Latent Representation Learning for Structural Characterization of Catalysts-Reference-Cited by-同舟云学术

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Latent Representation Learning for Structural Characterization of Catalysts

Published:2021-02-23 Issue:8 Volume:12 Page:2086-2094
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

Routh Prahlad K.¹,Liu Yang¹,Marcella Nicholas¹^ORCID,Kozinsky Boris²³^ORCID,Frenkel Anatoly I.¹⁴^ORCID

Affiliation:

1. Department of Materials Science and Chemical Engineering, Stony Brook University, Stony Brook, New York 11794, United States

2. John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States

3. Bosch Research, Cambridge, Massachusetts 02139, United States

4. Division of Chemistry, Brookhaven National Laboratory, Upton, New York 11973, United States

Funder

Basic Energy Sciences

Publisher

American Chemical Society (ACS)

Subject

General Materials Science,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.0c03792

Reference74 articles.

1. Heterogeneous Catalysis: A Central Science for a Sustainable Future

2. When Gold Is Not Noble: Catalysis by Nanoparticles

3. Tangential Ligand-Induced Strain in Icosahedral Au13

4. Shape-Dependent Catalytic Properties of Pt Nanoparticles

5. Computational Design of Alloy-Core@Shell Metal Nanoparticle Catalysts

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3. From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design;ACS Catalysis;2024-07-24

4. AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy;Nature Communications;2024-07-15

5. Emerging Atomistic Modeling Methods for Heterogeneous Electrocatalysis;Chemical Reviews;2024-07-11

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