People

Miguel Caro

Senior Scientist

T105 Chemistry and Materials

Full researcher profile

https://research.aalto.fi/...

[email protected]

Research groups

DAS Group, Senior Scientist

Publications

Cluster-based multidimensional scaling embedding tool for data visualization

Patricia Hernandez Leon, Miguel A. Caro 2024 Physica Scripta

Experimental and Computational Study Toward Identifying Active Sites of Supported SnO_x Nanoparticles for Electrochemical CO₂ Reduction Using Machine-Learned Interatomic Potentials

Junjie Shi, Paulina Pršlja, Benjin Jin, Milla Suominen, Jani Sainio, Hua Jiang, Nana Han, Daria Robertson, Janez Košir, Miguel Caro, Tanja Kallio 2024 Small

Experiment-Driven Atomistic Materials Modeling : A Case Study Combining X-Ray Photoelectron Spectroscopy and Machine Learning Potentials to Infer the Structure of Oxygen-Rich Amorphous Carbon

Tigany Zarrouk, Rina Ibragimova, Albert P. Bartók, Miguel A. Caro 2024 Journal of the American Chemical Society

Machine learning based modeling of disordered elemental semiconductors: understanding the atomic structure of a-Si and a-C

Miguel A. Caro 2023 Semiconductor Science and Technology

Tensor-Reduced Atomic Density Representations

James P. Darby, Dávid P. Kovács, Ilyes Batatia, Miguel A. Caro, Gus L.W. Hart, Christoph Ortner, Gábor Csányi 2023 Physical Review Letters

Searching for iron nanoparticles with a general-purpose Gaussian approximation potential

Richard Jana, Miguel A. Caro 2023 Physical Review B

Gaussian approximation potentials: Theory, software implementation and application examples

Sascha Klawohn, James P. Darby, James R. Kermode, Gábor Csányi, Miguel A. Caro, Albert P. Bartók 2023 Journal of Chemical Physics

A general-purpose machine learning Pt interatomic potential for an accurate description of bulk, surfaces, and nanoparticles

Jan Kloppenburg, Livia B. Pártay, Hannes Jónsson, Miguel A. Caro 2023 The Journal of chemical physics

Exploring the configuration space of elemental carbon with empirical and machine learned interatomic potentials

George A. Marchant, Miguel A. Caro, Bora Karasulu, Livia B. Pártay 2023 npj Computational Materials

Quantum-corrected thickness-dependent thermal conductivity in amorphous silicon predicted by machine learning molecular dynamics simulations

Yanzhou Wang, Zheyong Fan, Ping Qian, Miguel A. Caro, Tapio Ala-Nissila 2023 Physical Review B