Work

An interpretable LSTM deep learning model predicts the time-dependent swelling behavior in CERCER composite fuels

Year: 2023

Type: article

Source: Materials Today Communications

DOI: 10.1016/j.mtcomm.2023.106998

Authors: Yunmei Zhao, Zhenyue Chen, Yiqun Dong, Jingqi Tu

Institutions: Tongji University, Fudan University

Language: English

Topic: Nuclear Materials and Properties

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: green

Funders: Natural Science Foundation of Shanghai, National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities

Awards: G3933237326, G7441660939

OpenAlex ID: W4386401729

FWCI: 0.913

Cites: 43

Cited by: 13

Related to: 10