Stability prediction of gold nanoclusters with different ligands and doped metals: deep learning and experimental tests-Reference-Cited by-同舟云学术

Stability prediction of gold nanoclusters with different ligands and doped metals: deep learning and experimental tests

Published:2024 Issue:8 Volume:12 Page:4460-4472
ISSN:2050-7488
Container-title:Journal of Materials Chemistry A
language:en
Short-container-title:J. Mater. Chem. A

Author:

Gu Yuming¹,Tang Shisi¹,Liu Xu¹^ORCID,Liang Xinyi¹,Zhu Qin¹,Wu Hongfeng²,Yang Xiao³,Jin Weihao¹,Chen Hongwei¹,Liu Chunyan⁴,Zhu Yan¹^ORCID,Ma Jing¹^ORCID

Affiliation:

1. Key Laboratory of Mesoscopic Chemistry of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China

2. Medical School, Kunming University of Science and Technology, Kunming, 650500, P. R. China

3. National Engineering Research Center for Biomaterials, Sichuan University, Chengdu, 610064, P. R. China

4. School of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082, P. R. China

Abstract

The formation energy of gold nanoclusters could be predicted quickly by deep learning.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/TA/D3TA06892G

Reference67 articles.

1. Atomically Precise Gold Nanoclusters as New Model Catalysts

2. Atomically Precise Clusters of Noble Metals: Emerging Link between Atoms and Nanoparticles

3. Atomically Precise Colloidal Metal Nanoclusters and Nanoparticles: Fundamentals and Opportunities

4. Nonscalable Oxidation Catalysis of Gold Clusters

5. A grand unified model for liganded gold clusters

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