Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy-Reference-Cited by-同舟云学术

Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy

Published:2020 Issue:34 Volume:22 Page:18902-18910
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Marcella Nicholas¹²³⁴⁵^ORCID,Liu Yang⁶²³⁴⁵,Timoshenko Janis¹²³⁴⁵^ORCID,Guan Erjia¹²³⁴⁵,Luneau Mathilde⁷⁸⁹⁵,Shirman Tanya¹⁰⁸⁹⁵¹¹^ORCID,Plonka Anna M.¹²³⁴⁵,van der Hoeven Jessi E. S.⁷⁸⁹⁵¹⁰,Aizenberg Joanna⁷⁸⁹⁵¹⁰^ORCID,Friend Cynthia M.⁷⁸⁹⁵¹⁰^ORCID,Frenkel Anatoly I.¹²³⁴⁵^ORCID

Affiliation:

1. Department of Materials Science and Chemical Engineering

2. Stony Brook University

3. Stony Brook

4. New York 11794

5. USA

6. Department of Chemistry

7. Department of Chemistry and Chemical Biology

8. Harvard University

9. Cambridge

10. John A. Paulson School of Engineering and Applied Sciences

11. Wyss Institute for Biologically Inspired Engineering

Abstract

Trained neural networks are used to extract the first partial coordination numbers from XANES spectra. In bimetallic nanoparticles, the four local structure descriptors provide rich information on structural motifs.

Funder

Basic Energy Sciences

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2020/CP/D0CP02098B

Reference56 articles.

1. Pd–Au bimetallic catalysts: understanding alloy effects from planar models and (supported) nanoparticles

2. Importance of electronic ligand effects in metal alloy catalysts

3. Synthesis, catalysis, surface chemistry and structure of bimetallic nanocatalysts