Atomic Positional Embedding-Based Transformer Model for Predicting the Density of States of Crystalline Materials-Reference-Cited by-同舟云学术

Atomic Positional Embedding-Based Transformer Model for Predicting the Density of States of Crystalline Materials

Published:2023-08-30 Issue:35 Volume:14 Page:7924-7930
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

Cui Yaning¹²^ORCID,Chen Kang³⁴,Zhang Lingyao¹²,Wang Haotian¹²,Bai Lei⁴,Elliston David¹,Ren Wei¹²^ORCID

Affiliation:

1. Physics Department, Materials Genome Institute, International Center for Quantum and Molecular Structures, Shanghai University, Shanghai 200444, China

2. Zhejiang Laboratory, Hangzhou 311100, China

3. School of Information Science and Technology, University of Science and Technology of China, Hefei 230026, China

4. Shanghai AI Laboratory, Shanghai 200030, China

Funder

Major Scientific Project of Zhejiang Laboratory

Science and Technology Commission of Shanghai Municipality

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

General Materials Science,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.3c02036

Reference40 articles.

1. Electronic Structure

2. Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies

3. Computational predictions of energy materials using density functional theory

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5. Innovative Materials Science via Machine Learning

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