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ORIGINAL RESEARCH ARTICLE

Data-driven identification of functional additives and solution parameters in mixed Sn-Pb perovskite solar cells via β-VAE augmentation

Behzad Iranipour1 ,  Mohammadreza Sadeghian2 ,  Ezeddin Mohajerani1*
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1 Laboratory of Photonics of Organic Materials and Polymers (POMP), Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, Iran
2 Faculty of Physics, Shahid Beheshti University, Tehran, Iran
IJAMD, 025480051 https://doi.org/10.36922/IJAMD025480051
Received: 30 November 2025 | Revised: 31 January 2026 | Accepted: 9 February 2026 | Published online: 26 March 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Optimizing perovskite solar cells (PSCs) requires precise control of solution chemistry and functional additives. However, limited experimental data hinder systematic discovery. Here, we integrate 1,540 carefully selected experimental device records with 4,000 synthetic data points generated by a beta-variational autoencoder to investigate solution parameters and organic additives governing device performance. A residual neural network trained on this hybrid dataset achieves strong predictive accuracy with an R2 of 0.87 for power conversion efficiency. Even when trained solely on synthetic data, the model attains an R2 of 0.785. Within this framework, 733 organic additives with diverse functional groups were evaluated to identify molecular features that enhance absorber quality. High-efficiency PSCs are associated with solution concentrations above 1.3 molar and elevated formamidinium iodide (FAI) ratios, in combination with additives containing benzene rings, methylene, and amine groups. Notably, a composition comprising FAI (1.05), cesium iodide (0.03), methylammonium chloride (0.3), lead(II) iodide (1.5), and a molybdenum trioxide interlayer, combined with 1,3-dihydro-1-[1-(phenylmethyl)-4-piperidinyl]-2Hbenzimidazol-2-one as an additive, yields a PCE of 25.66%. This additive was absent from the training data, demonstrating the capability of the proposed framework to discover novel and effective organic additives for PSC optimization.

Graphical abstract
Keywords
Perovskite solar cell
Experimental data
Synthetic data
Additive
Funding
None.
Conflict of interest
The authors declare that they have no competing interests.
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