Hard and superconducting cubic boron phase via swarm-intelligence structural prediction driven by a machine-learning potential-Reference-Cited by-同舟云学术

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Hard and superconducting cubic boron phase via swarm-intelligence structural prediction driven by a machine-learning potential

Published:2021-01-08 Issue:2 Volume:103 Page:
ISSN:2469-9950
Container-title:Physical Review B
language:en
Short-container-title:Phys. Rev. B

Author:

Yang Qiuping^ORCID,Lv Jian,Tong Qunchao^ORCID,Du Xin,Wang Yanchao,Zhang Shoutao^ORCID,Yang Guochun^ORCID,Bergara Aitor^ORCID,Ma Yanming

Funder

National Natural Science Foundation of China

Postdoctoral Science Foundation of Jiangsu Province

Natural Science Foundation of Jilin Province

Higher Education Discipline Innovation Project

Ministerio de Ciencia e Innovación

Jilin Province Out-standing Young Talents project

Publisher

American Physical Society (APS)

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevB.103.024505/fulltext

Reference89 articles.

1. The Origin of the Term Allotrope

2. The era of carbon allotropes

3. Broad Family of Carbon Nanoallotropes: Classification, Chemistry, and Applications of Fullerenes, Carbon Dots, Nanotubes, Graphene, Nanodiamonds, and Combined Superstructures

4. Penta-graphene: A new carbon allotrope

5. Direct Band Gap Silicon Allotropes

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1. Machine learned interatomic potentials for ternary carbides trained on the AFLOW database;npj Computational Materials;2024-07-02

2. Theoretical Design of Strengthened Nanotwinned γ*-Boron;The Journal of Physical Chemistry Letters;2024-03-06

3. Predictions of Boron Phase Stability Using an Efficient Bayesian Machine Learning Interatomic Potential;The Journal of Physical Chemistry Letters;2024-02-23

4. Structure searches and superconductor discovery in XB₂ (X = Sc, Ti, V, Cr, and Tc);RSC Advances;2024

5. Machine-learning approach for discovery of conventional superconductors;Physical Review Materials;2023-05-31

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