Rational Atom Substitution to Obtain Efficient, Lead‐Free Photocatalytic Perovskites Assisted by Machine Learning and DFT Calculations

Author:

Li Xuying1,Mai Haoxin1ORCID,Lu Junlin2,Wen Xiaoming12ORCID,Le Tu C.3ORCID,Russo Salvy P.4ORCID,Winkler David A.567ORCID,Chen Dehong1ORCID,Caruso Rachel A.1ORCID

Affiliation:

1. Applied Chemistry and Environmental Science School of Science STEM College RMIT University Melbourne Victoria 3000 Australia

2. School of Science, Computing and Engineering Technologies Swinburne University of Technology Hawthorn Victoria 3122 Australia

3. School of Engineering STEM College RMIT University GPO Box 2476 Melbourne Victoria 3001 Australia

4. ARC Centre of Excellence in Exciton Science School of Science RMIT University Melbourne Victoria 3000 Australia

5. Monash Institute of Pharmaceutical Sciences Monash University Parkville Victoria 3052 Australia

6. School of Biochemistry and Chemistry La Trobe University Kingsbury Drive Bundoora Victoria 3042 Australia

7. School of Pharmacy University of Nottingham Nottingham NG7 2RD UK

Abstract

AbstractInorganic lead‐free halide perovskites, devoid of toxic or rare elements, have garnered considerable attention as photocatalysts for pollution control, CO2 reduction and hydrogen production. In the extensive perovskite design space, factors like substitution or doping level profoundly impact their performance. To address this complexity, a synergistic combination of machine learning models and theoretical calculations were used to efficiently screen substitution elements that enhanced the photoactivity of substituted Cs2AgBiBr6 perovskites. Machine learning models determined the importance of d10 orbitals, highlighting how substituent electron configuration affects electronic structure of Cs2AgBiBr6. Conspicuously, d10‐configured Zn2+ boosted the photoactivity of Cs2AgBiBr6. Experimental verification validated these model results, revealing a 13‐fold increase in photocatalytic toluene conversion compared to the unsubstituted counterpart. This enhancement resulted from the small charge carrier effective mass, as well as the creation of shallow trap states, shifting the conduction band minimum, introducing electron‐deficient Br, and altering the distance between the B‐site cations d band centre and the halide anions p band centre, a parameter tuneable through d10 configuration substituents. This study exemplifies the application of computational modelling in photocatalyst design and elucidating structure–property relationships. It underscores the potential of synergistic integration of calculations, modelling, and experimental analysis across various applications.

Funder

Australian Research Council

Centre of Excellence in Exciton Science

Publisher

Wiley

Subject

General Chemistry,Catalysis

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