Inverse design workflow discovers hole-transport materials tailored for perovskite solar cells

The inverse design of tailored organic molecules for specific optoelectronic devices of high complexity holds an enormous potential but has not yet been realized. Current models rely on large data sets that generally do not exist for specialized research fields. We demonstrate a closed-loop workflow that combines high-throughput synthesis of organic semiconductors to create large datasets and Bayesian optimization to discover new hole-transporting materials with tailored properties for solar cell applications. The predictive models were based on molecular descriptors that allowed us to link the structure of these materials to their performance. A series of high-performance molecules were identified from minimal suggestions and achieved up to 26.2% (certified 25.9%) power conversion efficiency in perovskite solar cells.

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Publication Details

Journal
Science
Published
2024-12-12
DOI
https://doi.org/10.1126/science.ads0901
Citations
135
Primary Topic
Perovskite Materials and Applications
Type
article
Field-Weighted Citation Impact
28.17
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article

Inverse design workflow discovers hole-transport materials tailored for perovskite solar cells

Christoph Josef Brabec, Byung‐wook Park, Juan S. Rocha‐Ortiz, Larry Lüer et al.
135 citations
Science
Perovskite Materials and Applications
28.17
article

Inverse design workflow discovers hole-transport materials tailored for perovskite solar cells

Christoph Josef Brabec, Byung‐wook Park, Juan S. Rocha‐Ortiz, Larry Lüer, Yicheng Zhao, Sang Il Seok, Kaicheng Zhang, Dirk M. Guldi, M. Eugenia Pérez‐Ojeda, Anastasia Barabash, Patrick Reiser, Luyao Wang, Pascal Friederich, Jianchang Wu, Luca Torresi, Jiyun Zhang, Jens Hauch, Lin‐Long Deng, Yunuo Wang, Junsheng Luo, Zhiqiang Xie, Manli Hu
article en
135 citations

Abstract

The inverse design of tailored organic molecules for specific optoelectronic devices of high complexity holds an enormous potential but has not yet been realized. Current models rely on large data sets that generally do not exist for specialized research fields. We demonstrate a closed-loop workflow that combines high-throughput synthesis of organic semiconductors to create large datasets and Bayesian optimization to discover new hole-transporting materials with tailored properties for solar cell applications. The predictive models were based on molecular descriptors that allowed us to link the structure of these materials to their performance. A series of high-performance molecules were identified from minimal suggestions and achieved up to 26.2% (certified 25.9%) power conversion efficiency in perovskite solar cells.

ScienceVol. 386(6727)
Karlsruhe Institute of Technology (DE), University of Electronic Science and Technology of China (CN), University of Groningen (NL), Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Xiamen University (CN), International Council on Mining and Metals (GB), Helmholtz Institute Erlangen-Nürnberg (DE), National Engineering Research Center of Electromagnetic Radiation Control Materials (CN), Collaborative Innovation Center of Chemistry for Energy Materials (CN), Ulsan National Institute of Science and Technology (KR)
Affordable and clean energy
Openalex Percentile: Top 0%
Perovskite Materials and Applications
28.17
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