Research Group Patrick Rinke
Patrick Rinke
Prof. Dr.
Principal Investigator
Patrick Rinke
is Professor for AI-based Material Science at TU Munich.
His chair is developing electronic structure and machine learning methods and applies them to pertinent problems in material science, surface science, physics, chemistry and the nano sciences.
Team members @MCML
PostDocs
Casper Larsen
Dr.
→ Group Patrick Rinke
AI-based Material Science
Matthias Stosiek
Dr.
→ Group Patrick Rinke
AI-based Material Science
Xiangzhou Zhu
Dr.
→ Group Patrick Rinke
AI-based Material Science
PhD Students
Nitik Bhatia
→ Group Patrick Rinke
AI-based Material Science
Prajwal Pisal
→ Group Patrick Rinke
AI-based Material Science
Recent News @MCML
Publications @MCML
2025
[12]
L. Lind • H. Sandström • P. Rinke
An interpretable molecular descriptor for machine learning predictions in atmospheric science.
Preprint (Oct. 2025). arXiv
An interpretable molecular descriptor for machine learning predictions in atmospheric science.
Preprint (Oct. 2025). arXiv
[11]
P. Pisal • O. Krejci • P. Rinke
Machine learning accelerated descriptor design for catalyst discovery in CO2 to methanol conversion.
PSI-K 2025 - 7th PSI-K Conference. Lausanne, Switzerland, Aug 25-28, 2025. DOI
Machine learning accelerated descriptor design for catalyst discovery in CO2 to methanol conversion.
PSI-K 2025 - 7th PSI-K Conference. Lausanne, Switzerland, Aug 25-28, 2025. DOI
[10]
N. Bhatia • O. Krejci • S. Botti • P. Rinke • M. A. L. Marques
MACE4IR: A foundation model for molecular infrared spectroscopy.
Preprint (Aug. 2025). arXiv
MACE4IR: A foundation model for molecular infrared spectroscopy.
Preprint (Aug. 2025). arXiv
[9]
J. Brean • F. Bortolussi • A. Rowell • D. C. S. Beddows • K. Weinhold • P. Mettke • M. Merkel • A. Kumar • S. Barua • S. Iyer • A. Karppinen • H. Sandström • P. Rinke • A. Wiedensohler • M. Pöhlker • M. Dal Maso • M. Rissanen • Z. Shi • R. M. Harrison
Traffic-Emitted Amines Promote New Particle Formation at Roadsides.
ACS ES&T Air 2.8. Jul. 2025. DOI
Traffic-Emitted Amines Promote New Particle Formation at Roadsides.
ACS ES&T Air 2.8. Jul. 2025. DOI
[8]
R. R. Valiev • R. T. Nasibullin • H. Sandström • P. Rinke • K. Puolamäki • T. Kurten
Predicting intersystem crossing rate constants of alkoxy-radical pairs with structure-based descriptors and machine learning.
Physical Chemistry Chemical Physics Advance Article. Jun. 2025. DOI
Predicting intersystem crossing rate constants of alkoxy-radical pairs with structure-based descriptors and machine learning.
Physical Chemistry Chemical Physics Advance Article. Jun. 2025. DOI
[7]
P. Pisal • O. Krejci • P. Rinke
Machine learning accelerated descriptor design for catalyst discovery in CO2 to methanol conversion.
npj Computational Materials 11.213. Jun. 2025. DOI
Machine learning accelerated descriptor design for catalyst discovery in CO2 to methanol conversion.
npj Computational Materials 11.213. Jun. 2025. DOI
[6]
N. Bhatia • P. Rinke • O. Krejci
Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction.
Preprint (Jun. 2025). arXiv
Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction.
Preprint (Jun. 2025). arXiv
[5]
J. Baumsteiger • L. Celiberti • P. Rinke • M. Todorović • C. Franchini
Exploring Noncollinear Magnetic Energy Landscapes with Bayesian Optimization.
Digital Discovery 4.6. May. 2025. DOI
Exploring Noncollinear Magnetic Energy Landscapes with Bayesian Optimization.
Digital Discovery 4.6. May. 2025. DOI
[4]
H. Homm • J. Laakso • P. Rinke
Efficient dataset generation for machine learning halide perovskite alloys.
Physical Review Materials 9.053802. May. 2025. DOI
Efficient dataset generation for machine learning halide perovskite alloys.
Physical Review Materials 9.053802. May. 2025. DOI
[3]
P. Henkel • J. Li • P. Rinke
Design Rules for Optimizing Quaternary Mixed-Metal Chalcohalides.
Preprint (May. 2025). arXiv
Design Rules for Optimizing Quaternary Mixed-Metal Chalcohalides.
Preprint (May. 2025). arXiv
[2]
F. Bortolussi • H. Sandström • F. Partovi • J. Mikkilä • P. Rinke • M. Rissanen
Technical note: Towards atmospheric compound identification in chemical ionization mass spectrometry with pesticide standards and machine learning.
Atmospheric Chemistry and Physics 25.1. Jan. 2025. DOI
Technical note: Towards atmospheric compound identification in chemical ionization mass spectrometry with pesticide standards and machine learning.
Atmospheric Chemistry and Physics 25.1. Jan. 2025. DOI
[1]
K. Ghosh • M. Todorović • A. Vehtari • P. Rinke
Active learning of molecular data for task-specific objectives.
The Journal of Chemical Physics 162.014103. Jan. 2025. DOI
Active learning of molecular data for task-specific objectives.
The Journal of Chemical Physics 162.014103. Jan. 2025. DOI
©all images: LMU | TUM