Alsulami, B. N. N., David, T. W., Essien, A., Kazim, S., Ahmad, S., Jacobsson, T. J., Feeney, A. and Kettle, J. (2024) Application of large datasets to assess trends in the stability of perovskite photovoltaics through machine learning. Journal of Materials Chemistry A, 12(5), pp. 3122-3132. (doi: 10.1039/D3TA05966A)
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Abstract
Current trends in manufacturing indicate that optimised decision making using new state-of-the-art machine learning (ML) technologies will be used. ML is a versatile technique that rapidly and accurately generates new insights from multifactorial data. The ML approach has been applied to a perovskite solar cell (PSC) database to elucidate trends in stability and forecast the stability of new configurations. A database consisting of 6038 entries of device characteristics, performance, and stability data was utilised, and a sequential minimal optimisation regression (SMOreg) model was employed to determine the most influential factors governing solar cell stability. When considering sub-sections of data, it was found that pin-device architectures provided the best model fittings with a training correlation efficiency of 0.963, compared to 0.699 for all device architectures. By establishing models for each PSC architecture, the analysis allows the identification of materials that can lead to improvements in stability. This paper also attempts to summarise some key challenges and trends in the current research methodologies.
| Item Type: | Articles |
|---|---|
| Additional Information: | This work was supported in part by the EPSRC Grant “Green Energy-Optimised Printed ICs (GEOPIC)” under Grant EP/W019248/1 and the grant “Technology critical metal recycling using ultrasonics and catalytic etchants” (EP/W018632/1). |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Feeney, Dr Andrew and Kettle, Professor Jeff and Alsulami, Bashayer Nafe N |
| Creator Roles: | Alsulami, B. N. N.Conceptualization, Methodology, Software, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review and editing, Visualization Feeney, A.Investigation, Data curation, Writing – review and editing, Project administration, Funding acquisition Kettle, J.Conceptualization, Methodology, Formal analysis, Investigation, Data curation, Writing – review and editing |
| Authors: | Alsulami, B. N. N., David, T. W., Essien, A., Kazim, S., Ahmad, S., Jacobsson, T. J., Feeney, A., and Kettle, J. |
| College/School: | College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering College of Science and Engineering > School of Engineering > Systems Power and Energy |
| Journal Name: | Journal of Materials Chemistry A |
| Publisher: | Royal Society of Chemistry |
| ISSN: | 2050-7488 |
| ISSN (Online): | 2050-7496 |
| Published Online: | 03 January 2024 |
| Copyright Holders: | Copyright © The Royal Society of Chemistry 2024 |
| First Published: | First published in Journal of Materials Chemistry A 12: 3122-3132 |
| Publisher Policy: | Reproduced under a Creative Commons license |
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