Application of machine learning in perovskite materials and devices: A review-Reference-Cited by-同舟云学术

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Application of machine learning in perovskite materials and devices: A review

Published:2024-07 Issue: Volume:94 Page:254-272
ISSN:2095-4956
Container-title:Journal of Energy Chemistry
language:en
Short-container-title:Journal of Energy Chemistry

Author:

Chen Ming,Yin Zhenhua^ORCID,Shan Zhicheng,Zheng Xiaokai,Liu Lei,Dai Zhonghua,Zhang Jun,Liu Shengzhong (Frank),Xu Zhuo

Publisher

Elsevier BV

Reference101 articles.

1. Recent progress in development of diverse kinds of hole transport materials for the perovskite solar cells: A review

2. Materials and structures for the electron transport layer of efficient and stable perovskite solar cells

3. https://www.nrel.gov/pv/interactive-cell-efficiency.html

4. Machine Learning Interatomic Potentials as Emerging Tools for Materials Science

5. Big Data Creates New Opportunities for Materials Research: A Review on Methods and Applications of Machine Learning for Materials Design

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Developing a predictive model for the maximum power conversion efficiency of inorganic perovskites: A combined approach using density functional theory and machine learning;Computational Materials Science;2024-10

2. Breaking barriers: Novel approaches to proton-conducting oxide materials;Ceramics International;2024-10

3. Studying the Thermodynamic Phase Stability of Organic–Inorganic Hybrid Perovskites Using Machine Learning;Molecules;2024-06-22

4. Stability forecasting of perovskite solar cells utilizing various machine learning and deep learning techniques;Journal of Optics;2024-04-16

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