination.. 33 3.2 Quantitation of Steady-state Emission Rates 34 3.3 Spectral Analysis of Electrolysis Acoustic Emission 39 3.4 Variation of Signal Characteristics with Applied Potential 47 3.5 Detection of Surface Coating 50 3.6 Possible Sources of Acoustic Emission 53 11.4 Conclusions 58 11.5 Further Work 59 v i III. Acoustic Emission Monitoring of the Sensitivity of Chemicals to Impact 60 1 Introduction 60 1.1 Introduction to Explosives 60 1.2 Drop-weight Testing 61 1.2.1 Compression Ignition 65 111.2 Experimental 66 2.1 Reagents 66 2.2 Apparatus 66 2.3 Method 70 2.3.1 Initial Experiments 70 2.3.2 Water Calibration 70 2.3.3 Liquid Propellant Test 73 2.3.4 Solid Explosive Test. 73 111.3 Results and Discussion 75 3.1 Initial Modification of the Drop-weight Tester 75 3.2 Frequency-time Spectra for Liquid and Solid Sample Holders (no sample) 75 3.3 Water Calibration 79 3.4 Spectrogram of Water ...83 3.5 Liquid Sample Test for Nitromethane 83 3.6 Spectrogram of Nitromethane 88 3.7 Solid Sample Test for Ammonium Dichromate 88 3.8 Spectrogram of Ammonium Dichromate 91 111.4 Conclusions 96 Literature Cited 97 v i i LEGENDS TO TABLES Page Table 1 a) Time-domain Descriptors 17 b) Frequency-domain Descriptors 17 Table 2 Approximation of the size of bubbles in the electrolysis of water 44 Table 3 Correlation of signal descriptors with applied potential 49 Table 4 Procedure for calculating the sensitivity value of explosives 72 Table 5 Correlation of acoustic RMS (root mean square) values with positive and negative results for water calibration. Positive results always show a higher RMS value 82 Table 6 Lack of correlation between acoustic RMS values and positive and negative results for nitromethane. The table shows the ^reproducibility of the RMS values 87 Table 7 Correlation of acoustic RMS values with positive and negative results for ammonium dichromate. The table shows that RMS values could be used to decifer whether a result is positive or negative 92 v i i i LEGENDS TO FIGURES Page Fig. 1 Mechanism for dislocation propagation 5 Fig. 2 Mechanism for crack formation and growth 6 Fig. 3 Frequency response from transducer used in electrochemical experiments (reproduced with permission by Bruel & Kjaer, Bruel & Kjaer Instruction manual) 11 Fig. 4 Apparatus for the frequency response measurement from a transducer 23 Fig. 5 Experimental apparatus for monitoring acoustic signals from an electrochemical cell 24 Fig. 6 Circuit diagram for voltage control device .....26 Fig. 7 Experimental apparatus used for volumetric gas studies 32 Fig. 8 Comparison of a current against voltage plot with an acoustic RMS against voltage plot, a) has been extrapolated to find the decomposition voltage, b) has had the background subtracted, and can be used to estimate the decomposition voltage 35 Fig. 9 Chart recorder trace of the raw and integrated acoustic signal, showing the effect of changes in applied potential on rate of emission. The integration shows three linear portions due to the different voltages applied (hence the change in observed rate 36 Fig. 10 Plots of total acoustic emission against volume of gas produced, which shows the linearity between total acoustic emission and volume of gas evolved 38 Fig. 11 Frequency response of the transducer used in the electrolysis experiments (Signal intensity increases with decrease in log of voltage) 40 i x Fig. 12 Comparison of raw average power spectra from an electrolysis cell. Spectra at 1.4 or 1.6 volts indicate background noise. Spectra at 1.8 to 2.6 volts show copious gas evolution 41 Fig. 13 Background spectrum (1.6 volts) .42 Fig. 14 Background-subtracted average power spectrum for hydrogen evolution at the Ni electrode, using 1.0 M NaOH. The spectrum for 1.6 V has been subtracted from the spectrum taken at 2.6 V 43 Fig. 15 Response surface from the electrolysis cell showing the combined effects of electrolyte concentration and applied potential on the acoustic emission. The contour and surface plots show acoustic power increasing with applied voltage and electrolyte concentration. The acoustic power decreases for electrolyte concentrations > 1.5 M NaOH 45 Fig. 16 Correlation of mean values of frequency mean and frequency median signal descriptors with applied potential. The plot indicates the consistent frequency content appearing in the power spectra 48 Fig. 17 3-D surface indicating that the frequency spectrum is changing over time. The spectrum is taken at the nickel electrode while it is producing oxygen. The change in the spectrum suggests that another process is occurring 51 Fig. 18 3-D surface indicating that the frequency spectrum is changing over time. The spectrum is taken at the nickel electrode while it is producing hydrogen. The change in the spectrum suggests that another process is occurring 52 Fig. 19 Principal Component Analysis showing the clustering of signals from surface coating (A) and bubble emission (B,C) 54 Fig. 20 Time and frequency-domain signals for a) bubble emission and b) surface coating emission 55 Fig. 21 Possible sources of acoustic emission 57 Fig. 22 Drop-weight testing apparatus 62 Fig. 23 Sample holder for liquid samples 67 Fig. 24 Sample holder for solid samples 69 X Fig. 25 The above trace indicates that the bounce occurs at 360 ms. This enabled the window to be reduced for further experiments, eliminating the noise associated with the bounce 76 Fig. 26 Spectrogram for the liquid sample holder with no sample present (blank)...77 Fig. 27 Spectrogram for the solid sample holder with no sample present (blank) 78 Fig. 28 Time-domain signal for the calibration of the apparatus using water. The result is negative, and if a larger time window had been used, a bounce would have been seen at 360 ms..... 80 Fig. 29 Time-domain signal for the calibration of the apparatus using water. The result is positive, and would not show a bounce if the time window had been extended to 360 ms 81 Fig. 30 A positive result: This surface shows a decrease in intensity of a peak at 300 kHz after 1.2 ms followed by an increase in the peak intensity due to rupture of the diaphragm and subsequent release of water vapour....84 Fig. 31 A negative result shows a decrease in intensity of the 300 kHz peak after 1.2 ms. The diaphragm does not rupture, and so the 300 kHz does not increase thereafter 85 Fig. 32 Time-domain signal for a typical negative result from nitromethane 86 Fig. 33 Spectrogams showing the inconsistency of negative results for nitrometane samples. The variability in the spectra is due largely to the liquid sample holder. The diaphragm did not rupture, but rather the sample scored the O-ring and escaped through the side 89 Fig. 34 Typical time-domain signal for the ammonium dichromate solid sample 90 Fig. 35 Frequency spectrum for the detonation of ammonium dichromate at 182.5 Kg cm There is an intense peak around 900 kHz which appears for a positive result. The intensity of a positive result is greater than a negative result 93 Fig. 36 Frequency spectrum for no detonation of ammonium dichromate at 182.5 Kg cm The peak around 900 kHz is not so pronounced as that for a positive result 94 GLOSSARY x i a constant in Tafel Equation 00 coefficient for Kalman Filter a.c. alternating current A.E. acoustic emission b constant in Tafel Equation b\ coefficient for Kalman Filter bi coefficient for Kalman Filter ci coefficient for Kalman Filter C2 coefficient for Kalman Filter d coefficient for Kalman Filter D A C A data acquisition and control adapter DACO digital-to-analog convertor output d.c. direct current Eceii applied potential E°cei i theoretical cell potential E 5 0 point at which the probability of explosion is 50 % f frequency fr approximate resonant bubble frequency F Faraday's constant FFT fast Fourier transform 1 current ic current density I"F Faradaic current density I.D. inner diameter n number of data points in a record A/cai number of points in the calibration set number of fitted parameters number of points in the test set outer diameter power atmospheric pressure principal components analysis lead zirconate titanate bubble radius rate of reaction resistance random access memory root mean square standard error of estimation standard error of prediction soft independent modelling of class analogy three dimensional time resolved average power spectra average value of the signal voltage of one data point root mean square voltage applied potential parameter electrolyte concentration parameter total acoustic power calculated response observed response number of electrons involved in the reaction anodic overpotential cathodic overpotential density of liquid medium population standard deviation surface tension specific heat ratio of a gas x i v ACKNOWLEDGEMENTS I wish to thank Oli-oil, Kev-the-bev, Hell's Bell's, Ives, Pat, Adrian-dodger-bourbon-biscuit, Bruce-bicep, Paul, Peter, Megs (for her mindless ability to write gobbledegook without practice), Pat-the-nap, and Steve for their overall friendship, and especially their tea-making abilities. I feel happy with computers now, and considering no previous knowledge of them, I feel a distinct amount of tolerance must have been provided by everyone who helped me. Thanks must also go to the big boss (Adrian Wade), whose patience, and remarkable ability to get money and things done at the last minute, made working for him very pleasant. Thanks must also go to Ram Gopal and Nancy Brown, for their technical help; and to glassblowers, Sean and Steve; electricians, Mike, Brian, and Milan; and mechanical shop workers, Bryn, Brian, and Dick. CREDITS This work was made possible by Grant 5-50886 from the Institute for Chemical Science and Technology, and matching Grant 5-80389 from the Cooperative Research and Development Program of the Natural Sciences and Engineering Research Council of Canada. 1 CHAPTER I Chemical Acoustic Emission 1.1 I N T R O D U C T I O N This thesis reports on the chemical acoustic emission from two different chemical systems; namely, the electrolysis of water, and the explosion of impact-sensitive compounds. The advantages of this acoustic technique over unsatisfactory techniques presently employed are discussed. Acoustic emission has only recently been used for chemical analysis, but there are many examples throughout history of the use of acoustic emission. Potters, as early as 6500 B.C., used audible acoustic emissions to determine whether their clay was cooling too quickly in the kiln. A cracking noise enabled the artisan to detect defective creations [1]. Acoustic emission has been used by material scientists since the 1920s, their work has resulted in theories for deformation, cracking, and other physical processes in metals and plastics [2-10]. The Acoustical Society of America and the Journal of Acoustic Emission were founded in order to cope with the enormous amount of acoustic emission research in metallurgy and materials science. The 1980s also established acoustic emission in the world of the wood products and food industries [11]. Sound waves emitted by micro-fractures in structural timber were monitored, allowing a convenient method for the grading of wood [12]. Recently, it was reported that tomato plants in need of water emitted bursts of high frequency sound [13]. The emissions stopped once the plant's water supply had been replenished. Portable acoustic emission systems have been used in research in the pulp and paper industry [14]. The applications of acoustic emission in material science, metallurgy, entomolgy, agricultural science, forestry, and seismology are numerous, but very few applications have 2 appeared in chemistry. The first chemical application of acoustic emission to appear in a thesis occurred in 1957, when Ranke Madsen used his ear to determine the end point of an acid-base titration [15]. In 1978, Van Ooijen et al. [16] prepared a crystalline solid, dichloro(pyrazine)zinc(II), by reaction of zinc chloride with pyrazine. The reaction was acoustically emissive and the intensity of sound was reported as being proportional to the concentration of both reactants. Betteridge et al [17] realized the potential of this technique in analytical chemistry from van Ooijens' work and carried out an extensive acoustic emission study of 43 different chemical reactions and mixing processes. The research was seminal in that it demonstrated that acoustic energy was commonplace in certain types of reactions. Since then, various chemical acoustic emission studies have been conducted. Thermosonimetry (the study of sound emitted during the heating or cooling of a substance) was applied to phase transformations [18]. Lsnvik was able to show that the thermosonimetric activity of brucite (Mg(OH)2) depended on the site from which it was mined [19]. Sawada et al. [20] studied phase transitions of /?-cresol, water, and methyloxybenzilidene-4-n-butylaniline (MBBA) liquid crystals, and found that the acoustic activity started at the onset of the phase transition and ceased upon its completion. Sawada et al [21] later, went on to study the emissions arising from the reaction of sodium carbonate and calcium chloride to form the gelatinous calcium carbonate. The microfracture processes and release of trapped gases during the melting of ice are acoustically active [22]. Most recently, Lee et al. [23] studied the solid-solid phase (II/III) transition of hexachloroethane and established that the acoustic activity correlated with dilatometric measurements. Acoustic emission studies based on the stressing of polymers, plastics, and glass-fibre composites occurred in the early 1980s [24]. Belchamber et al studied many polymer and glass-fibre systems and analyzed the signals using advanced statistical techniques [25], such as Principal Components Analysis (PCA). The acoustic emission was believed to result from different fracture processes, where each provided their own class of 3 signal. These types of signal were established by pattern recognition techniques. Two very recent applications of chemical acoustic emission involve gas evolution processes. Firstly, a method was reported in which bovine liver catalase was immobilized onto the surface of a transducer in order to monitor the conversion of hydrogen peroxide to oxygen and water [26]. Secondly, the ultrasonic acoustic emission from an alkaline electrolysis cell has been studied; this is the basis for chapter 2 of this thesis [27]. 1.2 PRINCIPLES OF ACOUSTIC EMISSION Definition Acoustic emission is a transient elastic wave caused by a rapid localized supramolecular event within (or on the surface of) a material. The energy emitted in the case of chemical acoustic emission could be the direct result of the system attempting to reattain equilibrium. The frequency spectrum of acoustic emission is very large, ranging from infrasonic (< 16 Hz), through audible (16 Hz - 16 kHz), to ultrasonic (16 kHz - > 25 MHz). Earthquake studies and exploration seismology involve frequencies ranging from 0 to 100 Hz. Laboratory and field geological studies monitor frequencies up to 10 kHz. Frequencies of bursting bubbles are typically found in the audible region of the frequency spectrum. Frequencies above 100 kHz arise from acoustic emission from metals, plastics, and chemical reactions. So far, there has been no chemical acoustic emission reported above 1 MHz, although this may reflect the limitations of present apparatus and the range of reactions studied. 4 Acoustic Emission Sources There are at least five sources of acoustic emission which are of major importance to chemical systems. 1) Dislocation Movements Crystal arrangement of atoms in metallic materials is seldom perfect. Defects may be caused by vacant sites, impurities, or interstitially placed atoms. Dislocation can determine the behavior of metals and alloys [28]. A dislocation in its simplest form consists of an extra plane or line of atoms within the crystal (Fig. 1). When a collective number of atoms move then acoustic emission results. 2) Crack Formation, Growth, and Friction A crack forms when the localized force is greater than the force required to break the bonds between atoms (Fig. 2). This results in intense acoustic emission. Once the crack has been formed, propagation occurs rapidly, and friction movements between planes cause bursts of acoustic emission. 3) Phase Transformation Acoustic energy is released when some materials rapidly transform from one crystal structure to another (as a result of temperature or pressure changes). This is the result of the rearrangement of atoms (e.g. the solid-solid phase (II/III) transition of hexachloroethane [23]). 4) Boiling and Bubble Evolution In many instances the boiling of substances results in the release of gas bubbles which collide with each other and surroundings, and eventually reach the surface and collapse. Furthermore, most emission is not from surface collapse, but from pre-boiling 1 2 3 4 5 Crystal contains an extra line of atoms (shaded black) Under a load, columns 3 and 4 slip with respect to columns 1 and 2 — Dislocation has moved The result is that the dislocation has moved and releases acoustic energy. Fig. 1 Mechanism for dislocation propagation 6 Cracks form at areas where the local stress concentration exceeds the fracture strength of the material (e.g. at surface irregularities) The load which was carried by AC" broken atomic bond at the - v | \ / \/ x**A.L. crack tip is transferred to the adjacen releasee bond and energy is The acoustic emission results from many bonds breaking Fig. 2 Mechanism for crack formation and growth 7 (collapse before reaching the surface). This collapse of the bubbles releases high frequency emissions. The release of acoustic emission can be seen in electrolysis cells with the evolution of gas bubbles [29], although pre-boiling does not apply in the electrolysis cell. 5) Explosion The rapid release of explosion products is often associated with a substantial amount of acoustic emission {e.g. the explosion of nitromethane ( C H 3 N O 2 ) to form reactive intermediates C H 3 N O , O , and then final reaction products which include methane and carbon dioxide}. 6) Cavitation / Implosion Cavitation involves the formation and collapse of microbubbles when ultrasonic waves are applied to the solution. The microbubbles can behave in two different ways. They can either be stable and oscillate about their mean size, or they can be unstable and grow, before violently imploding. The consequent shock waves have been known to cause sonoluminescence. The implosion creates, momentarily, local pressures of up to several GPa and local temperatures from 103 to perhaps 106 K. For example, benzene can be oxidized using ultrasound in an aqueous media into phenol and, surprisingly, nitrogen-containing compounds [29], but proves resistant to the strongest oxidant. 8 1.3 A C O U S T I C W A V E T Y P E S Wave Propagation in Solids For solids there are many modes of propagation for acoustic waves, and they will be discussed below. Bulk Waves When an acoustic wave travels through a medium whose dimensions are greater than the acoustic wavelength, two types of bulk waves can exist; a longitudinal and a transverse wave. Longitudinal (compression) waves are transient waves that oscillate parallel to the direction of wave propagation. Transverse (shear) waves oscillate perpendicular to the direction of propagation. Surface Waves Rayleigh and Love waves can be created due to the anisotropy of the coupling forces between atoms at the surface of a bounded solid. Rayleigh waves are commonly seen because the plane of oscillation is perpendicular to the surface, and therefore are easy to detect by a transducer. However, Love waves are seldom seen because the plane of oscillation is parallel to the surface. Plate Waves Plate (Lamb) waves are surface waves which result when a solid is bounded by two surfaces and the plate is several acoustic wavelengths thick. Wave Propagation in Liquids In liquids, surface and P-waves (compressional wave) are the only two types of wave that can exist. 9 Wave Propagation in Gases P-waves are the only mode of propagation for an acoustic wave in a gas. The wave velocity (v), frequency (f), and wavelength (A) , are related by v = f A The waves can exist in any material, and the velocities of the waves varies considerably. The velocities of longitudinal, shear, and Rayleigh waves in steel are 5940, 3250, and 3030 ms"*, respectively. Typically, transverse or shear waves travel at a little over half of the P-wave's velocity. 1.4 DETECTION OF ACOUSTIC EMISSION Sensors Transducers, a hybrid Latin word meaning to "lead across", are devices that convert one form of energy into another form of energy. In the case of acoustic emission, sound energy is converted into electrical energy. The discovery of piezoelectricity by Pierre and Jacques Curie [29] in 1880 led ultimately to the development of the high frequency acoustic emission transducers used today. When placed under pressure, Quartz, ammonium dihydrogen phosphate, and Rochelle salt all produce an electrical potential between certain surfaces, and are thus called piezoelectric materials. Ferroelectrics have now replaced the single crystal piezoelectric materials, but are essentially the same as the original piezoelectric devices. The difference is that no strain is required to produce polarization in the ferroelectric material, because the material already has a polar axis. Today, almost all acoustic emission sensors are made from ferroelectric ceramics of various types [30]. The lead zirconate titanate (PZT) transducers, 10 manufactured by the Acoustic Emission Technology Corporation are examples of ferroelectric transducers. Several factors can effect the performance of the transducer; namely, size, couplant, and temperature. The world meeting on acoustic emission in 1989 led to an article entitled "The General Problems of A E Sensors" [31]. Some of the problems identified are discussed below. Use of a coupling agent is essential for the effective detection of low level signals, since this fills the microscopic gaps between the surfaces. The coupling agent should always be appropriate for the sample used, especially if extreme temperatures are involved. Typical couplants include petroleum grease, high vacuum stop cock grease, dental cement, and water. Transducers constructed from ferroelectric materials must be used within known temperature ranges, because at higher temperatures a transformation to a new nonferroelectric phase might occur. Depending upon the application, the transducer can be of the resonant type (having a single frequency band at which it responds with much more sensitivity than all others), or of the broad band type. A broad band transducer, as used for acoustic spectral analysis, should ideally have a flat frequency response over a wide range (some have a flat frequency response over a range of 50 kHz to 2 MHz). The typical frequency response curve for a broad band transducer is shown in Fig. 3, and is far from flat. dB re, 1 V/ms~1 Brtiel & Kjtor BrOel & Kjier 100 kHz 2 0 0 3 0 0 4 0 0 6 0 0 6 0 0 7 0 0 8 0 0 900 1 MHz 1,1 1,2 1,3 1,4 1,5 FREQUENCY Fig. 3 Frequency response from transducer used in the electrochemical experiments (adapted with permission from Druel & Kjaer, Bruel k Kjaer instruction manual). 12 1.5 F A C T O R S A F F E C T I N G T H E S I G N A L The actual waveform at source would be hard to determine from the digitized waveform since there are many factors that will modify the waveform. The observed digitized waveform is a function of many factors, namely: 1) Sample 2) The multiple paths that the signal can take from the source 3) Sample vessel 4) Couplant 5) Transducer (electronics, resonances, and temperature effects) 6) Preamplifier and filters 7) Cabling and screening 8) Conditioning amplifier (gain and bandwidth) and filters (bandwidth and roll-off) 9) Cabling 10) Digitizer (resolution, record length, and sampling rate) 1.6 A C O U S T I C E M I S S I O N I N S T R U M E N T A T I O N The sensing apparatus required for acoustic emission is very simple. The transducer is mounted either onto the vessel containing the sample or onto the sample itself. Waveguides, such as described by Clark [32], may be used in experiments where the temperature exceeds the maximum operating temperature of the transducer. The output of the piezoelectric element is sometimes preamplified, then sent to a conditioning amplifier. 13 Signal Conditioning Most acoustic emission monitoring systems require a conditioning amplifier. This provides: 1) a selectable (variable) gain 2) bandpass filters which prevent aliasing and decrease detection of unwanted noise, whilst allowing passage of as much of the desired signal as possible. Signal Capture A transient digitizer enables the signal to be digitized in real time and stores the signal in Random Access Memory (RAM). The contents of this memory can then be transferred to a computer for the operator to interpret at their leisure. One essential requirement for adequate digitization is to sample the signal at a fast enough rate. The Nyquist frequency is one-half of the sampling frequency in a digital system. The Nyquist theorem states that the frequency information in a signal will be retained only if the signal is sampled at a rate which is at least twice the frequency of the highest digitized frequency component. If a signal is sampled at less than this rate, frequencies higher than the Nyquist frequency are reflected back into the observed frequency spectrum (i.e. they "alias" as apparently lower frequency components). The process of aliasing distorts the waveform and prevents the true original waveform from being recovered. Aliasing of high frequency components can be prevented by using a low pass filter in the conditioning amplifier, and by sampling at a rate equal to (or greater than) twice the highest frequency component remaining. A fast storage oscilloscope is a commonly used transient digitizer. This can acquire and digitize input signals, process the information in a variety of ways, and display or store the results. The Tektronix 2430A, and 2230 oscilloscopes are suited to acoustic emission monitoring and can sample at rates of up to 100 MHz. Each can send data to personal computers across an IEEE-488 high-speed parallel instrumentation interface. However, 14 the time to store the waveform is much greater than that needed to acquire it, and consequently many emissions can be missed. Quantification of signals RMS measurement The waveform captured is in the form of a series of n voltage readings, V\, taken at equal time intervals. The root mean square (RMS) voltage of the signal, FRMS, gives an indication of the total energy of the signal. KRMS = (1/n • E * ? ) V 2 n = i The RMS values of each signal do not indicate the true RMS output of the chemical system, since only a fraction of the total acoustic events are usually captured, and significant time periods can occur without acoustic emission. The true RMS voltage, over all signals, can be obtained in an analog fashion by coupling the a.c. output of a conditioning amplifier to a "True RMS" meter (which has a time constant of 1.6 s). This is particularly meaningful when the signal is continuous, or for slowly decaying signals. Analog Chart Recorders When the d.c. output is connected directly to the input of the chart recorder, a spike (of height proportional to the peak signal voltage) is seen on the chart recorder whenever an emission occurs. The d.c. output has a time constant of 200 ms, which is slow enough for the chart recorder to register a response. Given 2 channels, the recorder can also be used to display (e.g.) temperature, pressure, or pH measurements simultaneously with acoustic emission. An analog signal indicating the integrated acoustic emission level can be sent from the computer back to the chart recorder to provide an indication of total and rate of emission vs. time. 15 Slow Digital Acquisition Data Acquisition and Control Adapters (DACA) can be used to digitize the d.c. output of the conditioning amplifier, with 8, 12, or 16-bit precision and acquisition rates of upto 10 kHz. The RTT 815F board by Analog Devices can be programmed to act as a slow digitizer. This board has the advantage of having direct memory access (DMA) capabilities to the computer. This allows the effective record length to be limited only by the memory available to the computer, and facilitate faster data processing speeds. 1.7 S I G N A L A N A L Y S I S Much of the work in acoustic emission depends on statistical techniques to extract information from extensive and somewhat nebulous data sets obtained. Several scientific papers have reported using various strategies for analyzing chemical acoustic emission signals [33-39]. The raw digitized acoustic emission signals (signal amplitude vs. time) are not of a form well suited to pattern recognition; this has led to the use of numeric descriptors to represent the key attributes of the waveforms. Previous workers [39] have utilized 5 descriptors - peak amplitude, pulse duration, rise time, half-life, and RMS - to characterize a time-domain signal. Table la indicates the time-domain descriptors typically used in this research group. Providing that the Nyquist frequency condition has been satisfied, a Fast Fourier Transform (FFT) may be used to generate a frequency-domain representation of the signal, from which frequency-domain descriptors may be calculated (Table lb). A Fast Fourier Transform (FFT) transforms the time-domain signals into the frequency-domain. The number of descriptors generated has increased each year as new ones prove their usefulness. The processing of a 1024-point raw signal provides information at 512 frequencies, which are preferably viewed as a power spectrum. The frequency (power) spectrum information is a valuable means of characterizing a set of signals. Far more reproducible results are obtained if the power spectra of all signals captured over the entire experiment are averaged to produce an average power spectrum. Time-resolved Studies The progress of reactions can be monitored by following changes in acoustic emission intensity and frequency content. For this, the reaction is divided into time intervals (ms, s, min, etc.) and the frequency spectra of signals occurring within each time window are averaged; this is achieved by a program written in this laboratory called TRAPS (Time-Resolved Average Power Spectra). A variant on this is the time-resolved total power spectrum, in which the power spectra of all signals occurring within each time window are summed. This provides a better feel for the intensity and rate of reaction. Pattern Recognition Studies In most cases, waveform descriptors (e.g. root mean square, area, peak, frequency maximum, etc.) are generated from both the time and frequency domains of each signal captured. Once the values for the descriptors have been calculated, pattern recognition, principal components analysis (PCA), dendrograms, and SIMCA can be performed. PCA aids in visualizing discrete signal classes and correlations between descriptors, dendrograms help the operator visualize distinct categories in the data, and SIMCA is used to help assign data to predetermined classes. All of these strategies have been discussed in detail elsewhere [33-47]. Correlation Studies Correlation of the descriptors with parameters from the experiment is another useful technique to understand the process being monitored, and has been discussed previously [48]. Table la- Time-domain descriptors 17 D E S C R I P T O R PEAK RMS AREA CREST 50-CROSS 25-CROSS 10-CROSS 0-CROSS KURTOSIS HALF-LIFE 1/8T-8/8T D E F I N I T I O N Largest positive or negative amplitude in signal Root mean square (RMS) voltage over all data samples Summation of the absolute voltage values Ratio of PEAK to RMS Number of crossings at ± 50% maximum possible amplitude Number of crossings at ± 25% maximum possible amplitude Number of crossings at ± 10% maximum possible amplitude Number of crossings of signal mean voltage Fourth statistical moment Time to half area Normalized RMS of signal in each l/8th of the waveform D E S C R I P T O R F R Q - M A X F R Q - M E D F R Q - M E A N F - C R E S T F B W ( 1 5 % ) F - Q R T L B W D F B 1 - D F B 8 Table lb- Frequency-domain descriptors  D E F I N I T I O N Frequency with highest intensity in power spectrum Median frequency Mean frequency Power spectrum crest factor Bandwidth of frequencies which have power >15% of FRQ-MAX Interquartile bandwidth of power spectrum Power present in Defined Frequency Bands (usually l/8th's of the power spectrum, but user definable) 18 CHAPTER II Industrial Electrolysis II. 1 I N T R O D U C T I O N Electrolysis has played an important part in chemistry since the 18th century. Current and voltage measurements are typically used to monitor electrochemical reactions in a non-destructive manner. Direct measurement of current becomes impracticable in industrial electrolyzers because such high current densities are involved. Furthermore, other electrochemical reactions taking place within the reaction vessel (corrosion of nickel anode by chlorine impurities) can distort any current measurements obtained. Little effort has been invested into looking for new technologies for monitoring such reactions, which typically proceed inside sealed vessels. Acoustic emission offers one non-invasive method which can be implemented in the electrochemical industry. Electrochemists have already taken advantage of ultrasonic emissions to study the corrosion in Type 304 stainless steel [48] and other electrode materials [49], and bubble nucleation rates have been determined by Lubetkin using audible emissions [50]. 19 II . l . l I N D U S T R I A L E L E C T R O L Y S I S O F W A T E R The first electrolysis of water was in 1789 by van Troostwijk and Deimann [52], who used static electricity to drive the reaction. However, the limitations of the machine producing the static electricity prevented study of the chemical reaction. Industrial electrolysis of water is achieved by passing an electrical current through an aqueous solution of an inorganic acid such as sulfuric acid or an alkali metal hydroxide such as sodium hydroxide or potassium hydroxide. An alkaline medium is preferred because there are fewer corrosion problems and the cheaper structural and electrode materials can be used. The concentration of the electrolyte is 20-25 wt% since such values give close to optimum conductivity at the operating temperature (typically 70-80 °C). Electrolysis requires pure water, since chloride ion (a common impurity in water) causes pitting of the passive films formed on the metal surfaces in alkali. A detailed knowledge of the factors which affect the energetics and kinetics of electrode processes is a prerequisite for optimization and efficient operation [53-56]. The rate of energy supply to the cell is simply the electrical power, P (Watts), which is the product of ic, the current passed (amps), and Eceii, the applied potential (volts). The total energy (which is the principal operating cost of the process) is obtained by integrating this over time. The efficiency of electrolyzers is perhaps only 70-80 %, as E c e i i is, by necessity, substantially higher than the theoretical value, E°ceii , derived from the free energy of the process. Reasons for this unfavorable situation include the high internal electrical resistance of the electrolyzer and high overvoltages experienced at both the anode and cathode. These contributions may be summarized: E°cell = E°Cathode " E°anode Ecell = E°Cell + l'cR + V anode + ^cathode where r/anode and r? cathode are the overpotentials, and R is the specific resistance per unit 20 surface area. The resistance term includes the "ohmic drop" due to the electrolyte and diaphragm, and its initial increase due to bubble curtain formation [57]. The half-cell reactions for the electrolysis of water are: Cathodic half-reaction Anodic half-reaction Overall reaction 4H20 + 4e--> 4H + 40H" 40FT-+ 40H + 4e" 2H20^ 2H2 + 02 4H- 2H2 40H^ 2H20 + 02 AG° = 474.4 kJ.mol1 E°cathode = -0.83 V E ° a n o de = +0.40 V E°ce„ = -1.23 V A major objective of industrial electrochemistry is to achieve the maximum yield of product (here, primarily H2) per unit time, and per unit cell volume, with the minimum energy consumption. Current efficiency, fractional conversion and rate of reaction must all be considered. It has been estimated that a 100 mV decrease in the potential which must be applied could decrease the energy requirements of one major industrial company such that a direct saving of perhaps $1M per annum per site might be achieved. The most obvious place to seek such a gain is in lowering the overpotentials, and much effort has gone into seeking out electrode materials and coatings which improve efficiency in this way (e.g. Ru02-coated titanium substrates [58]). Typically, the older electrolyzers used iron as a cathode because of its low hydrogen overvoltage, and nickel is used as an anode due to its low oxygen overvoltage. Modern electrolyzers now use nickel plated onto steel for the anode and Raney nickel for the cathode. In modern cells high surface areas are preferred. Platinum, although it has low oxygen and hydrogen overvoltages, is far too expensive for commercial application. In the last 10 years some electrolyzers have been based on "acidic" solid polymer electrolytes [59]. These solid polymer electrolytes were first developed for the NASA space programme, and were later employed in military applications. The solid polymer electrolyte has the most impressive overall performance of all the electrolyzers; its properties include high current densities, low overvoltages, reduced membrane thickness (which lowers the potential drop in the electrolyte), and high operating temperature (which promotes conductivity and reduces overvoltages). Development of non-invasive, real-time sensor techniques which are capable of monitoring the electrochemical processes occurring on the surfaces of electrodes is of significant industrial interest, especially since current measurement (which is traditionally used to monitor electrochemical reactions) is not viable for high current density electrolyzers, such as the alkaline water electrolyzer. This chapter outlines an acoustic emission monitoring approach as a possible sensor for such systems. 22 II.2 E X P E R I M E N T A L 11.2.1 R E A G E N T S Electrolyte solutions of sodium hydroxide (0.1, 0.2, 0.3, 0.4, 0.5, 0.9, 1.0, 1.2, 1.5, 1.8, 2.0, and 2.1 M) were prepared from sodium hydroxide pellets (AnalaR grade, BDH, Toronto, Ontario). Nickel chloride solution (1.0 M) was prepared from the solid (BDH Chemicals Limited, Poole, England). 11.2.2 A P P A R A T U S The apparatus (Fig. 4) required for the determination of the frequency response characteristics of the detection transducer involved an emitting transducer (Model FAC500, Acoustic Emission Technologies Inc., Sacramento, CA) which had a well characterized flat response between 100 kHz and 2MHz. The detection transducer was a broad-band piezoelectric device (Model 8312, Bruel and Kjaer, Naerum, Denmark) with a built-in 40 dB preamplifier. The excitation source for the emitting transducer was a frequency generator (Model F-52A Wavetek, Interfax, Vancouver, B.C.), which provided a continuous sinusoidal output voltage of the appropriate frequencies. The output of the detection transducer was sent to a digital storage oscilloscope (Model 2430A, Tektronix, Beaverton, Oregon), so comparison of the detection signal could be made with the excitation signal. Experiments to investigate the electrolysis start-up kinetics, measure steady state emission rates and capture individual signals used the apparatus shown in Fig. 5. The anode was a stainless-steel rod of circular cross-section and 120 mm in length by 7 mm in diameter. The cathode was a nickel rod of the same dimensions. The two electrodes were immersed in 1.0 M sodium hydroxide solution to a depth of 1.5 cm. Both had a 4 mm 23 EMITTING TRANSDUCER FREQUENCY GENERATOR (CONTINUOUS SINE WAVE) COLLECTING TRANSDUCER CONDITIONING AMPLIFIER CH. 1 CH. 2 OSCILLOSCOPE Fig. 4 Apparatus for the frequency response measurement from a transducer P C - A T 24 DATA BUS CONDITIONING AMPLIFIER TWO PEN CHART RECORDER IBM DACA BOARD APPARATUS FOR CAPTURING INDIVIDUAL SIGNALS DIGITAL SIGNAL OUT TO COMPUTER 0 0 t \ J TEKTRONICS 2430A DIGITAL SCOPE VOLTAGE CONTROL REFERENCE ELECTRODE COUNTER ELECTRODE TRANSDUCER MOUNTED ON WORKING ELECTRODE GLASS APPARATUS CONTAINING NaOH Fig. 5 Experimental apparatus for monitoring acoustic signals from an electrochemical cell 25 diameter hole drilled transversely through their upper end to form a socket suitable for connection to the voltage source, a laboratory power supply (Model LXD20, Xantrex, North Vancouver, B.C.). The top 80 mm of each electrode was machined flat to allow good contact with the acoustic sensor, which was mounted on the working electrode with insulating tape. A layer of stopcock grease (Apiezon Type L, Fisher Scientific, Richmond, B.C.) was applied between the working electrode and the transducer to enhance acoustic coupling. Unless otherwise stated, a thin layer of Teflon tape was used to prevent any leakage of current from the working electrode through the transducer to ground, and so obviate any electronic interference that this might cause. A saturated calomel reference electrode (Fisher Scientific, Richmond, B.C.) completed the apparatus. The applied potential was controlled through a simple power amplification circuit (Fig. 6.) designed in this laboratory. The target voltage to be applied across the working and counter electrodes was set using one of the two digital-to-analog converters of the Data Acquisition and Control Adapter ((DACA), IBM Instruments, Boca Raton, FL), situated in an Intel 80286-based P C / A T microcomputer (NORA Systems, Vancouver, B.C.). To ensure adequate accuracy, this 12-bit resolution card also re-read the supplied voltage via an analog-to-digital convertor. Additional current and potential readings were made with a digital multimeter (Model D M 25L, Beckmann Industrial Corporation, Brea, CA). All studies were done in a three-compartment glass cell constructed in this department (Fig. 5). Each compartment was of 125 mm depth and 70 mm internal diameter. The central chamber was connected to the counter electrode chamber by a glass conduit into which had been set a coarse porous frit of 2.5 cm diameter and 5 mm width. The reference electrode cell was partitioned from the working electrode compartment, but connected via 1 mm i.d. capillary tube. Initially, the centre chamber contained the working electrode, and the other two chambers contained the counter electrode and reference electrode respectively. In later experiments, both working and counter electrodes were present in the middle compartment, but were separated by a polyvinylchloride dividing piece of 125 mm length, 26 + 10 V + 10 V -10 V + CELL Fig. 6 Circuit diagram for voltage control device 27 70 mm width, and 7 mm thickness. This partition had a 35 mm diameter porous glass frit mounted into its center, and was sealed into the center compartment with silicone rubber (RTV General Electric Company, N.Y.). This modification allowed closer proximity of the working and counter electrodes, and higher currents. 2.2.1 Transducer and signal conditioning electronics The ultrasonic transducer used was the broad-band piezoelectric device (Model 8312, Bruel and Kjaer, Naerum, Denmark) previously characterized, which is designed specifically for acoustic emission studies. Its operation has been discussed elsewhere [24]. It derived its power from and delivered its output to a high quality signal conditioning amplifier (Model 2638, Bruel & Kjaer). This provided a switch-selectable gain of 0 to 60 dB in 1 dB steps, and several bandpass filter ranges. A 50 kHz - 2 MHz bandpass and an amplifier gain of 40 dB were chosen. The conditioning amplifier provided a d.c. peak level detect output which was connected to a high impedance input of a dual-channel chart recorder (Model SE 120, BBC Goerz Metrawatt, Vienna, Austria). The a.c. output from the conditioning amplifier presented an amplified, filtered version of the acoustic signal to the input of the digitizer. 2.2.2 Data acquisition systems The digitizer used for the decomposition voltage experiments was a commercially-available unit (Model SDA 2000, Soltec, San Fernando, CA). It was controlled across an IEEE-488 interface (Model PC-IIA, National Instruments, Austin, TX) by a PC/AT compatible microcomputer (Nora Systems, Vancouver, B.C.). Data acquisition software was as provided by the digitizer's manufacturer. Steady state emission rate measurements were made using a fast data acquisition board (Model RTI-815F, Analog Devices, Norwood, MA) mounted in a portable PC/XT 28 compatible microcomputer (Compaq Model II, Houston, TX). A digital-to-analog converter on the RTI-815F board was used to relay the computed integration of the acoustic activity to the second channel of the chart recorder. The d.c. output from the conditioning amplifier was digitized and processed, using a direct memory access method of programming, details of which have been published elsewhere [61]. The digitizer used to capture individual burst signals was a digital storage oscilloscope (Model 2430A, Tektronix, Beaverton, OR). The digitized data were transferred to a PC/AT personal computer via an IEEE-488 standard instrumentation interface and stored on a hard disk for later processing. 2.2.3 Software Data analysis software was written in this laboratory in Microsoft Quick-Basic (ver. 4.00B, Microsoft Corporation, Richmond, WA). Lotus 123 was used for some exploratory data analysis (ver. 2.01, Lotus Corporation, Somerville, MA). Commercially available graphics programs, Sigmaplot (ver. 3.10, Jandel Scientific, Sausatito, CA) and Surfer (ver. 4.10, Golden Software Inc., Golden, CO) were used to generate graphs and three-dimensional plots, respectively. 29 II.2.3 M E T H O D 2.3.1 Confirmation of frequency response curve The transducer frequency response curve (Fig. 3) was verified by using another transducer, according to the method described below. The excitation and detection transducers were placed firmly together, with a thin layer of petroleum grease as an acoustic couplant (Fig. 4) between them. A waveform generator supplied a continuous sine wave to the emitting transducer. The signal from the waveform generator and the output from the detection transducer were sent to input channels 1 and 2 of the oscilloscope, and the amplitudes of the two waveforms were compared. In this manner the response of the detection transducer was determined from 100 kHz to 2 MHz. 2.3.2 Calculation of the decomposition voltage of water The Soltec digitizer provided a single-shot record length of up to 3 Megabytes (1.5 million data readings). Each sample required 2 bytes, and was of 12-bit resolution. The start of sampling was automatically triggered by opening the switch on the power supply unit which applied the working potential. Conditions used were a sampling interval of 0.2 ms and a record length of 65,535 samples. These allowed 12.85 s of observation time. Studies were done at applied potentials of 0.0, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, and 5.0 volts. Initial data analysis was done largely using Soltec's software and a commercial spreadsheet. A data format conversion program written in this laboratory allowed further post-process data analysis using other routines also written in this laboratory. The RMS voltage of the acoustic emission signal was calculated using the Soltec software, and this was then plotted against the voltage applied. A linear extrapolation of the graph enabled an estimate of the decomposition voltage to be calculated. 30 2.3.3 Measurement of steady-state emission rates Studies were carried out at applied potentials of 1.4, 1.6, 1.8, 1.9, 2.0, 2.1, 2.2, 2.4, 2.6, 2.8, 3.0, 3.5, 4.0, and 5.0 volts. In each set of experiments the electrodes were placed into the solution at the same depth (1.5 cm) so as to maintain the same contact area of the electrode surfaces with the electrolyte. Before and after each individual experiment the current was measured by placing the digital multimeter in series with the working electrode, and the voltages of both the working electrode and the counter-electrode were measured with respect to the reference electrode. Prior to acquisition of acoustic emission signals from the electrolyte, the level of background noise was established by collecting background readings, for typically 1 minute, in the absence of an applied potential. Then, a voltage was applied, and readings were made over a period of 10 minutes. 2.3.4 Capture of individual emissions during steady-state operation The digitizer used (Tektronix 2430A) allowed multiple 1024-point by 8-bit resolution records to be acquired, one per emission signal. The sampling frequency used was 2.5 MHz. Each waveform contained 100 points collected before the trigger point. The maximum throughput of this system (capture and transfer) in its "NORMAL" acquisition mode was ca. 2 signals.s-1. Typically 200 signals were collected at each voltage using either continuous monitoring or a trigger level set at 250 mV (well above background noise). Data analysis software written in this laboratory facilitated the calculation and viewing of individual and average power spectra, application of pattern recognition and descriptor analysis techniques [48] to the signals captured, and correlation of acoustic parameters with applied potential and current. A least squares approach [60] was used to fit the data obtained to a function which accounts for the effects on acoustic emission intensity caused by the changes in concentration and voltage. 31 2.3.5 Monitoring of acoustic emission from possible oxide coating at start of electrolysis The apparatus was the same as that for the individual signal capture. Potentials of 1.9, 2.0, 2.1, 2.5, 3.0, and 4.0 volts were applied. The amplification provided by the conditioning amplification was increased to 50 dB, to improve sensitivity. Initially, 1.0 M NaOH solution was placed in the cell and the acoustic emission from hydrogen generation at the nickel electrode was monitored. Then the polarity was reversed to clean the electrode and the acoustic emission from oxygen generation was measured. 50 signals were captured using the Tektronix 2430A oscilloscope in the "FAST-TRANSMIT' mode, which allowed maximum capture rate of ca. 10-15 signals.s"^ . 2.3.6 Direct volumetric measurements of gas evolution The apparatus was set up as shown in Fig. 7. Gas volumes were collected over a period of 10 minutes at potentials of 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 volts. One side of the central compartment and one side compartment were sealed to prevent any escape of the gas being collected. 3 2 PC-AT IBM DACA BOARD t t VOLTAGE CONTOL TO GAS BURETTE 44 COUNTER ELECTRODE REFERENCE ELECTRODE WORKING ELECTRODE PARTITION - CONTAINING POROUS FRIT GLASS APPARATUS CONTAINING NaOH Fig. 7 Experimental apparatus used for volumetric gas studies II.3 RESULTS AND DISCUSSION 33 Initial experiments, conducted in 1.0 M sodium hydroxide solution in a 250 ml beaker, showed that gas evolution started to occur at applied potentials of between 1.8 and 2.0 volts and that this was accompanied by copious acoustic emission. As might be expected, hydrogen and oxygen bubble evolution were both acoustically active, with more emission coming from the hydrogen electrode due to the larger volume of gas being produced. The acoustic power spectra revealed no differences between the signals from hydrogen and oxygen evolution. The individual electrode potential and the total potential across the cell correlated linearly. The relationship between current and overvoltage followed the exponential Tafel relationship [59] v = a + b log i where r\ is the overvoltage (in volts), a and b are constants, and i is the current density (Am - 2). Initially, the working and counter electrodes were situated in separate compartments of the three-chamber cell and currents of 0 to 300 mA were drawn when potentials of 0.0 to 5.0 volts were applied. The current requirement of the cell was then increased by situating the electrodes in the central compartment, thus bringing the working and counter electrodes closer together. The reason for increasing the current requirements was to attempt to maximize the current density of the cell, in order to more closely mimic an industrial electrolysis cell. Currents of 0 to 500 mA were then drawn when potentials of 0.0 to 5.0 volts were applied. 3.1 Decomposition voltage determination Normally, current against voltage measurements are performed in order to estimate the decomposition voltage at which both hydrogen and oxygen are produced. Note that the 34 current-voltage plot does not behave exponentially, as would be the case for a Tafel plot, because no consideration is given to the individual electrode reactions, or the subsequent iR drop between the electrodes. The current-voltage plot, as shown in Fig. 8a is bi-linear, and extrapolation of the steeper linear portion of the graph to the x-intercept gave a decomposition voltage of 1.9 ± 0.1 volts. The actual voltage at which decomposition was observed was between 1.75 and 1.80 volts. The plot of background subtracted acoustic root mean square (RMS) voltage against applied potential is shown in Fig. 8b. The acoustic RMS was calculated from the time-domain signal obtained over 12.85 s. The plot of acoustic RMS against voltage is linear and can be used to estimate the decomposition voltage based solely on gas evolution and no other electrochemical process (such as corrosion). The background RMS (55.42 mV) was calculated from the average of several experiments with zero potential applied and subtracted from all the measurements. Extrapolation of the graph to find the voltage at which a background subtracted acoustic RMS of zero is obtained, resulted in a value of 1.8 ± 0.1 volts. Any voltage above 1.8 volts will result in bubble evolution (gas production). The estimated value of 1.8 ± 0.1 volts is significantly more reliable than the estimated voltage obtained from the extrapolation of the current-voltage plot. 3.2 Quantitation of steady-state acoustic emission rates The effect of applied voltage on acoustic activity is shown Fig. 9. No activity was observed below an applied voltage of 1.7 volts - this corresponded to background. At a voltage of 1.8 volts, acoustic emission was generated by the electrolysis process. When integrated, the observed acoustic emission activity is linear with respect to time. Increasing the applied potential to 2.0 V resulted in a corresponding increase in acoustic activity which is evident from the greater slope in the integration trace for this potential. The linearity indicated that the rate of evolution of bubbles from the electrode was constant for a given applied potential. The spikes above background in the time domain signal shown in Fig. 9 0 . 6 3 0 0 1 2 3 4 5 1 2 3 4 5 6 VOLTAGE A P P L I E D (V) VOLTAGE A P P L I E D (V) Fig. 8 Comparison of a current against voltage plot with an acoustic RMS against voltage plot. a) has been extrapolated to find the decomposition voltage, b) has had the background subtracted, and can be used to estimate the decomposition voltage W ACOUSTIC EMISSION INTENSITY (ARBITRARY UNITS) — N J o o o o o o o o o Q . Q CD 9E 37 were caused by the release of a localized group of small bubbles or large individual bubbles. Thus, acoustic emission intensity increases with applied potential in a highly characteristic and repeatable manner. The acoustic emission was accompanied by a corresponding increase in the rate of gas rate of gas evolution, as expected, since the rate is dependent on the current (Faradays Law) by the following relation ip = zrF where ip is the current density (kA m"^ ), z is the number of electrons involved in the 9 1 reaction, r is the rate of reaction (kmole m"^  s ), and F is Faraday's constant. At 1 kHz, the data acquisition rate was sufficiently greater than required to adequately sample the d.c. peak level output of the conditioning amplifier (which had a 200 ms time constant). Thus, all fluctuations in this output were noticed and quantified. Confirmatory measurements to correlate the volumetric rate of gas production with acoustic activity used the closed cell shown in Fig. 7. These indicated excellent correlation between the gas volume produced and acoustic emission observed over the range of applied potentials, as shown in Fig. 10. Monitoring of the acoustic emission with the chart recorder proved to be limited to lower rates of bubble evolution, because the acquisition rate was is too slow to detect faster rates of bubble evolution, and therefore a maximum rate of detection is reached. A better estimate of the limiting rate of the system was obtained by integration of the psuedo-continuous acoustic emission over a fixed period of time. This experiment used the a.c output of the conditioning amplifier connected to the oscilloscope. Acoustic emission intensity increased with electrolyte concentration for concentrations of up to 1.5 M. At NaOH concentrations of 2.0 M and above, the acoustic emission intensity dropped. The inability of our apparatus to supply adequate current under such conditions, or simply the fact that the current has approached its limiting current density (which is mass transfer controlled and independent of potential) could contribute to the decrease observed. CORRELATION OF ACOUSTIC EMISSION WITH V O L U M E O F GAS EVOLVED AFTER 5 MINUTES. V O L T A G E S OF 2 . 5 , 3 .0 , 3 .5 AND 4 . 0 VOLTS WERE U S E D T 10 1 5 20 VOLUME OF GAS PRODUCED(CM 3 ) 25 o 02 GO ZD UJ o ZD O o < o < o r t : m o r < 3 . 5 3.0 -2.5 0 C O R R E L A T I O N OF ACOUSTIC EMISSION WITH V O L U M E OF GAS EVOLVED AFTER 5 MINUTES. V O L T A G E S O F 2 . 0 , 2 . 5 , 3 . 0 , 3 .5 A N D 4 . 0 VOLTS WERE U S E D 10 15 20 25 VOLUME OF GAS PRODUCED(CM ) 30 CORRELATION O F ACOUSTIC EMISSION WITH V O L U M E O F GAS EVOLVED AFTER 5 MINUTES. VOLTAGES O F 2 . 0 , 2 . 5 , 3 .0 , 3 .5 AND 4 . 0 VOLTS WERE U S E D 0 10 20 30 40 50 VOLUME OF GAS PR0DUCED(CM ) CORRELAT ION OF A C O U S T I C EMISSION WITH V O L U M E OF GAS EVOLVED AFTER 5 MINUTES. V O L T A G E S O F 2 . 0 , 2 . 5 , 3 . 0 , 3 .5 A N D 4 . 0 VOLTS WERE U S E D 10 20 30 40 50 VOLUME OF GAS P R O D U C E D ( C M 3 ) Fig. 10 Plots of total acoustic emission against volume of gas produced, which shows the relationship between total acoustic emission and volume of gas evolved at NaOH concentrations of a) 0.5 M, b) 1.0 M, c) 1.5 M and d) 2.0 M 39 Acoustic monitoring and visual observation revealed that the experimental potential needed for electrolysis to begin was in good agreement with typical values used in industry, which can vary from 1.8 to 2.2 volts [57], and was considerably above the theoretical cell voltage for O2 and H2 evolution of 1.23 volts. No acoustic signals were detected at values of applied potential below 1.7 V. 3.3 Spectral analysis of acoustic emission from electrolysis Transducer resonances should only be seen at 800 kHz and 1100 kHz as indicated in Fig. 11. The acoustic power spectra given in Fig. 12 show that the acoustic emission and background noise are spectrally quite different, but both contain the transducer resonance frequencies that were expected. The acoustic emission from electrolysis was broadband in nature and occurred largely between 100 and 800 kHz. Emission between 50 kHz and 100 kHz was largely occluded by the noise, and frequencies below 50 kHz (including ambient audible noise) had been filtered out electronically by the conditioning amplifier. The acoustic emission from electrolysis was at substantially higher frequencies than had been expected from other studies [27,34]. Subtraction of the background spectrum (Fig. 13) was quite straightforward and resulted in a superior acoustic emission power spectrum for electrolysis with a flat background and well defined peaks as shown in Fig. 14. In sonochemistry, the Minneart equation [29] was developed to calculate the approximate resonant bubble frequency (fr) of a bubble of a particular radius (r), in a liquid medium of density (p), with surface tension (K) , and specific heat ratio (heat capacity at constant pressure divided by the heat capacity at constant volume) of the gas ( 7 ) , at atmospheric pressure (Pa), as defined by: fr=l/(2rr){(37/p)KP.+ 2ic)/r]} V2 The resonant bubble frequency is defined as the ultrasonic frequency required to F R E Q U E N C Y ( k H z ) Fig. 1 1 Frequency response of t ransducer used in electrolysis experiments (Signal intensity increases with decrease in log of voltage) 4^ O Q O o O C -h 3 o- =r 3 «• O Q Ul O CD O ~° o ' CD O CD C/> Q W ^ o ' co ^ o o 3 M Q O) 3 < CD O CD '-+- O </) r-«-l l 2 «' ° 8 ACOUSTIC POWER (ARBITRARY UNITS) ACOUSTIC POWER (ARBITRARY UNITS) ACOUSTIC POWER (ARBITRARY UNITS) o o o o o o o o O o b b b b b . b b b b b o —^ hO 4=- o — 1 ho 04 o o o o o b b b b b o — k hO ACOUSTIC POWER (ARBITRARY UNITS) ACOUSTIC POWER (ARBITRARY UNITS) ACOUSTIC POWER (ARBITRARY UNITS) o o o o o b b b b b o —>• hO o o o o o b b b b b o —•>• ho o o o o o b b b b b o — ' ho o hO o o S ° m z o 7T X N o o CO o o o o o hO o o A C O U S T I C P O W E R ( A R B I T R A R Y U N I T S ) o o o o o b b b o hO U J o zv 0.05 0.04 w r 0 .03 -° 5 o £ P < 0.02 oo or o < < ~ 0.01 0.00 - 0 . 0 1 0 200 400 600 800 FREQUENCY (kHz) 1000 1200 Fig. 14 Background —subtracted average power spectrum for hydrogen evolution at the Ni electrode, using 1.0 M NaOH. The spect rum for 1.6 volts has been subtracted from the spectrum taken at 2.6 volts 44 cause a bubble to resonate, arid consequently become unstable and burst. This equation can be greatly simplified by the following assumptions. If the electrolyte is considered to be water, the gas air, the specific heat ratio assumed to be 1, and surface tension effects treated as negligible, the equation simplifies as follows:-fr=l/(2rr)[3'/Pa/p]1/2 This form suggests that the frequencies present in the average power spectrum shown in Fig. 14 would be a result of bubbles of radius l O 4 to l O 6 m. The predicted radius values for 100 kHz to 800 kHz are listed in Table 2. These dimensions would not be an unreasonable estimate of the behavior observed. Table 2 - Approximation of the size of bubbles in the electrolysis of water, using the frequency information of the average power spectrum. Frequency (kHz) Bubble radius (m) 100 8.7 x 10"5 200 4.4 x 10"5 300 2.9 x 10"5 400 2.2 x 10-5 500 1.7 x lO - 5 600 1.5 x 10"5 700 1.2 x 10-5 800 1.1 x 10'5 Considerable structure is evident in the power spectrum obtained. The variation of the applied potential resulted only in a change in the magnitude of the observed spectrum (Fig. 13), and not in shifting of the emission bands. Correlation coefficients of pairs of spectra taken at consecutive applied potentials were between 0.90 and 1.00. The combined effects of applied potential and electrolyte concentration on emission intensity were visualized with a response surface and associated contour plot (Fig. 15). This summarizes cell behavior for applied potentials of 1.5 - 4.0 volts and electrolyte Fig. 15 Response surface from the electrolysis cell showing the combined effects of electrolyte concentration and applied potential on the acoustic emission. The contour and surface plots show acoustic power increasing with applied voltage and electrolyte concentration. The acoustic power decreases for electrolyte concentrations > 1.5 M NaOH. 46 concentrations of 0.1 - 2.0 M. The surface again reveals the steady increase in total acoustic power for electrolyte concentrations of 0.1 -1.5 M, followed by the noticeable drop in total acoustic power at concentrations of 1.5 M and above. This behavior indicated that an optimum electrolyte concentration exists for the cell under study. This is expected since, in all electrolysis cells, the maximum rate at which electroactive species can reach the electrodes' surfaces is a function of electrolyte concentration and applied voltage. The surface was then modelled using a Kalman filter and a basis set which allowed least squares fitting of the function shown below [60]. y = ao + b\Xi + 62*2 + c\X\2 + C2X22 + dx\X2 The x parameters are applied potential (x\) and electrolyte concentration fa), and the response, y , is the total acoustic power observed, which was obtained by integrating area under the acoustic emission. Best-fit values for the six coefficients were found to be a0 = 2.90; bi = 0.0935; b2 = -0.200; ci = -0.200; c2 = 0.244 and d = 0.511. The goodness of fit was indicated by values for standard error of estimation (SEE) and standard error of prediction (SEP). The SEE is defined as SEE = { E ()>; - y c a l c d ) 2 / (Weal - Wpar) } V 2 where yt is the observed response, y c a icd is the calculated response, Nca\ is the number of points in the calibration set (Nca\ = 48), and Npat is the number of fitted parameters (Wpar = 6) . The SEP is defined by SEP = {E(Vj -ycalcd) 2 / M e s t } 1 / 2 where yj is the measured response of the test point, y c a i C d is the calculated response, and Mest is the number of points in the test set. The SEE was 0.05, and the SEP 0.103; together, these values indicated that the model equation provided a close fit to the experimental data. The fact that the coefficients c\ and C2 differ significantly from 0.0 indicates the non-linear nature of the surface in x\ and xi. The coefficients presented here are only empirical, and provide no insight into the chemical process occurring within the cell. 47 3.4 Variation of signal characteristics with applied potential Sets of 200 signals were captured at voltages between 2.0 and 4.0 volts, and were analyzed by means of multiple descriptive statistical factors, using the methods described elsewhere [48]. Fig. 16 shows that the mean and median frequency of the acoustic power spectrum remains constant as the hydrogen electrode potential is increased, once the background has been subtracted. The large contributions from transducer resonances at 0.8 and 1.1 MHz are always observed; however this is transducer specific. Table 3 indicates the good correlation of the intensity of the mean and median acoustic emission frequencies with the individual hydrogen electrode potential. Useful time-domain descriptors were the root mean square (RMS) voltage, area, crest, and kurtosis [48]. CREST = PEAK / RMS KURTOSIS = 1/n V[(Vi-V)/o] 4 - 3 where Vis the average value of the signal, and a is the population standard deviation of all of the signal values, V\, about zero volts. The mean and median values of CREST and KURTOSIS were found to correlate linearly with applied potential. The descriptors RMS and AREA relate directly to the magnitude of the signal, and increasing the potential leads to an increase in their magnitude. Outlier identification methods proposed elsewhere [48] were applied to these data sets, and it was confirmed that as the applied potential increases, a greater number of signals could be classified as outliers. Visual observation of cell operation at the higher potentials suggested that sporadic spurts of bubbles from the base and sides of the electrodes, with en route combination of many small bubbles into larger ones (avalanche behavior), were the cause of these emissions. There is intense clouding of the electrode surfaces at higher voltages, and bubble combination is made possible by the large number density of small bubbles in the region of the electrodes. The increased turbulence and/or 3 0 0 MEAN FREQUENCY MEAN 2 8 0 N X 2 6 0 >-O z U J O U J or 2 4 0 2 2 0 2 0 0 -MEAN FREQUENCY MEDIAN - 0 . 5 0 . 0 0 . 5 1 .0 1.5 HYDROGEN ELECTRODE POTENTIAL (VOLTS) 2 . 0 Fig. 16 Correlat ion of mean values of frequency mean and frequency median signal descriptors with applied potential. The plot indicates the consistent frequency content appearing in the power spectra 00 49 Table 3. - Correlation of signal descriptors with applied potential (using all signals)  a) Mean values for descriptor distributions Electrode Freq. Freq. Potential Mean Median RMS Area Crest Kurtosis (volts) (kHz) (kHz) (V) (VsxlO"2) (-) (-) -0.22 512.9 442.5 0.1037 83.03 4.572 1.007 0.56 505.1 432.9 0.1088 87.03 4.406 0.8527 0.72 497.9 421.7 0.1134 91.43 4.294 0.8294 1.00 495.9 416.7 0.1156 93.00 4.158 0.6747 1.38 489.9 412.5 0.1244 100.8 3.867 0.4167 1.82 475.3 391.3 0.1343 109.1 3.644 0.2874 Correlation Coefficient -0.991 -0.986 0.986 0.985 -0.983 -0.973 b) Median values for descriptor distributions Electrode Potential (volts) Freq. Mean (kHz) Freq. Median (kHz) RMS (V) Area (Vs xlO"2) Crest (-) Kurtosis (-) -0.22 512.2 439.5 0.1038 83.23 4.553 0.9392 0.59 504.0 432.1 0.1087 86.15 4.373 0.8341 0.72 502.4 432.1 0.1087 87.56 4.369 0.8459 1.00 496.4 419.9 0.1127 90.56 4.216 0.6521 1.38 488.3 411.4 0.1208 97.76 3.942 0.4019 1.82 479.9 400.4 0.1308 106.2 3.653 0.2874 Correlation -0.992 -0.976 0.975 0.971 -0.980 -0.953 Coefficient 50 resistance caused by the clouding is likely one of the causes of decreased efficiency at high potentials. Acoustic detection of this phenomenon may therefore be a valuable tool in design of improved electrolyzers, since the time bubbles spend attached to the electrode surface will directly affect corrosion processes. Bubble flow is known to be very important in the engineering of electrolyzers. CREST and KURTOSIS are descriptors related to the decay rate of individual acoustic signals. The higher their value the faster the decay of the signals. Table 3 indicates that higher potentials result in a slower rate of signal decay, which would also be expected since more time is required to form the larger bubbles observed. Injection of power ultrasound into various heterogeneous chemical systems is known to have a homogenizing effect. It is therefore likely that one of the primary mechanisms by which power ultrasound assists electrolysis efficiency [62] is in the destruction, disruption, or minimisation of these large bubbles and localized bubble bursts. 3.5 Detection of surface coating The interesting observations noticed in Figs. 17 and 18 are that there seems to be some variation in the frequency spectra over a period of 50 seconds, which indicated that different classes of signals existed. On further examination, the new class of signal was only present when the electrodes had been freshly cleaned, and a new electroactive surface had been created on application of potential. The different signal classes could be observed visually in both the time and frequency-domain. The most appropriate descriptors for representing these differences were found using a program (AETREND) written in this laboratory, and these descriptors could be seen (by visually recognizing the signals) as being the most likely to determine the differences between the signal classes. Once the descriptors had been reduced in number, pattern recognition proved very successful at separating the classes of signals. RMS, PEAK, CREST, KURTOSIS, HALF-LIFE, 1/8T, and FBW (15 %) were the descriptors most appropriate. The definitions for Fig. 17 a n o t h e r p r o c e s s i s o c c u r r i n g fi s p e c t r u m s u g g e s t s t h a t 53 these were provided in Table 2. Principal components analysis (PCA) was carried out, with a varimax rotation, and provided a separation of the signals (Fig. 19). The figure suggests that there are at least two distinct classes (a, b&c) and possibly three classes (a, b, c). Fig. 20 shows the difference between a typical bubble emission signal and one from surface coating (oxide formation). The noticeable differences between these signals are the distinct frequency peak at 385 kHz and absence of a broadband emission in the signals from (oxy)hydroxide nickel layer formation. At potentials above 2.5 volts the detection of this type of signal is difficult, since i) formation of the oxide is rapid and ii) emission from bubble formation becomes so intense and frequent that they are captured in preference. 3.6 Possible sources of acoustic emission The above studies indicated unequivocally that the ultrasonic emissions detected were due to gas bubble evolution. The apparatus design prevented the possibility of an acoustically active recombination of the oxygen and hydrogen gases. Experiments were run to determine if the formation of a nickel oxyhydroxide layer on the surface of the nickel electrode was also acoustically active. The layer can be seen as a brown/black discoloration, and is readily removed by reversing the applied potential. It is conductive and may be responsible for electrode-kinetic changes during the reaction. Initially, no acoustic signals were detected from deposition or removal of the layer. However further experiments with a faster capture mode and higher amplification led to a few signals being detected which were markedly different to gas evolution signals, and which only occurred when the electrode had recently been cleaned, and the nickel oxyhydroxide was forming. Further studies carried out in a 50 mL beaker sought to determine if the reaction of nickel (as chloride) with sodium hydroxide to form nickel hydroxide (initially a gel) had any observable acoustic emission behavior. No acoustic signals were detected, which suggested that the signals from the cleaned electrode were coming from a heterogeneous process on the electrode surface, rather than gel formation only. 54 - 2 - 1 0 1 2 3 4 PRINCIPAL COMPONENT #1 19 Principal Components analysis showing the clustering of signals f rom surface coating (A) and bubble emission (B,C) a 127 0 o h-< N o Q - 1 2 7 0 T I M E - D O M A I N T R A C E F R O M B U B B L E S B U R S T I N G POINT # 1024 2.5 >-c o z LJJ I — z LJJ > I — U J or 0.0 F R E Q U E N C I E S A S S O C I A T E D WITH B U B B L E B U R S T I N G 185 TRANSDUCER RESONANCES 0 250 500 750 1000 FREQUENCY (kHz) 1250 b 127 - 1 2 7 0 T I M E - D O M A I N T R A C E F R O M E L E C T R O D E S U R F A C E COATING POINT # 1024 >-C O z LJ I— z LJJ > I — <c I LJJ F R E Q U E N C I E S A S S O C I A T E D WITH E L E C T R O D E S U R F A C E COATING 0 0 250 500 750 1000 1250 FREQUENCY (kHz) Fig. 20 Time and f requency-doma in representations for a) bubble emission and b) surface coating emission cn An oxide layer (probably chromium oxide) is formed on the surface of the stainless-steel electrode, and this again provided signals once the surface had been cleaned. The differences between the two types of signal can be seen in Fig. 20. From the above one can conclude that when the electrode surface had not been recently cleaned, the chemical acoustic emissions being monitored were exclusively from the formation of hydrogen and oxygen bubbles. However, at higher amplification and with a fresh electrode surface available, acoustic emission is initially detected from both oxide (or oxyhydroxide) formation and bubble emission. A summary of the possible sources of acoustic emission is shown in Fig. 21. BARRIER Ni ELECTRODE PRODUCING OXYGEN STAINLESS-STEEL ELECTRODE PRODUCING HYDROGEN COLLISION WITH SURFACE BREAKING OF .SURFACE TENSION AE I I RELEASE OF OXYGEN I FROM NUCLEATJON SITE FORMATION OF NICKEL (OXY)HYDROXIDE ON SURFACE OF ELECTRODE RELEASE OF HYDROGEN FROM NUCLEATION SITE AE POSSIBLE FORMATION OF IRON, NICKEL, AND CHROMIUM HYDRIDES ON ELECTRODE SURFACE Fig. 21 Possible sources of acoustic emission 58 II.4 CONCLUSIONS Acoustic emission monitoring has been shown to be a useful tool for characterization of the operation of gas producing electrolyzers. This is of significance in industry, because i) current measurements commonly cannot be used to measure rates of gas evolution because the current density changes involved are too large and ii) pressure measurements are often unsuitable for measurements of rate of gas production since the electrolyzer is maintained at high pressure (often 20 atmospheres). Electrolysis is perhaps particularly suited to being monitored by acoustic emission (electrosonimetry, c.f. [19]) because close contact between the electrode and transducer is possible. Both time- and frequency-domain representations of acoustic emission from electrolysis reliably show the onset of gas evolution. The acoustic emission also indicates the effect that electrolyte concentration and applied potential have on bubble emission intensity. The formation of oxides and (oxy)hydroxides on the surface of the anode can be detected at lower potentials (1.8 - 2.0 V). Formation of the nickel (oxy)hydroxide coating is beneficial to most electrolysis experiments because it provides better conductivity than an electrode without such a coating, and therefore it reduces the overvoltage. It also increases the rate of bubble desorption from the electrode surface. Corrosion in acidic media has already been monitored by an acoustic emission method [50]. The use of an alkaline electrolyte also involves corrosion (hydroxides, and complexation occurs), and the same acoustic technology that was applied to corrosion in an acidic media can thus be used for the alkaline electrolysis system. Industrial electrolyzers need to be optimized for temperature, pressure, concentration, current density, and potential. Acoustic emission will be a useful tool for those that seek to achieve this optimization since the integration of the acoustic RMS generated from bubble evolution with respect to time provides a simple, efficient and non-invasive measure of the rate of gas production. 59 II.5 F U T U R E W O R K Stimulation by injection of power ultrasound is becoming increasingly valuable in chemical processes [62]. Reactions such as electrolysis are low power sources of ultrasonic waves of similar and higher frequencies to commercial power ultrasound sources, which are typically 20 - 45 kHz. This thesis has shown that bubble release and formation of electrode coatings from an electrochemical reaction can be followed by their release of ultrasonic energy. Moriguchi has suggested that the water decomposition voltage of electrochemical processes can be. reduced by ultrasound provided by an external source [63], thus the natural ultrasonic emission may assist in the process. Ultrasonic waves have been used to study electrolytic solutions in other ways [64], and ultrasound-induced electrochemical synthesis of various anions [65] has been reported. An in-depth study into the ultrasound produced from several different electrochemical reactions which involve gas evolution (e.g. the chloro-alkali and water electrolysis cells) would provide a great amount of information about the bubble dynamics within such cells. Furthermore, the study of the effects of ultrasound produced from bubbles could help to provide insight into the importance of ultrasound on the reaction kinetics of electrolyzers. 60 CHAPTER in Acoustic Emission Monitoring of the Sensitivity of Chemicals to Impact III.l I N T R O D U C T I O N There is an urgent need for an alternative method for evaluating the sensitivity of explosive compounds to impact. The resistance of a material to impact-induced explosion is one of its most valuable quantitative characteristics, as it gives assurance of safety in handling, transportation, and use. The present method involves repetitive use of a drop-weight tester. Small amounts of sample materials (mg) are subjected to impact. The indication of a positive result (an explosion) is very subjective and operator dependent; therefore acoustic emission was considered as an alternative method for determining if the result was positive, and hence improve the reliability of the sensitivity values obtained for explosives and propellants. 1.1 I N T R O D U C T I O N T O E X P L O S I V E S An explosion is a rapid violent release of chemical, mechanical, or nuclear energy from a confined region. The result of an explosion is the production of a considerable quantity of heat and a large volume of gas. The design and application of explosives is a science and explosives are as capable of being controlled as are other products of industry. Steel can be hardened by the use of explosives. The intricate patterns that are created by fireworks are dependent on the correct mixture of compounds, and a detailed knowledge of their burning rates and flame colours. 61 An explosive can be classified as being either a deflagrating explosive (propellent), a high explosive (secondary explosive), or an initiating explosive (primary explosive). A propellant is an explosive which burns at a steady speed and can be detonated only under extreme conditions. An initiator (e.g. mercury fulminate) is an explosive that is extremely sensitive to shock. High explosives normally burn without undue violence when ignited in an open space, but can be detonated by a sufficiently large sudden mechanical or explosive shock. The most important properties of explosives are the velocity of burning or detonation, the explosion temperature, the sensitivity to impact, and the power. Sensitivity and power are measured on a relative scale. Originally for sensitivity, picric acid was used as a standard compound, with an assigned value of 100 [66]. Nowadays, each machine used for sensitivity testing has its own method of calibration. The present drop-weight method for sensitivity testing yields very imprecise values. This is partly because the interpretation of results from the test is very subjective; for instance, the sign of smoke, the smell of a gas, or the visual observation of a dark residue in the sample holder have all been used to adjudicate a positive result. Therefore a more sophisticated method for sensitivity testing is necessary. Acoustic emission is a possible alternative for the testing of explosives, since obvious amounts of audible acoustic emission result from explosions. We decided to monitor acoustic emission resulting from the existing shock sensitivity testing procedure, and evaluate the efficiency of both acoustic emission monitoring and the present procedure for determining the sensitivity of liquid and solid explosives and calibration compounds. 1.2 D R O P - W E I G H T T E S T I N G Drop-weight testing was introduced in the early 1930s by the Bureau of Mines Explosives Experiment Station for testing the sensitivity of explosives used in the mines. There were two machines designed. One was a small impact machine, which was used for testing fine-grained or finely pulverized homogeneous explosive compounds. The size and design of the apparatus was similar to the Olin-Mathieson drop-weight tester reported in 62 this thesis (Fig. 22), and the same sample volumes were used. With this machine a weight of 6 Kg can be dropped from a height of 50 cm onto a sample of 20 mg. The other machine was a large impact machine, which was used to test coarse-grained material (e.g. compounded explosives such as dynamite). With this machine a 200 Kg weight could be dropped from 7.5 m onto 80 g samples. World War II caused a considerable need for a more detailed study of the fundamentals involved in the impact test, but little headway was made; however, the apparatus and testing procedures used were improved. In 1959 the Joint Army-Navy-Air Force Panel on Liquid Propellant Test Methods accepted the Olin-Mathieson drop-weight tester as the standard method for determining the impact sensitivity of liquids. Apart from drop weight testing, there is no other quick and simple way to evaluate solid and liquid propellants for their explosive sensitivity. The impact sensitivity for a given sample may be defined as the potential energy value (height x weight) at which explosion occurs in fifty per cent of tests. In liquid propellant testing the explosion is initiated by the adiabatic compression of the gas volume present in the sample. This process is extremely complex, and prevents the fundamental significance of the test from being established. The same is true for the testing of solid propellants, although the governing factors are different. There is, however, no standard impact test for solids at the present time. The determination of the relative safety of handling hazardous chemicals is the principal function of the impact test. For this reason, materials are compared with known materials on a relative basis, rather than on a standard numerical scale [67-69]. Many different types of drop-weight testers have been designed, and consequently many different values for the same explosives materials have been reported. Even two machines of the same design can give contrasting values. Bowden and Yoffe [70] have shown that "hot spots" are the reason for initiation on impact, and not uniform heating. These "hot spots" can be caused by friction between crystal particles, the compression of small gas pockets in the solids, and even by heating of the solid by viscous flow. The "hot spot" theory has also been confirmed by Cook [71]. SOLTEC D I G I T I Z E R H E I G H T OF P L A T F O R M C A N B E VARIED W E I G H T STACKED ON THIS P L A T F O R M C O N D I T I O N I N G A M P L I F I E R R E L E A S E M E C H A N I S M FOR D R O P - W E I G H T T R A N S D U C E R C U P ASSEMBLY C O N T A I N I N G S A M P L E Fig . 22 D r o p - w e i g h t t e s t ing appara tus 64 The importance of cross-sectional area, thickness of the sample, drop-distance, and drop-weight used in impact testing were all verified by Africano [72]. Most machines have very good agreement for sensitive explosives but vary considerably for less sensitive materials, probably due to the difference in striker area. The thermodynamic and physical properties of a propellant or explosive can be measured on an absolute basis. However, as will be discussed below, the chemical-kinetic properties (burning rate, spontaneous ignition temperature, ignition delay, compression ignition sensitivity, detonation sensitivity, and thermal stability) are not fundamental properties, and therefore cannot be determined on an absolute basis. These chemical-kinetic properties are dependent on the temperature and reaction-velocity relationship of a system and its heat of reaction, and are the critical factors on which the practicability of a propellant or explosive must be judged. They are, in turn, functions of the physical conditions governing the rate of transfer of heat between the system and surroundings, and between the reactants and products. This explains the effect of pressure on ignition and burning rate, and the critical diameter effect in detonation and deflagration propagation [73]. When a weight falls, the transfer of energy from the falling weight to the sample is a function of many factors: namely; the mass and velocity of the weight; the mass and surface hardness of the striker and anvil; and the cross-sectional area, thickness, physical composition, and degree of confinement of the sample. The last of these factors is often dependent on the constant thickness of the diaphragm used to confine the liquid sample. This thickness proved inconsistent throughout the experiments detailed in this thesis. In fact, many of these variables are difficult to control, even though the test conditions are arbitrary. The Olin-Mathieson drop-weight test was designed to provide an accurate sample volume, a controlled bubble volume (air pocket within the cavity), and complete sealing of the sample cavity to prevent leakage during the impact and explosion. The prevention of leakage resulted in a large reduction in the impact energy required for initiation of explosion, so that the method has been able to differentiate between materials covering the full range, from insensitive fuels to highly sensitive explosives. Radiometric and spectroscopic methods [74,75] have been used to investigate the decomposition of explosives on the drop-weight machine. Initial radiometric results revealed consistent, sequential emissions for specific impacted explosives. 1.2.1 Compression Ignition Compression ignition [73] can be a complicated process when there is both liquid and vapor present in the sample cavity. For the simple case, where just vapor compression is involved, adiabatic conditions can be assumed and the temperature increase during compression can be expressed as a function of the compression ratio and specific heat ratio of the gas or vapor. However, when both liquid and vapor are present the adiabatic assumption can no longer be true, since there can be a transfer of heat from the vapor to the liquid. The size of the bubble is very important, since the rate of transfer of heat from the bubble to the surrounding liquid is inversely dependent on the size of the bubble. Consequently for very small bubbles adiabatic conditions cannot occur. Sample volume and temperature are therefore very important properties for accurate sensitivity measurements. 66 III.2 E X P E R I M E N T A L 2.1 R E A G E N T S Water (distilled, University of British Columbia Chemistry Department). Dichloromethane (AnalaR grade, BDH Chemicals, Toronto). Ammonium Dichromate (AnalaR grade, Fischer Scientific, Fair Lawn, NJ). Nitromethane (AnalaR grade, Aldrich Chemical Company, Inc, Milwaukee, WI). 2.2 A P P A R A T U S All experiments involved the Olin-Mathieson drop-weight tester (Technoproducts Division, Quantic Industries Inc., San Carlos, CA). All the equipment was provided by the manufacturers of the drop-weight, unless otherwise stated. The height and weight of the dropping weight could be altered. Different sample holders were used for solid and liquid measurements. Liquid samples The sample holder for the calibration test and other tests on liquid samples was as shown in Fig. 23. A steel cup (1.000 inches diameter, 0.625 inches depth)*, with a cylinder * (0.375 inches diameter, 0.500 inches depth) cut out, was positioned in the body of the sample holder. A rubber O-ring (Type AN6227-5, 0.239 inches I.D . , and 0.279 inches C D . ) was placed in the bottom of the cup and pushed down firmly using the piston (0.363 inches diameter, and 0.750 inches height)*. The sample solution (0.03 ml) was injected into the cavity created using a fixed-stroke syringe (No. 4250, Nimetrics Corporation, Anaheim, * CA), and a stainless steel diaphragm (0.015 inches thick, and 0.363 inches diameter) was * Manufacturer's values STEEL BALL VENT SAMPLE CAVITY Fig . 23 Sample ho lde r for l i q u i d s amples 0\ 68 dropped flat onto the O-ring. The piston was placed onto the diaphragm, and was designed with a vent hole which is blocked by the diaphragm. A steel ball (0.825 inches diameter) was placed on the piston to prevent it from moving upwards after the explosion. The last stage in assembly was the addition of the cap to the body of the sample holder. This cap was screwed onto the body and tightened to a torque of 7 lbs using a torqometer. Finally, the sample holder was situated in the base of the drop-weight tester. Solid Samples The sample holder for solids is depicted in Fig. 24. A solid sample of mass 0.02 g was weighed out on an analytical balance, and deposited in a brass cup (0.313 inches diameter, 0.121 inches depth, and 0.012 inches thickness) . The plunger tip (0.304 inches diameter)* was then carefully lowered into the cup. The sample holder was then placed onto the base of the drop-weight tester. Acoustic Emission Detection The broadband transducer (Model FAC500, Acoustic Emission Technologies Inc., Sacramento, CA), used for all measurements, was mounted using insulating tape onto one end of a flexible strip of stainless steel (2 mm thick, 2.5 cm width, and 20 cm length), which, in turn, rested on the sample holder. Petroleum grease was used to improve the coupling between the transducer and the strip, and between the strip and the sample holder. The output of the transducer was connected to a conditioning amplifier (Type 2638, Bruel & Kjaer). This provided a switch-selectable gain of 0 to 60 dB in 1 dB steps, and several bandpass filter ranges. The a.c. output of this amplifier was connected to a digitizer (Model SDA 2000, Soltec Inc., San Fernando, CA). The digitizer transferred the data via an IEEE-488 interface to the hard drive of a P C / X T class personal computer for later processing. The digitizer was controlled using the software provided by the digitizer's manufacturer. * Manufacturer's values PLUNGER BODY PLUNGER TIP SOLID SAMPLE BRASS CUP CONTAINING SAMPLE Fig . 24 Sample ho lder for s o l i d samples 70 2.3 M E T H O D 2.3.1 Initial Experiments Improvements to the stability of the tester were made by bolting the tester to a rectangular steel plate of 0.75 inches thickness, 36 inches length, and 24 inches width, which in turn was mounted in a wooden frame. A trigger mechanism was also added to facilitate a more reproducible release of the dropping weight. These improvements greatly increased the reproducibility of the experiment. 2.3.2 Water Calibration The purpose o f the calibration procedure was to determine the sensitivity value at which hydraulic pressure from the sample causes a puncture of the diaphragm. The sensitivity value for the water calibration sets the maximum sensitivity value. The sensitivity value for nitromethane must lie below the water sensitivity value in order to eliminate the possibility that the diaphragm has ruptured because of hydraulic pressure. The sensitivity value for liquid or solid samples is the potential energy value (height x weight) at which the probability of explosion is 50%. The 50%-point ( E 5 0 ) was determined by a statistical method known as the "Up and Down" method [76]. The sample cavity was filled with 0.03 ml of distilled water. After every test the diaphragm and O-ring were changed, and all parts of the sample holder for liquids (Fig. 23) were cleaned with a cloth soaked in dichloromethane. The conditioning amplifier gain was set to 30 dB, and a 50 kHz - 2 MHz filter was used. A sampling interval of 7/ is, and a record length of 65536 (64 k) data points was used, initially, to measure the time of the bounce of the dropped weight. These conditions provided a time window of 389.9 ms. Once this was established, the sample size was then increased to 128 k samples and the 71 sampling frequency increased to 200 ns, so as to satisfy Nyquist frequency conditions, and create a time window of 26 ms. A weight of 4 Kg was dropped from a height of 35 cm. If the diaphragm punctured, or stuck to the piston, then a positive result was deemed to have occurred, and the weight was sequentially reduced in steps of 200 g until a negative result was obtained (no puncture of the diaphragm). From this point, another 20 trials were carried out. During these, whenever a positive result was obtained, the weight was reduced by 200 g, and if a negative result was obtained, 200 g was added. Once a minimum of 20 tests was completed, the total positive and negative tests were marked down, as well as their respective probabilities (Table 4) . The mean value, E 5 0 , was then estimated by linear interpolation between the percentages either side of the 50% point. The mean may also be taken from the arithmetic mean of all the tests (positive and negative). The sensitivity.value was always presented to the nearest 1/10 Kg cm. N U M B E R OF TRIALS T O T A L Of /a R / K g c m 1 2 3 4 5 6 7 0 9 10 1 1 12 13 14 15 1(5 17 10 19 20 + - I 'OSSIUILITV 140.0 + + + + + + + 7 0 100 133.0 - - + - + - - + - - 3 7 30 126.0 - - - 0 3 0 S E N S I T I V I T Y N U M B E R ( E 5 Q ) INTERPOLATION: E 5 0 = 133.0 + (140.0 - 133.0) 5 0 - 3 0 = 133.1 Kg c m A R I T H M E T I C M E A N : 100-30 7 X 140.0 10 X 133.0 3 X 120.0 980.0 1330.0 370.0 = 2G00.0 / 20 = 134.'I Kir cm Table 4 Procedure for calculating the sensitivity value of explosives 73 2.3.3 Liquid Propellant Test The digitizer conditions were similar to those used for the water calibration except that a smaller record length (16384 samples) was used to make data storage easier. The conditions provided a time window of 3.244 ms, which avoided the inclusion of a bounce, if it occurred. The sample cavity was filled with 0.03 ml of nitromethane. Initially, a 6 Kg weight was dropped from 20 cm; if puncture of the diaphragm occurred, the weight was decreased to 1 Kg. If the latter test appeared positive then the height was reduced until a negative result was obtained. The weight or height was gradually reduced, or increased, until a change in sign (positive or negative) was obtained with a change of approximately 5% of the total weight. Once these conditions were attained, 20 more tests were carried out. If the sensitivity value exceeded the energy required to rupture the diaphragm by hydraulic pressure (i.e. the value obtained from the water calibration), then the test was aborted. Again the diaphragm was changed every time a test was completed, irrespective of whether the test was positive or negative. 2.3.4 Solid Explosive Test The same digitizer conditions were applied as used for tests on liquid samples. A brass cup was filled with 0.02 g of ammonium dichromate and placed in the solid sample holder (Fig. 24). The conditioning amplifier gain was set to 40 dB, with a filter setting of 50 kHz - 2 MHz. The filter setting was changed to 400 kHz - 2 MHz when it was realized that most of the acoustic emission observed was at 400 kHz and beyond. A 6 Kg weight was first released from a height of 50 cm. If this test was negative, then the sample could not be tested. If the test was positive (as indicated by deformation of the brass cap, signs of gas evolution, or discoloration of the sample) then the weight was reduced to 1 Kg. Thereafter, for a positive test the new weight (3 Kg) would be half the previous weight (6 Kg). The procedure was continued by adding or decreasing the test by half the previous weight until a change in sign has occurred for a change of weight of approximately 5% of the total weight (e.g. for a 2 Kg weight the test would finish once the change in weight had reached 0.1 Kg). Once this condition was achieved, the results of a further 20 trials were acquired. After every test the brass cap was changed and the plunger tip was wiped clean using dichlorome thane. 75 III.3 RESULTS AND DISCUSSION 3.1 Initial Modification of the Drop-weight Tester Bouncing of the dropping weight initially provided a serious problem; since the bounce occurred at 360 ms (Fig. 25), it was thought this could interfere with a long-lasting acoustic signal. To avoid all possibility of such interference the sampling time was restricted to less than 50 ms. Furthermore, the improvements to the apparatus (i.e. bolting of the drop-weight tester to the steel plate) completely removed the occurrence of a bounce for the water calibration (but not for other samples). Under such conditions all tests which appeared positive from their RMS values, also resulted in the perforation of the diaphragm. The modified apparatus therefore facilitated a fast YES/NO answer to the impact procedure, and reliable determination of a positive result for the water calibration. Before the modifications, the results were extremely inconsistent for all experiments, and a sensitivity value for the water calibration could not be obtained. 3.2 Frequency-time spectra (spectrograms) for liquid and solid sample holders (no  sample) We sought to analyze the change in frequency spectrum present over the time period of the experiment (spectrogram). The TRAPS program [23] was applied to the signals obtained from the impact, to see how the averaged frequency spectra varied with time during the experiment, in the hope of being able to associate the frequencies observed with the various stages of impact and reaction. The spectrograms for the liquid and solid sample tests with no sample present (blanks) are shown in Figs. 26 and 27, respectively. The liquid sample holder spectrogram shows a distinct peak at 300 kHz, which is vastly different to the broad band of frequencies shown in the spectrogram for the solid sample BOUNCE OF DROP-WEIGHT ASSEMBLY OCCURRED AT 360 ms 0 195 390 TIME (ms) Fig. 25 The above trace indicates that the bounce occurs at 360 ms. This enabled the window to be reduced for further experiments, eliminating the noise associated with the bounce •vi 78 79 holder. The variation is caused by the different way in which the striker interacts with parts of the sample holder cup assembly. For instance, the liquid sample holder contains a rubber O-ring, which would be expected to have relatively low resonant frequencies, and prevents the collision of the two metal surfaces (the steel diaphragm with the base of the sample cup); however, direct collision between two metal surfaces (the plunger with the brass cup) occurs within the solid sample holder, and thus would be expected to produce higher frequency emission. 3.3 Water calibration The modified apparatus was calibrated using distilled water. It was found that a positive result could be obtained, and that this result could be verified not only by puncture of the diaphragm, but also by the lack of a bounce after the initial striking of the sample holder. The time-domain signal for an experiment in which a bounce occurred (Fig. 28) was considerably different to that from a positive result (Fig. 29) and therefore the two could readily be distinguished. The RMS of the signal over a frequency range of 50 kHz-2 MHz was used to predict the result of the impact on the sample. The root mean square (RMS) voltage values for the positive tests were always considerably less than that for the negative tests, in which a bounce was always observed. Table 5 shows that, when the bounce was removed from consideration by using a smaller time window, the positive result had a higher RMS (7.2 ± 1.9 mV) than the negative result (4.8 ± 1.0 mV) at the 90 % confidence level. Furthermore, the release of the explosion products (the water calibration experiments produced water vapor) at high pressure will undoubtedly lead to the generation of sound waves. Generally, if the RMS value is more than 6.0 mV, then the test is positive and rupture of the diaphragm has occurred. The sensitivity value for water was calculated to be 133.1 Kg cm (Table 4), with an arithmetic mean of 134.4 Kg cm. This E50 was consistent with values from previous tests conducted elsewhere [70]. Attainment of this value allowed the testing of the liquid propellant (nitromethane) to be carried out, Fig. 20 Time-domain signal for the calibration of the apparatus using water. The result is negative, and if a larger time window had been used, a bounce would have been seen at 360 ms 00 o Fig. 29 Time-domain signal for the calibration of the apparatus using water. The result is positive, and would not show a bounce if the time window had been extended to 360 ms 00 H TEST NO. IIElGIIT/cm WEIGIIT/Kg E/Kg cm POS NEG REMARKS RMS/mV 1 35 4.0 140.0 + 9.069 2 35 3.B 133.0 - BOUNCED 4.159 3 35 1.0 140.0 + U.30'1 1 35 3.3 133.0 - BOUNCED 5.836 f» 35 4.0 140.0 + 7.562 6 35 3.3 133.0 7,631 7 35 3.6 126.0 - B O U N C E D A .750 u 35 3.3 133.0 - BOUNCED 4.555 0 35 •1.0 140.0 + 7.214 10 35 3.M 133.0 + 6.350 1 1 35 3.6 126.0 - BOUNCED 5.702 12 35 3.M 133.0 - BOUNCED •1.73(1 13 35 •1.0 140.0 + 8.126 M 35 3.0 133.0 - BOUNCED 4.071 15 35 4.0 140.0 + 7.379 16 35 3.8 133.0 + 5.437 17 35 3.6 126.0 - BOUNCED '1.650 in 35 3.8 133.0 - BOUNCED 3.04 1 19 35 4.0 140.0 + 4.649 20 35 3.8 133.0 BOUNCED 5.624 Table 5 Correlation of acoustic RMS (root mean square) values with positive and negative results for water calibration. Positive results always show a higher RMS value 83 knowing the potential energy required to rupture the diaphragm by hydraulic pressure alone. 3.4 Spectrogram of water The acoustic intensity obtained from the calibration test (Fig. 30) was considerably greater than that obtained from a blank test, in which the sample compartment contained no distilled water (Fig. 26). This observation confirmed the existence of acoustic emission other than that produced by the initial impact. The spectrum indicates that rupture of the diaphragm occurs approximately 1.6 ms after the initial impact. This is in agreement with previous values [66] obtained elsewhere. The increase in intensity of the frequency band centered about 300 kHz after approximately 1.6 ms (Fig. 30) is associated with the rupture of the diaphragm by hydraulic pressure. Where no rupture has occurred this increase is absent, as seen in Fig. 31. The boiling of water is known to give similar spectra with the majority of emission at frequencies below 300 kHz. The peak around 1 MHz is believed to be the movement of the sample holder parts in the initial impact, and the friction thereby produced. 3.5 Liquid Sample Testing of Nitromethane The test for nitromethane proved difficult because the explosion of the sample refused to pierce the diaphragm, but instead favored cutting through the O-ring, and scoring the side of the piston. Because of this, the time-domain signal obtained was found to vary considerably. The higher magnitude of RMS values, relative to those from the water calibration, is in part due to the different time window considered. A typical negative result is shown in Fig. 32. It proved impossible to calculate the sensitivity value (E50) for nitromethane because no value had a 50% chance of exploding (Table 6). None of the positive tests mentioned in Table 6 resulted in rupture of the diaphragm; therefore, a FIR. HO A Posj-ivo result.: This surface shows a (Increase in intensity of a peak at juu kHz aRcr l.d ms followed by an increase in the peak intensity after 1.4 ins due in the rupture of the diaphragm and subsequent release of water vapour 00 85 Fig. 32 Time-domain signal for a typical negative result from nitromethane 6 as TEST NO. HEIGHT/cm WEIGHT/Kg E/Kg cm POS NEC REMARKS RMS/mV 1 20 6.00 120.0 75.8 2 20 5.95 119.0 - 14.7.1 3 20 6.00 120.0 + 45.07 4 20 5.95 119.0 - 181.2 5 20 6.00 120.0 - 108.9 6 20 6.05 121.0 - 255.0 7 20 G.05 121.0 - 148.8 0 20 6.05 121.0 - 180.9 9 20 6.05 121.0 - 258.3 10 20 G.05 121.0 + 79.7 11 20 6.00 120.0 - 343.7 12 20 6.05 121.0 - 236.4 13 20 6.05 121.0 - 98.9 14 20 6.05 121.0 61.1 15 20 G.00 120.0 - 73.9 16 20 6.05 121.0 - 310.1 17 20 G.05 121.0 - 71.6 18 20 6.05 121.0 - 161.3 19 20 6.05 121.0 - 196.2 20 20 6.05 121.0 58.9 Tabic C Lack of correlation between acoustic RMS values and positive and negative results for nitromethane. The table shows the ^reproducibility of the RMS values 88 positive result was assigned when the O-ring and piston had been scored. The maximum weight of 6.05 Kg could not be exceeded since the sensitivity value would be too close to that for hydraulic rupture, and the maximum amount of weight that could be added was 6.05 Kg. This restriction limited the test to a maximum value of 121 Kgcm and therefore if the test proved negative at this value (which it frequently did) then the value could not be further increased. This factor, along with the absence of puncture of the diaphragm, cutting/melting of the diaphragm, and the random alternative escape route of the reaction products up the sides of the piston, resulted in acoustic RMS values that did not follow any particular pattern. However, Table 6 indicates that a higher RMS is generally associated with a negative result. 3.6 Spectrogram of Nitromethane The inconsistency of the frequency spectra for negative results for nitromethane are shown in Fig. 33. The positive results provided equally inconsistent frequency spectra. There seems much randomness in the intensities of the 3D surfaces generated and, while the surfaces exhibit the same general frequencies as found for the liquid sample holder, no distinct spectral features exist which distinguish a positive from a negative result. 3.7 Solid Sample Testing of Ammonium Dichromate For the solid samples, again much variation was seen in the way the explosive deforms the brass cap, and the degree to which the sample actually explodes. One reason for this variability is almost certainly due to the grain size of the solid explosive sample [70]. If samples were ground to the same particle size distribution then the results would be improved. A typical time-domain signal can be seen in Fig. 34. The time-domain signal always consisted of several intense bursts of acoustic emission followed by a decay after 2.5 ms. The calculation of the sensitivity value was straight-forward and a value of 180.1 Kg cm 91 was obtained. A high RMS value indicated a positive result, whereas a low RMS value indicated no detonation (Table 7). The acoustic detection of detonation proved to be very dependent on where, and how well the transducer was coupled to the metal strip resting on the sample holder, and where the strip was placed on the sample holder. The reason for this is probably due to the ease with which the released explosion products create sound waves which are intense enough to reach the transducer, through the thick steel of the sample holder. Experiments to increase the intensity of sound released due to an explosion resulted in a procedure which was too noisy (audibly) for the laboratory. These experiments used stainless steel cups (0.500 inches diameter, 0.240 inches depth, and 0.100 inches thickness). The intention was to increase the amount and reproducibility of the acoustic energy by (i) improving the confinement of the reaction gases within a stronger cup, and (ii) removing any effects caused by the variability in fracture of the brass cups. The original brass cups resulted in less audible noise, and some of the acoustic emission detected was from their deformation and cracking. 3.8 Spectrogram of Ammonium Dichromate Again it was observed that the acoustic intensity for the spectrogram of ammonium dichromate was significantly greater than the acoustic intensity observed for a blank test (no sample present). We were expecting to hear the fracture processes involved in the crushing of the solid sample, and the sounds of subsequent reaction. The initial spectra for ammonium dichromate indicated that there might be acoustic activity at frequencies beyond 400 kHz, and therefore a higher frequency band filter (400 kHz - 2 MHz) was used. The acoustic emission above 400 kHz provided a fairly reproducible frequency spectrum. The difference between a detonation (Fig. 35) and no detonation (Fig. 36) was readily seen (as expected from the RMS values) in the intensity of the emission spectrum. Likely reasons for the TEST NO. HEIGHT/cm WEIGHT/Kg E/Kg cm POS NEG REMARKS RMS/mV 1 50 3.65 182.5 + 26.90 2 50 3.60 180.0 + 39.76 3 50 3.55 177.5 - 9.77 4 50 3.60 180.0 - 24.87 5 50 3.65 182.5 - 15.42 6 50 3.70 185.0 + 38.00 7 50 3.65 182.5 + 65.55 8 50 3.60 180.0 - 20.79 9 50 3.65 182.5 + 42.59 10 50 3.60 180.0 - 26.01 11 50 3.65 182.5 -12 50 3.70 185.0 - 24.38 13 50 3.75 187.5 -14 50 3.00 190.0 + 58.39 15 50 3.75 187.5 + 42.30 16 50 3.70 105.0 + 31.10 17 50 3. (.5 5 102.5 — 1.1.07 18 19 50 3.70 185.0 + 48.61 50 3.05 102.5 + 40.07 20 50 3.70 105.0 + Table 7 Correlation of acoustic RMS values with positive and negative results for ammonium dichromate. The table shows that RMS values could be used to decifer whether a result is positive or negative Fig. !J5 Frequency spectrum for the detonation of ammonium dichromate at 102.5 Kgcm There is an intense peak around 000 kHz which appears for a positive result. The intensity of a positive result is greater than a negative result Fig. 3G Frequency spectrum for no detonation of ammonium dichromate at 102.5 Kgcm. The peak around 900 kHz is not so pronounced as that for a positive result 95 increase in intensity of the emission spectrum include crystal fracture, release of explosion products, and the high frequency emission associated with the deformation and cracking of the brass cup after the sample detonated. III.4 CONCLUSIONS 96 Acoustic emission has been successfully applied to the drop-weight tester method for measuring the sensitivity of explosives and propellants. Modifications made to the drop-weight apparatus eliminated problems in calibration caused by bounce of the drop-weight and generally increased the reproducibility of operation of the impact procedure. Once these improvements were made, acoustic emission successfully monitored a reliable series of instrument calibration experiments, and determined the presence or absence of reaction within the sample chamber for solid samples. In both cases the acoustic RMS provided a numerical basis for assigning a positive result, and was more reliable than the previously uncertain assignment of the result by the operator. Problems with the design of the liquid sample cavity resulted in the failure to quantify the sensitivity of liquid propellant samples. This work suggests that acoustic emission should prove to be a useful tool for redesign of parts of the apparatus which are presently the major sources of irrepeatability. The sample holders must be designed to respond in a more reproducible way when an explosion has occurred. The diaphragms provided by the manufacturer were too thick for successful application to the liquid propellant tested, and should be redesigned. Since the temperatures and pressures generated in the nitromethane experiments were too high for the rubber O-ring to withstand, alternative O-ring materials and designs should be evaluated. The strength of the brass caps used for solid samples should be increased. The ability to measure acoustic frequency spectra at intervals of 0.15 ms or less throughout the brief course of the drop-weight experiment has transformed this instrument from a device which provided a simple YES/NO decision per experiment into one which yields numerical information in two dimensions. 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