Investigation on the Structure Profile of Precise Copper Tube by Three-Roll Planetary Rolling Based on Finite Element Simulation Assisted by Machine Learning DOI
Jinsong Liu,

Y.H. Sun,

Dayong Chen

et al.

Journal of Materials Engineering and Performance, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 3, 2024

Language: Английский

Luminescence From Localized States in Solids: A First‐Principles Perspective DOI Open Access

Zewei Li,

Jiahao Xie, Muhammad Faizan

et al.

Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown

Published: March 3, 2025

Abstract Localized‐state luminescence (LSL) has emerged as a promising mechanism for high‐performance optoelectronic applications, including lighting, photodetection, and quantum technologies. Characterized by rich intriguing spectral features, LSL involves significant electron‐phonon coupling, which varies in strength across different systems. First‐principles methods, particularly density functional theory (DFT) its extensions provide an efficient framework modeling the process with reasonable accuracy. This comprehensive review examines DFT‐based studies on three representative types of solids: from self‐trapped excitons (STEs), normal defects, intentionally doped ions. The discussion begins overview entire process, highlighting computational methods excited state structures energies, well simulations luminescent spectrum within multi‐phonon transition framework. Detailed discussions follow, focusing structural distortion modes STEs, behavior mechanisms Finally, strategies to address current challenges advance theoretical design materials are proposed, offering valuable insights future developments field.

Language: Английский

Citations

1
Application of machine learning in polyimide structure design and property regulation DOI Creative Commons

Wenjia Huo,

Haiyue Wang, Liying Guo

et al.

High Performance Polymers, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Polyimide (PI) is widely used in modern industry due to its excellent properties. Its synthesis methods and property research have significantly progressed. However, the design regulation of PI structures through traditional technologies are slow expensive, which make it difficult meet practical demand materials. With rapid development high-throughput computing data-driven technology, machine learning (ML) has become an important method for exploring new Data-driven ML envisaged as a decisive enabler PIs discovery. This paper first introduces basic workflow common algorithms ML. Secondly, applications material properties prediction, assisting computational simulation inverse desired reviewed. Finally, we discuss main challenges possible solutions research.

Language: Английский

Citations

0
Machine learning strategies for small sample size in materials science DOI
Qiuling Tao,

Jinxin Yu,

Xiangyu Mu

et al.

Science China Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Language: Английский

Citations

0
Machine learning-driven insights into biaxial strain-induced anomalous thermal conductivity enhancement of boron arsenide DOI
Yikun Liu, Yurong He,

Tianqi Tang

et al.

Science China Technological Sciences, Journal Year: 2025, Volume and Issue: 68(5)

Published: April 7, 2025

Language: Английский

Citations

0
Editorial: special topic on computation-assisted materials screening and design DOI Open Access
Jinlan Wang, Chenghua Sun, Shaohua Dong

et al.

Science China Materials, Journal Year: 2024, Volume and Issue: 67(4), P. 1011 - 1013

Published: March 26, 2024

Language: Английский

Citations

2
Crystal structure graph neural networks for high-performance superconducting critical temperature prediction DOI

Jingzi Zhang,

Chengquan Zhong, Xiaoting Lu

et al.

Science China Materials, Journal Year: 2024, Volume and Issue: 67(10), P. 3253 - 3261

Published: Aug. 23, 2024

Language: Английский

Citations

0
The Imaginary and the Real in Mathematics and Its Applications DOI
Viktor Krasnoshchekov, Natalia Semenova, Leonid Maslov

et al.

Lecture notes in networks and systems, Journal Year: 2024, Volume and Issue: unknown, P. 27 - 44

Published: Jan. 1, 2024

Language: Английский

Citations

0
Investigation on the Structure Profile of Precise Copper Tube by Three-Roll Planetary Rolling Based on Finite Element Simulation Assisted by Machine Learning DOI
Jinsong Liu,

Y.H. Sun,

Dayong Chen

et al.

Journal of Materials Engineering and Performance, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 3, 2024

Language: Английский

Citations

0