The development and applications of autonomous process optimization systems
department or school: Science, Faculty of
department or school: Chemistry, Department of
data provider: DSpace
degree campus: UBCV
creator: Christensen, Melodie Deniz
issued: 2022-12-05T23:55:55Z
issued: 2022
related degree: Doctor of Philosophy - PhD
degree grantor: University of British Columbia
description: Autonomous process optimization involves the human-intervention free search of an input parameter space in order to minimize or maximize output parameters of interest. These systems automate the repetitive and manual approach to process optimization that currently dominates the field. The field of autonomous process optimization is in its infancy and a majority of examples have focused on flow reactor-based systems, however, not all processes can be executed in flow reactors due to heterogeneity or long reaction times. We extended this novel technology to high-throughput microscale batch reactors through the integration of commercial Chemspeed robotics platforms with online analytical instruments and optimization algorithms using a Python interface. The first system was applied to the optimization of a stereoselective Suzuki-Miyaura process, and the second to the optimization of a Wohl-Ziegler photobromination process. We found that optimization performance was impacted by the definition of the search space, the appropriate representation of chemical structure, the optimization algorithm, the acquisition function and the selection of the appropriate reactor and analysis technology. These aspects are discussed in detail for each case study. Finally, the analysis of multivariate optimization data proved to be a challenging proposition, and we found that qualitative machine learning approaches such as random forest modeling allowed for the determination of parameter influences in an effective way. The strategy that we have implemented for autonomous process optimization has the potential to be scaled to additional robotic and analytical instruments, as well as optimization algorithms, through its modular Python interface. We envision a future where the utilization of such systems is commonplace.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/83357
note: THE DEVELOPMENT AND APPLICATIONS OF AUTONOMOUS PROCESS OPTIMIZATION SYSTEMS by Melodie Deniz Christensen B.Sc., American University, 2002 M.S., American University, 2003 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Chemistry) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) December 2022 © Melodie Christensen, 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: The Development and Applications of Autonomous Process Optimization Systems submitted by Melodie Christensen in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Chemistry Examining Committee: Jason Hein, Associate Professor, Chemistry, UBC Supervisor Gregory Dake, Associate Professor, Chemistry, UBC Supervisory Committee Member Michael Wolf, Professor & Head, Chemistry, UBC University Examiner Jeff Clune, Associate Professor, Computer Science, UBC University Examiner Additional Supervisory Committee Members: Laurel Schafer, Professor, Chemistry, UBC Supervisory Committee Member Stephen Withers, Professor, Chemistry, UBC Supervisory Committee Member iii Abstract Autonomous process optimization involves the human-intervention free search of an input parameter space in order to minimize or maximize output parameters of interest. These systems automate the repetitive and manual approach to process optimization that currently dominates the field. The field of autonomous process optimization is in its infancy and a majority of examples have focused on flow reactor-based systems, however, not all processes can be executed in flow reactors due to heterogeneity or long reaction times. We extended this novel technology to high-throughput microscale batch reactors through the integration of commercial Chemspeed robotics platforms with online analytical instruments …
has type: Thesis/Dissertation
date issued: 2023-05
is shown at: 10.14288/1.0422385
language: eng
degree discipline: Chemistry
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Hein, Jason
type: Text
identifier URI: http://hdl.handle.net/2429/83357