Unveiling the physical mechanisms driving delafossite crystal (ABX<sub>2</sub>) formation through interpretable machine learning-Reference-Cited by-同舟云学术

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Unveiling the physical mechanisms driving delafossite crystal (ABX₂) formation through interpretable machine learning

Published:2024 Issue:49 Volume:60 Page:6324-6327
ISSN:1359-7345
Container-title:Chemical Communications
language:en
Short-container-title:Chem. Commun.

Author:

Xu Ning¹,Li Zheng¹,Fu Xiaolan¹,Hu Xiaojuan²³,Xu Wenwu¹^ORCID,Han Zhong-Kang³^ORCID

Affiliation:

1. Department of Physics, School of Physical Science and Technology, Ningbo University, Ningbo, 315211, China

2. Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany

3. School of Materials Science and Engineering, Zhejiang University, Hangzhou, 310027, China

Abstract

A method integrating machine learning with first-principles calculations is employed to forecast the formation energy of delafossite crystals, facilitating the rapid identification of stable crystals.

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/CC/D4CC01490A

Reference36 articles.

1. p‐Type Near‐Infrared Transparent Delafossite Thin Films with Ultrahigh Conductivity

2. Solution‐Processable Epitaxial Metallic Delafossite Oxide Films

3. Reactive Templated Grain Growth and Thermoelectric Power Factor Enhancement of Textured CuFeO2 Ceramics

4. Fundamental properties of delafossite CuFeO2 as photocatalyst for solar energy conversion

5. Delafossite as hole transport layer a new pathway for efficient perovskite-based solar sells: Insight from experimental, DFT and numerical analysis

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