Rapid Data-Efficient Optimization of Perovskite Nanocrystal Syntheses through Machine Learning Algorithm Fusion
© 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH.
| Veröffentlicht in: | Advanced materials (Deerfield Beach, Fla.). - 1998. - 35(2023), 16 vom: 21. Apr., Seite e2208772 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | Advanced materials (Deerfield Beach, Fla.) |
| Schlagworte: | Journal Article Bayesian optimization Gaussian processes data-efficient optimization halide perovskites machine learning nanocrystals photoluminescence |
| Zusammenfassung: | © 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH. With the demand for renewable energy and efficient devices rapidly increasing, a need arises to find and optimize novel (nano)materials. With sheer limitless possibilities for material combinations and synthetic procedures, obtaining novel, highly functional materials has been a tedious trial and error process. Recently, machine learning has emerged as a powerful tool to help optimize syntheses; however, most approaches require a substantial amount of input data, limiting their pertinence. Here, three well-known machine-learning models are merged with Bayesian optimization into one to optimize the synthesis of CsPbBr3 nanoplatelets with limited data demand. The algorithm can accurately predict the photoluminescence emission maxima of nanoplatelet dispersions using only the three precursor ratios as input parameters. This allows us to fabricate previously unobtainable seven and eight monolayer-thick nanoplatelets. Moreover, the algorithm dramatically improves the homogeneity of 2-6-monolayer-thick nanoplatelet dispersions, as evidenced by narrower and more symmetric photoluminescence spectra. Decisively, only 200 total syntheses are required to achieve this vast improvement, highlighting how rapidly material properties can be optimized. The algorithm is highly versatile and can incorporate additional synthetic parameters. Accordingly, it is readily applicable to other less-explored nanocrystal syntheses and can help rapidly identify and improve exciting compositions' quality |
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| Beschreibung: | Date Completed 20.04.2023 Date Revised 20.04.2023 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1521-4095 |
| DOI: | 10.1002/adma.202208772 |