Autonomous closed-loop framework for reproducible perovskite solar cells

Gao D, Lu S, Zhang C, Wang N, Yu Z, Sun X, Martin R, Vanin F, Qian L, Long N, Lüer L, Li B, Stolterfoht M, Hou J, Yin J, Lin YH, Lu H, Li N, Gasparini N, Brabec C, Stranks SD, Zeng XC, Zhu Z (2026)

Publication Type: Journal article

Publication year: 2026

Journal

Nature Nature Research

Book Volume: 653

Pages Range: 707-714

Journal Issue: 8115

DOI: 10.1038/s41586-026-10482-y

Abstract

The commercialization of perovskite solar cells (PSCs) is bottlenecked by inefficient trial-and-error approaches reliant on human expertise in both materials discovery and device fabrication1, 2–3. Here we introduce an autonomous closed-loop framework that integrates machine learning (ML)-driven materials discovery with an automated manufacturing platform. The system uses active learning and quantum modelling to rapidly identify high-performance molecules and the platform uses Bayesian optimization and symbolic regression in a feedback loop to continuously refine the fabrication process. This integrated approach enabled the discovery of a passivation molecule, 5-(aminomethyl)nicotinonitrile hydroiodide (5ANI), which yielded 0.05-cm2 solar cells with a power conversion efficiency (PCE) of 27.22% (certified maximum power point tracking (MPPT) efficiency of 27.18%) and 21.4-cm2 mini-modules with a PCE of 23.49%. Moreover, the devices exhibited long-term operational stability, retaining 98.7% of their initial efficiency after 1,200 h of continuous operation under the ISOS-L-1I protocol. Crucially, the automated platform achieved an efficiency reproducibility nearly five times that of manual fabrication. This work establishes an automated closed-loop system that synergizes ML-powered discovery with the high-fidelity data from automated manufacturing, setting a benchmark for autonomous discovery and manufacturing in photovoltaics and materials.

Authors with CRIS profile

Larry Lüer Institute Materials for Electronics and Energy Technology (i-MEET) Christoph Brabec Institute Materials for Electronics and Energy Technology (i-MEET)

Involved external institutions

City University of Hong Kong (CityU) CN China (CN) University of Cambridge GB United Kingdom (GB) Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB) The Chinese University of Hong Kong (CUHK) CN China (CN) Hong Kong Polytechnic University (PolyU) CN China (CN) Hong Kong University of Science and Technology (HKUST) / 香港科技大學 CN China (CN)

How to cite

APA:

Gao, D., Lu, S., Zhang, C., Wang, N., Yu, Z., Sun, X.,... Zhu, Z. (2026). Autonomous closed-loop framework for reproducible perovskite solar cells. Nature, 653(8115), 707-714. https://doi.org/10.1038/s41586-026-10482-y

MLA:

Gao, Danpeng, et al. "Autonomous closed-loop framework for reproducible perovskite solar cells." Nature 653.8115 (2026): 707-714.

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