Multimodal high-throughput approach assisted by deep learning for the analysis of ceramic saggars-Reference-Cited by-同舟云学术

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Multimodal high-throughput approach assisted by deep learning for the analysis of ceramic saggars

Published:2025-02 Issue:2 Volume:45 Page:116873
ISSN:0955-2219
Container-title:Journal of the European Ceramic Society
language:en
Short-container-title:Journal of the European Ceramic Society

Author:

Zhang Lina,Yuan Jingbin,Huang Lian’ming,Wu Wei,Wang Qi,Li Weifu,Min Xin,Han Hua,Fang Minghao

Funder

National Natural Science Foundation of China

China Academy of Space Technology

Publisher

Elsevier BV

Reference39 articles.

1. Potassium-ion batteries: outlook on present and future technologies

2. Sodium and sodium-ion energy storage batteries

3. Synthesizing low-cost, high-corrosion-resistant refractory kiln furniture for the calcination of Li-ion battery cathode materials

4. Research on saggars of lightweight design used to prepare cathode materials for Li-ion batteries

5. Use of Coal Gangue to Prepare Refractory Saggars with Superior Corrosion Resistance and Thermomechanical Properties for the Calcination of Li-Ion Battery Cathode Materials

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