Dissertation/Thesis Abstract

Computationally Advancing the Predictive Ppower of the Nanoporous Materials Genome
by Witman, Matthew D, Ph.D., University of California, Berkeley, 2019, 180; 13860128
Abstract (Summary)

Since tens of thousands of nanoporous materials have been synthesized and millions have been hypothesized, our ability to both predict novel materials and their performance for a given application in a computational setting is becoming increasingly important. Utilizing simulations that can screen for optimal material performance becomes invaluable since exhaustive experimental exploration of this vast chemical space can quickly become experimentally intractable from an expense and time efficiency standpoint. This thesis is therefore dedicated to advancing the computational tools and algorithms that can be used to both predict novel materials and evaluate their performance for clean energy technologies.

Indexing (document details)
Advisor: Smit, Berend
Commitee: Reimer, Jeffrey, Neaton, Jeffrey, Mesbah, Ali
School: University of California, Berkeley
Department: Chemical Engineering
School Location: United States -- California
Source: DAI-B 81/3(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Materials science, Chemical engineering, Chemistry
Keywords: Computational chemistry, Computational materials science, Materials discovery, Materials screening
Publication Number: 13860128
ISBN: 9781088331347
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