Machine Learning for Revealing Spatial Dependence among Nanoparticles: Understanding Catalyst Film Dewetting via Gibbs Point Process Models-Reference-Cited by-同舟云学术

Machine Learning for Revealing Spatial Dependence among Nanoparticles: Understanding Catalyst Film Dewetting via Gibbs Point Process Models

Published:2020-12-09 Issue:50 Volume:124 Page:27479-27494
ISSN:1932-7447
Container-title:The Journal of Physical Chemistry C
language:en
Short-container-title:J. Phys. Chem. C

Author:

Aziz Ezzat Ahmed¹,Bedewy Mostafa²^ORCID

Affiliation:

1. Department of Industrial & Systems Engineering, Rutgers University, New Brunswick, New Jersey 08901-8554, United States

2. Department of Industrial Engineering, Department of Chemical and Petroleum Engineering, Department of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States

Funder

Division of Civil, Mechanical and Manufacturing Innovation

Publisher

American Chemical Society (ACS)

Subject

Surfaces, Coatings and Films,Physical and Theoretical Chemistry,General Energy,Electronic, Optical and Magnetic Materials

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcc.0c07765

Reference76 articles.

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2. Synthesis and catalytic properties of metal nanoparticles: Size, shape, support, composition, and oxidation state effects

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4. Control of metal-support interactions in heterogeneous catalysts to enhance activity and selectivity

5. Effect of interparticle interaction on the low temperature oxidation of CO over size-selected Au nanocatalysts supported on ultrathin TiC films

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