Matteo Cobelli

University of Milano-Bicocca — Italy

Materials Science · Physical Sciences

6h-index119citations20works2.22yr avg
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Research Topics

Machine Learning in Materials Science(12), Phase-change materials and chalcogenides(5), Computational Drug Discovery Methods(4), Chalcogenide Semiconductor Thin Films(4), X-ray Diffraction in Crystallography(4)

Publications20 total

<i>Ab initio</i> study of electromigration in liquid GeAsSe alloys for selector devices
The Journal of Chemical Physics·2025
Sampling latent material-property information from LLM-derived embedding representations
Materials Today Communications·2024Open Access
Sampling Latent Material-Property Information From LLM-Derived Embedding Representations
arXiv (Cornell University)·2024Open Access
Machine-Learning-Assisted Construction of Ternary Convex Hull Diagrams
Journal of Chemical Information and Modeling·2024· 10 citedOpen Access
Author Correction: A rule-free workflow for the automated generation of databases from scientific literature
npj Computational Materials·2024· 1 citedOpen Access
A rule-free workflow for the automated generation of databases from scientific literature
npj Computational Materials·2023· 27 citedOpen Access
Machine-learning surrogate model for accelerating the search of stable ternary alloys
Physical Review Materials·2023· 4 cited
Cluster expansion constructed over Jacobi-Legendre polynomials for accurate force fields
Physical review. B./Physical review. B·2023· 13 cited
Machine-Learning-Assisted Construction of Ternary Convex Hull Diagrams
arXiv (Cornell University)·2023Open Access
Machine-Learning Surrogate Model for Accelerating the Search of Stable Ternary Alloys
arXiv (Cornell University)·2023Open Access
A rule-free workflow for the automated generation of databases from scientific literature
arXiv (Cornell University)·2023· 2 citedOpen Access
Cluster expansion constructed over Jacobi-Legendre polynomials for accurate force fields
arXiv (Cornell University)·2022Open Access
Local inversion of the chemical environment representations
Physical review. B./Physical review. B·2022· 5 citedOpen Access
Spectral neighbor representation for vector fields: Machine learning potentials including spin
Physical review. B./Physical review. B·2022· 29 citedOpen Access
A spectral-neighbour representation for vector fields: machine-learning potentials including spin
arXiv (Cornell University)·2022Open Access
Inversion of the chemical environment representations
arXiv (Cornell University)·2022Open Access
Metal-semiconductor transition in the supercooled liquid phase of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Ge</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi>Sb</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi>Te</mml:mi><mml:mn>5</mml:mn></mml:msub></mml:mrow></mml:math> and GeTe compounds
Physical Review Materials·2021· 19 citedOpen Access
First-Principles Study of Electromigration in the Metallic Liquid State of GeTe and Sb<sub>2</sub>Te<sub>3</sub> Phase-Change Compounds
The Journal of Physical Chemistry C·2020· 9 citedOpen Access
Electronic properties of phase change compounds in the liquid state: effective charges for electromigration and semiconductor-metal transition from first principles
BOA (University of Milano-Bicocca)·2020
First-Principles Study of Electromigration in the Metallic Liquid State of GeTe and Sb₂Te₃ Phase-Change Compounds
The Journal of Physical Chemistry·2020

Frequent Co-authors

Stefano Sanvito(18), Luke P. J. Gilligan(5), Marco Bernasconi(5), Michelangelo Domina(4), Hugo Rossignol(4), Valentin Taufour(3), Mario Galante(3), Daniele Dragoni(2), Urvesh Patil(2), Michail Minotakis(2), Silvia Gabardi(2), Paddy Cahalane(2), Hasan M. Sayeed(2), Taylor D. Sparks(2), S. Caravati(1), Dario Baratella(1), Paolo Fantini(1), Michail Minotakis(1), Michael Minotakis(1)