Miguel A. Caro

Miguel A. Caro

Aalto-yliopisto

H-index: 29

Europe-Finland

About Miguel A. Caro

Miguel A. Caro, With an exceptional h-index of 29 and a recent h-index of 25 (since 2020), a distinguished researcher at Aalto-yliopisto, specializes in the field of Interatomic potentials, Atomistic materials modeling, Machine learning, Enhanced atomistic simulation.

His recent articles reflect a diverse array of research interests and contributions to the field:

Experiment-driven atomistic materials modeling: A case study combining XPS and ML potentials to infer the structure of oxygen-rich amorphous carbon

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

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

Gaussian approximation potentials: Theory, software implementation and application examples

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

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

Tensor-reduced atomic density representations

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

Miguel A. Caro Information

University

Position

Academy of Finland Research Fellow

Citations(all)

3264

Citations(since 2020)

2552

Cited By

1487

hIndex(all)

29

hIndex(since 2020)

25

i10Index(all)

50

i10Index(since 2020)

42

Email

University Profile Page

Google Scholar

Miguel A. Caro Skills & Research Interests

Interatomic potentials

Atomistic materials modeling

Machine learning

Enhanced atomistic simulation

Top articles of Miguel A. Caro

Title

Journal

Author(s)

Publication Date

Experiment-driven atomistic materials modeling: A case study combining XPS and ML potentials to infer the structure of oxygen-rich amorphous carbon

arXiv preprint arXiv:2402.03219

Tigany Zarrouk

Rina Ibragimova

Albert P Bartók

Miguel A Caro

2024/2/5

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

The Journal of chemical physics

Jan Kloppenburg

Livia B Pártay

Hannes Jónsson

Miguel A Caro

2023/4/7

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

Miguel A Caro

2023/3/6

Gaussian approximation potentials: Theory, software implementation and application examples

The Journal of Chemical Physics

Sascha Klawohn

James P Darby

James R Kermode

Gábor Csányi

Miguel A Caro

...

2023/11/7

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

Physical Review B

Yanzhou Wang

Zheyong Fan

Ping Qian

Miguel A Caro

Tapio Ala-Nissila

2023/2/6

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

npj Computational Materials

George A Marchant

Miguel A Caro

Bora Karasulu

Livia B Pártay

2023/7/27

Tensor-reduced atomic density representations

Physical Review Letters

James P Darby

Dávid P Kovács

Ilyes Batatia

Miguel A Caro

Gus LW Hart

...

2023/7/13

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

Physical Review B

Richard Jana

Miguel A Caro

2023/6/16

Structure and Pore Size Distribution in Nanoporous Carbon

Chemistry of Materials

Yanzhou Wang

Zheyong Fan

Ping Qian

Tapio Ala-Nissila

Miguel A Caro

2022/1/4

Reassignment of magic numbers for icosahedral Au clusters: 310, 564, 928 and 1426

Nanoscale

Jan Kloppenburg

Andreas Pedersen

Kari Laasonen

Miguel A Caro

Hannes Jónsson

2022

Cluster-based multidimensional scaling embedding tool for data visualization

Physica Scripta

Patricia Hernández-León

Miguel Caro

2022/9/14

Accurate Computational Prediction of Core-Electron Binding Energies in Carbon-Based Materials: A Machine-Learning Model Combining Density-Functional Theory and GW

Chemistry of Materials

Dorothea Golze

Markus Hirvensalo

Patricia Hernández-León

Anja Aarva

Jarkko Etula

...

2022/7/13

Addressing dynamics at catalytic heterogeneous interfaces with DFT-MD: Anomalous temperature distributions from commonly used thermostats

J. Phys. Chem. Lett.

Ville Korpelin

Toni Kiljunen

Marko M Melander

Miguel A Caro

Henrik H Kristoffersen

...

2022/3/17

Machine learning force fields based on local parametrization of dispersion interactions: Application to the phase diagram of C

Physical Review B

Heikki Muhli

Xi Chen

Albert P Bartók

Patricia Hernández-León

Gábor Csányi

...

2021/8/6

Stability and residual stresses of sputtered wurtzite AlScN thin films

Physical Review Materials

Elmeri Österlund

Glenn Ross

Miguel A Caro

Mervi Paulasto-Kröckel

Andreas Hollmann

...

2021/3/2

What Determines the Electrochemical Properties of Nitrogenated Amorphous Carbon Thin Films?

Chemistry of Materials

Jarkko Etula

Niklas Wester

Touko Liljestrom

Sami Sainio

Tommi Palomaki

...

2021/8/23

Connection between the physicochemical characteristics of amorphous carbon thin films and their electrochemical properties

Journal of Physics: Condensed Matter

Elli Leppänen

Anja Aarva

Sami Sainio

Miguel A Caro

Tomi Laurila

2021/8/18

X-ray Spectroscopy Fingerprints of Pristine and Functionalized Graphene

The Journal of Physical Chemistry C

Anja Aarva

Sami Sainio

Volker L Deringer

Miguel A Caro

Tomi Laurila

2021/8/16

Multiband model and fitting scheme for ab initio based electronic structure parameters for wurtzite GaAs

Physical Review B

Oliver Marquardt

Miguel A Caro

Thomas Koprucki

Peter Mathé

Morten Willatzen

2020/6/22

Undoped Tetrahedral Amorphous Carbon (ta-C) Thin Films for Biosensing

Anja Aarva

Miguel Caro

Tomi Laurila

2020/4/8

See List of Professors in Miguel A. Caro University(Aalto-yliopisto)

Co-Authors

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