Griego, Charles D
(2022)
Rethinking Computational Catalyst Searches with Alchemical Perturbation Density Functional Theory.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
The expense of quantum chemistry calculations significantly hinders endeavors to search through diverse materials space for catalysts that promote sustainable production of energy and chemicals. Motivated by this challenge, we report our study on alchemical perturbation density functional theory (APDFT), an easy and highly cost-efficient calculation scheme that enables high-throughput computational screening of hypothetical catalysts. APDFT requires just a small number of reference DFT calculations to approximate quantities such as adsorbate binding energies (BE) and reaction barriers on a large numbers of hypothetical catalyst surfaces by employing simple arithmetic manipulations to electrostatic potentials. In this dissertation, we discuss how APDFT can be used to rapidly predict catalyst descriptors from numerous atomic transmutations done to a single reference catalyst, and we address multiple factors that influence the accuracy of these predictions. We first demonstrate that first order APDFT predicts adsorbate BE on many variations of carbide, nitride, and oxide catalysts in close agreement with DFT results, and we determined that predictions based in metallic systems are most accurate. Additionally, first order APDFT reliably predicts many energy profiles and barrier heights using a single nudged elastic band calculation for CH4 dehydrogenation on Pt(111). Machine learning models trained on correlations between APDFT errors and reference system properties produced BE prediction corrections over multiple classes of adsorbates at multiple coverages on hypothetical Pt alloys. We further uncover these correlations by revisiting multiple catalyst systems with second order APDFT approximations from VASP and CP2K data. Finally, we introduce ways to produce alchemical energy functions that help illustrate the agreement between reference system with differing characteristics and increasing orders of APDFT. We find that there are greater limitations with VASP for second order APDFT, but results from CP2K show promising advances with APDFT for widespread applications in computational materials science.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
|
| Date: |
10 June 2022 |
| Date Type: |
Publication |
| Defense Date: |
1 April 2022 |
| Approval Date: |
10 June 2022 |
| Submission Date: |
6 April 2022 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
108 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Chemical Engineering |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
computational chemistry, heterogeneous catalysis, materials screening |
| Date Deposited: |
10 Jun 2022 18:52 |
| Last Modified: |
10 Jun 2022 18:52 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/42521 |
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