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Document type:
Zeitschriftenaufsatz 
Author(s):
Stanley, J.C.; Mayr, F.; Gagliardi, A. 
Title:
Machine Learning Stability and Bandgaps of Lead‐Free Perovskites for Photovoltaics 
Abstract:
Compositional engineering of perovskites has enabled the precise control of material properties required for their envisioned applications in photovoltaics. However, challenges remain to address efficiency, stability, and toxicity simultaneously. Mixed lead‐free and inorganic perovskites have recently demonstrated potential for resolving such issues but their composition space is gigantic, making it difficult to discover promising candidates even using high‐throughput methods. A machine learning...    »
 
Keywords:
density functional theory feature engineering lead‐free perovskites machine learning materials prediction 
Journal title:
Adv. Theory Simul. 2019, 1900178 2019-11 
Year:
2019 
Year / month:
2019-11 
Quarter:
4. Quartal 
Month:
Nov 
Pages contribution:
1-6 
Language:
en 
Fulltext / DOI:
Publisher:
Wiley Online Library