Larry Lüer

Larry Lüer is a Group Leader at the Chair of Materials for Electronics and Energy Technology at FAU, specializing in PV Applications and Machine Learning. His work integrates materials science with advanced computational methods to optimize photovoltaic technologies.

Research interests focus on high-throughput materials discovery, perovskite solar cells, defect-tolerant semiconductors, and machine learning-driven optimization. He leads projects like the self-driving AMADAP lab and develops digital twins for photovoltaic systems.

Recent work includes minimizing voltage losses in tandem solar cells, autonomous optimization of perovskite solar cells, and understanding degradation mechanisms under accelerated aging. Collaborations involve institutions like the Helmholtz Institute Erlangen-Nürnberg and KIT.

Lüer's contributions span over 50 peer-reviewed articles from 2020–2025, addressing topics like radiative/non-radiative recombination, ink engineering for quantum dot PVs, and aerial photoluminescence imaging for module diagnostics. His research emphasizes bridging lab-to-fab processes and advancing solar cell efficiency/stability.