Papers
9
Total Citations
723
H-Index
7
About
Tobias Stubhan is a pioneering researcher at the intersection of photovoltaics, high-throughput experimentation, and machine learning, with a particular focus on perovskite solar cells and organic photovoltaics (OPVs). His work has fundamentally advanced how researchers explore and optimize complex material systems, replacing slow, manual experimentation with intelligent, robot-assisted platforms capable of screening vast compositional and processing parameter spaces. Stubhan's most influential contributions include the discovery of temperature-induced stability reversals in perovskite materials — a counterintuitive finding with major implications for real-world device reliability — and the development of robotic platforms that couple high-throughput fabrication with machine learning to accelerate materials discovery. His 2021 studies on perovskite stability and OPV optimization (174 and 168 citations, respectively) demonstrate both the breadth and depth of his impact. His earlier work exploring wide bandgap perovskite stability (120 citations) helped establish robotic screening as a credible methodology in the field. Through tools like the SPINBOT platform and self-driving laboratory concepts, Stubhan has helped define a new paradigm for solar cell research — one where autonomous experimentation dramatically shortens the path from material synthesis to high-performance devices. His body of work is essential reading for anyone advancing next-generation photovoltaics.
Research Focus
Key Achievements
Top Papers
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