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Artificial intelligence-driven paradigms for layered cathode materials: A systematic framework for multi-scale engineering

Year: 2026

Type: article

Source: Nano Energy

DOI: 10.1016/j.nanoen.2026.111978

Authors: Jingguo Gao, Tao Huang, Yuan Zhang, Yuan Zhang, Bin Chen, Xiangzhong Ren, Jiangtao Hu, Qianling Zhang, Heping Xie

Institution: Shenzhen University

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: closed

Funders: National Natural Science Foundation of China, Shenzhen University, Department of Education of Guangdong Province, Development and Reform Commission of Shenzhen Municipality, Shenzhen Science and Technology Innovation Program

Awards: G3085113786, G4519385417, G5179022082

OpenAlex ID: W7155165948

FWCI: 2.771

Cites: 134

Cited by: 2

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