3 papers
physics.comp-ph2026
Analysis of degradation in perovskite solar cells through physics-based machine learning
Kjeld O. Jensen, Gemma Giliberti, Aldo Di Carlo +5
Degradation in lead halide perovskite solar cells is analysed by inverse modelling of published measurements of characteristics of a single solar cell at ages 0, 90, 280, 480 minut…
cond-mat.mtrl-sci2026
Quantifying Perovskite Solar Cell Degradation via Machine Learning from Spatially Resolved Multimodal Luminescence Time Series
Giulio Barletta, Simon Ternes, Saif Ali +7
Perovskite solar cells achieve remarkable power conversion efficiencies, yet operational stability remains a major barrier to large-scale deployment. Reliable and rapid assessment…
cs.LG2026
A green solvent screening tool for emerging materials via uncertainty aware, transformer enhanced transfer learning
Ioannis Kouroudis, Simon Ternes, Zhaosu Gu +5
Accurate prediction of solubility remains a central challenge across materials science and sustainable chemistry. In particular due to emerging technologies like organic and hybrid…