Guillaume Lambard
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Generative AI-Driven Accelerated Discovery of Passivation Molecules for Perovskite Solar Cells
1 Introduction Halide perovskite solar cells (PSCs) have emerged as one of the most promising next-generation photovoltaic technologies owing to their exceptional optoelectronic properties, facile solution processability, and tunable bandgaps. Since their initial demonstration with a modest power conversion efficiency (PCE) of 3.8%, the efficiency of single-junction PSCs has rapidly advanced to 27.0%, while perovskite-based tandem devices are now approaching 35% [1, 2].
Data-driven automated robotic experiments accelerate discovery of multi-component electrolyte for rechargeable Li-O2 batteries
Highlights • Automated electrochemical experiments for performance evaluation of electrolytes • Efficient searching by machine-learning methodologies using Bayesian optimization • Multi-component electrolyte additives for lithium–oxygen batteries are discovered • Stable solid electrolyte interface formed via synergy among the various components Summary Rechargeable aprotic lithium–oxygen (Li–O2) batteries are promising candidates for next-generation energy-storage devices.
Mesoporous trimetallic PtPdAu alloy films toward enhanced electrocatalytic activity in methanol oxidation: unexpected chemical compositions discovered by Bayesian optimization
Mesoporous trimetallic PtPdAu alloy films toward enhanced electrocatalytic activity in methanol oxidation: unexpected chemical compositions discovered by Bayesian optimization† Asep Sugih Nugraha,a Guillaume Lambard, b Jongbeom Na, a Md Shahriar A.
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