Machine learning and linear programming models for targeting brucite-bearing serpentinite and kimberlite as feedstock for CO₂ sequestration at nickel and diamond mines

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Title	Machine learning and linear programming models for targeting brucite-bearing serpentinite and kimberlite as feedstock for CO₂ sequestration at nickel and diamond mines
Creator	Vanderzee, Sterling
Supervisor	Dipple, Gregory
Publisher	University of British Columbia
Date Issued	2024
Description	The full abstract for this item is available in the body of the item, and will be available when the embargo expires.
Genre	Thesis/Dissertation
Type	Text
Language	eng
Date Available	2026-01-31
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0447759
URI	http://hdl.handle.net/2429/90132
Degree	Doctor of Philosophy - PhD
Program	Geological Sciences
Affiliation	Science, Faculty of; Earth, Ocean and Atmospheric Sciences, Department of
Degree Grantor	University of British Columbia
Graduation Date	2025-05
Campus	UBCV
Scholarly Level	Graduate
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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Attribution-NonCommercial-NoDerivatives 4.0 International