Fabricating perovskite solar cells with robotic boxes

<p class="p1"><span class="s1">An international research team has developed an AI-driven robotic platform that autonomously designs, fabricates, and optimizes perovskite solar cells, completing the full experimental workflow in a closed-loop system. Using the platform, the researchers fabricated and tested more than 50,000 devices, achieving efficiencies of up to 27%.</span></p><p>An international research team has developed an AI-driven robotic platform capable of autonomously designing, fabricating, and optimizing perovskite solar cells.</p>
<p>“At the core of the study is the idea that robotic experimentation should do more than automate repetitive operations,” the researchers said in a statement. “Formulas and parameters are encoded into machine-readable recipes, translated into robot-executable commands, and then returned as structured feedback after fabrication and characterization. In this way, the system establishes a closed-loop workflow that links recommendation, execution, validation, and model improvement.”</p>
<p>Using the system, the researchers have fabricated and tested 50,764 devices. It is powered by a recipe language model (RLM) that encodes information from around 60,000 perovskite solar cell-related publications released over recent decades, as well as data generated by the platform during device fabrication. These inputs are processed through a seven-layer AI architecture comprising recipe learning, recipe generation, dataset construction (RecipeQA), fine-tuning, reasoning, evaluation, and optimization.</p>
<p>Automated fabrication is initiated after the reasoning stage, where new experimental recipes are proposed. Eleven robotic boxes then carry out synthesis, device fabrication, and characterization tasks while simultaneously generating a digital twin of the process. The setup includes 101 functional units, more than 1,500 components, and over 4,300 controllable parameters.</p>
<p>Boxes 1–3 handle chemical storage, solid sampling, and liquid dispensing. Boxes 4–11 are used for spin-coating, antisolvent application, thermal annealing, laser processing, device transfer, vacuum exchange, and thin-film deposition. These latter units are also equipped with cameras, sensors, and actuators for in situ characterization, feeding data back into the model’s evolution loop.</p>
<p>Overall, the researchers describe the workflow of the robotic system as progressing through four stages: an initial phase of broad, largely unguided exploration of perovskite formulations; a second stage introducing additives and self-assembled monolayers (SAMs) to enhance crystallization and interfacial properties; a third stage incorporating surface passivation to reduce defects and improve performance; and a final stage combining SAM-based hole transport layers with targeted additive and passivation strategies.</p>
<p>“In stage I, without interface or additive engineering, the power conversion efficiency ranges from 0% to 17.4%. The incorporation of SAMs and additives in stage II narrows the distribution and increases efficiency to around 23%,” the results showed. “In stage III, interfacial post-treatment passivation leads to a further improvement, reaching 25.6%. The final configuration in stage IV delivers an efficiency of 27.0% (certified at 26.5%).”</p>
<p>The researchers stated that the main innovation of their study lies in combining three advantages within a single closed-loop AI–robotics system. They described it as enabling the controlled robotic fabrication of complete perovskite solar cell devices, alongside robotic characterization that transforms high-throughput experimental results into structured evidence related to underlying mechanisms. They further noted the inclusion of a domain-specific RLM that is continuously trained to improve recipe recommendations, mechanistic understanding, and subsequent robotic execution.</p>
<p>The system was described in “<a href="https://www.sciencedirect.com/science/article/pii/S2095809926001840?via%3Dihub" rel="noopener" target="_blank">Agentic Robotic Boxes for Perovskite Solar Cell Fabrication with Recipe Language Model</a>,” published in <em>Engineering. </em>Scientists from the <a href="https://www.pv-magazine.com/2025/08/06/vertical-bifacial-photovoltaic-balaustrade-for-buildings/" rel="noopener" target="_blank">Hong Kong Polytechnic University</a>, <a href="https://www.pv-magazine.com/2026/03/19/epfl-csem-achieve-world-record-efficiency-of-30-02-in-perovskite-silicon-triple-junction-solar-cell/" rel="noopener" target="_blank">Swiss Federal Institute of Technology in Lausanne,</a> China’s Wenzhou Institute of Technology, <a href="https://www.pv-magazine.com/2025/05/13/heat-pump-deployment-requires-massive-amounts-of-storage-uk-researcher-finds/" rel="noopener" target="_blank">University of Nottingham</a> Ningbo China, Shenzhen University of Advanced Technology, <a href="https://www.pv-magazine.com/2025/10/08/perovskite-quantum-dot-solar-cell-achieves-record-breaking-efficiency-of-18-3/" rel="noopener" target="_blank">North China Electric Power University</a>, <a href="https://www.pv-magazine.com/2025/08/12/new-research-shows-cast-mono-wafers-are-still-far-from-commercial-maturity/" rel="noopener" target="_blank">Zhejiang University</a>, <a href="https://www.pv-magazine.com/2026/02/18/global-warming-induced-degradation-could-raise-rooftop-solar-lcoe-by-up-to-20/" rel="noopener" target="_blank">Peking University</a>, and the <a href="https://www.pv-magazine.com/2025/12/17/the-impact-of-transparent-conductive-electrodes-on-perovskite-silicon-tandem-solar-cell-performance/" rel="noopener" target="_blank">University of Oxford</a> in the United Kingdom have contributed to the research.</p>