Patrick Rinke

most citedEfficient dataset generation for machine learning perovskite alloys

6 citations · 6 across the 3 of their papers we have counts for

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physics.chem-ph2025

An interpretable molecular descriptor for machine learning predictions in atmospheric science

Linus Lind, Hilda Sandström, Patrick Rinke

The study of aerosol formation and chemistry using machine learning is limited by the lack of molecular descriptors suited to atmospheric compounds. Interpretable models are partic…

physics.chem-ph2025

Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction

Nitik Bhatia, Patrick Rinke, Ondrej Krejci

Infrared (IR) spectroscopy is a pivotal analytical tool as it provides real-time molecular insight into material structures and enables the observation of reaction intermediates in…

physics.chem-ph2024

Machine Learning Accelerated Descriptor Design for Catalyst Discovery in CO $_{2}$ to Methanol Conversion

Prajwal Pisal, Ondrej Krejci, Patrick Rinke

Transforming CO $_{2}$ into methanol represents a crucial step towards closing the carbon cycle, with thermoreduction technology nearing industrial application. However, obtaining hig…

An interpretable molecular descriptor for machine learning predictions in atmospheric science

Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction

Machine Learning Accelerated Descriptor Design for Catalyst Discovery in CO2​ to Methanol Conversion

Machine Learning Accelerated Descriptor Design for Catalyst Discovery in CO $_{2}$ to Methanol Conversion