Data-Driven Perovskite Design via High-Throughput Simulation and Machine Learning

Perovskites (ABX3) exhibit remarkable potential in optoelectronic conversion, catalysis, and diverse energy-related fields. However, the tunability of A, B, and X-site compositions renders conventional screening methods labor-intensive and inefficient. This review systematically synthesizes the role...

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Vydané v:	Processes Ročník 13; číslo 10; s. 3049
Hlavní autori:	Wang, Yidi, Sun, Dan, Zhao, Bei, Zhu, Tianyu, Liu, Chengcheng, Xu, Zixuan, Zhou, Tianhang, Xu, Chunming
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.10.2025
Predmet:	Accuracy Algorithms Analysis Catalysis Computer applications Critical phenomena Crystal structure Efficiency Electrocatalysts Embedding Energy storage Force and energy Functional materials Heterogeneity Iodine Learning algorithms Learning strategies Machine learning Material properties Optimization Optoelectronics Performance measurement Performance prediction Perovskite Perovskites Phase transitions Photovoltaic cells Point defects Simulation Simulation methods Solar cells
ISSN:	2227-9717, 2227-9717
On-line prístup:	Získať plný text
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