Machine-learning approach for discovery of conventional superconductors-Reference-Cited by-同舟云学术

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Machine-learning approach for discovery of conventional superconductors

Published:2023-05-31 Issue:5 Volume:7 Page:
ISSN:2475-9953
Container-title:Physical Review Materials
language:en
Short-container-title:Phys. Rev. Materials

Author:

Tran Huan^ORCID,Vu Tuoc N.^ORCID

Funder

Quỹ Đổi mới sáng tạo Vingroup

National Science Foundation

San Diego Supercomputer Center

Publisher

American Physical Society (APS)

Subject

Physics and Astronomy (miscellaneous),General Materials Science

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevMaterials.7.054805/fulltext

Reference109 articles.

1. Conventional superconductivity at 203 kelvin at high pressures in the sulfur hydride system

2. Superconductivity at 250 K in lanthanum hydride under high pressures

3. Room-temperature superconductivity in a carbonaceous sulfur hydride

4. Pressure-induced metallization of dense (H2S)2H2 with high-Tc superconductivity

5. High-temperature superconductivity in alkaline and rare earth polyhydrides at high pressure: A theoretical perspective

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1. Molecular hydrogen in the N-doped LuH3 system as a possible path to superconductivity;Nature Communications;2024-08-23

2. Discovery of novel materials through machine learning;Journal of Physics: Condensed Matter;2024-08-14

3. High- Tc superconductivity in squeezed cubic CSeH6 and C2TeH8 ternary polyhydrides;Physical Review B;2024-05-03

4. Unleashing the power of artificial intelligence in phonon thermal transport: Current challenges and prospects;Journal of Applied Physics;2024-05-02

5. Feasible Route to High-Temperature Ambient-Pressure Hydride Superconductivity;Physical Review Letters;2024-04-15

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