logo
ResearchBunny Logo
Machine learning-enabled chemical space exploration of all-inorganic perovskites for photovoltaics

Chemistry

Machine learning-enabled chemical space exploration of all-inorganic perovskites for photovoltaics

J. Kim, J. Noh, et al.

Discover a groundbreaking framework for designing B-site-alloyed ABX3 metal halide perovskites using advanced DFT and ML techniques. Researchers Jin-Soo Kim, Juhwan Noh, and Jino Im identify 10 promising compounds, including CsGe0.3125Sn0.6875I3, optimized for next-generation solar cells.

00:00
00:00
Playback language: English
Abstract
This paper proposes a framework for designing B-site-alloyed ABX3 metal halide perovskites (MHPs) using density functional theory (DFT) and machine learning (ML). A crystal graph convolutional neural network (CGCNN) was trained on 3159 DFT datasets to predict decomposition energy, bandgap, and bandgap type. The trained model explored the chemical space of 41,400 B-site-alloyed MHPs, identifying 10 promising compounds with optimal bandgaps for single-junction and tandem solar cells, namely CsGe0.3125Sn0.6875I3 and CsGe0.0625Pb0.3125Sn0.625Br3.
Publisher
npj Computational Materials
Published On
May 08, 2024
Authors
Jin-Soo Kim, Juhwan Noh, Jino Im
Tags
B-site-alloyed
metal halide perovskites
density functional theory
machine learning
solar cells
bandgap
decomposition energy

Related Publications

Explore these studies to deepen your understanding of the subject.

Small dataset machine-learning approach for efficient design space exploration: engineering ZnTe-based high-entropy alloys for water splitting
Engineering and Technology

Small dataset machine-learning approach for efficient design space exploration: engineering ZnTe-based high-entropy alloys for water splitting

S. V. Oh, S. Yoo, et al.

Interpretable machine learning-based decision support for prediction of antibiotic resistance for complicated urinary tract infections
Medicine and Health

Interpretable machine learning-based decision support for prediction of antibiotic resistance for complicated urinary tract infections

J. Yang, D. W. Eyre, et al.

Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials
Engineering and Technology

Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials

S. Kang, W. Jeong, et al.

Exploring the mechanism of path-creating strategy for latecomers: a combined approach of econometrics and causal machine learning
Business

Exploring the mechanism of path-creating strategy for latecomers: a combined approach of econometrics and causal machine learning

Y. Teng, Y. Li, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny