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cond-mat.mtrl-sci2026
Charting the thermodynamic stability of hybrid perovskite alloys with machine learning
Jarno Laakso, Armi Tiihonen, Patrick Rinke
Alloy-based perovskite semiconductor materials offer tunable properties and improved stability, but their complexity has impeded accurate modeling, hindering development of solar c…
cond-mat.mtrl-sci2026
Selectivity- and Activity-Aware Catalyst Descriptors for CO Hydrogenation on Alloy Nanocatalysts using Machine-Learned Force Fields
Prajwal Pisal, Ondřej Krejčí, Patrick Rinke
Adsorption energy distributions (AEDs) have emerged as a powerful and increasingly adopted descriptor for catalytic performance in high-entropy alloys and, more recently, in conven…
cond-mat.mtrl-sci2026
Role of photonic interference in exciton-mediated magneto-optic responses
Güven Budak, Christian Riedel, Akashdeep Kamra +4
Coupled optical and magnetic excitations can give rise to remarkably strong magneto-optic responses. This is particularly evident in van der Waals magnets, such as the antiferromag…