Spectral neighbor representation for vector fields: Machine learning potentials including spin M Domina, M Cobelli, S Sanvito Physical Review B 105 (21), 214439, 2022 | 23 | 2022 |
Metal-semiconductor transition in the supercooled liquid phase of the and GeTe compounds M Cobelli, D Dragoni, S Caravati, M Bernasconi Physical Review Materials 5 (4), 045004, 2021 | 19 | 2021 |
A rule-free workflow for the automated generation of databases from scientific literature LPJ Gilligan, M Cobelli, V Taufour, S Sanvito npj Computational Materials 9 (1), 222, 2023 | 12 | 2023 |
Cluster expansion constructed over Jacobi-Legendre polynomials for accurate force fields M Domina, U Patil, M Cobelli, S Sanvito Physical Review B 108 (9), 094102, 2023 | 9 | 2023 |
First-Principles Study of Electromigration in the Metallic Liquid State of GeTe and Sb2Te3 Phase-Change Compounds M Cobelli, M Galante, S Gabardi, S Sanvito, M Bernasconi The Journal of Physical Chemistry C 124 (17), 9599-9603, 2020 | 7 | 2020 |
Machine-learning surrogate model for accelerating the search of stable ternary alloys M Minotakis, H Rossignol, M Cobelli, S Sanvito Physical Review Materials 7 (9), 093802, 2023 | 6 | 2023 |
Local inversion of the chemical environment representations M Cobelli, P Cahalane, S Sanvito Physical Review B 106 (3), 035402, 2022 | 6 | 2022 |
Machine-learning-assisted construction of ternary convex hull diagrams H Rossignol, M Minotakis, M Cobelli, S Sanvito Journal of Chemical Information and Modeling 64 (6), 1828-1840, 2024 | 5 | 2024 |
Applying machine learning to model radon using topsoil geochemistry M Banríon, M Cobelli, QG Crowley Applied Geochemistry 158, 105790, 2023 | 1 | 2023 |
Sampling Latent Material-Property Information From LLM-Derived Embedding Representations LPJ Gilligan, M Cobelli, HM Sayeed, TD Sparks, S Sanvito arXiv preprint arXiv:2409.11971, 2024 | | 2024 |
A rule-free workflow for the automated generation of databases from scientific literature (vol 10, 4, 2024) LPJ Gilligan, M Cobelli, V Taufour, S Sanvito NPJ COMPUTATIONAL MATERIALS 10 (1), 2024 | | 2024 |
Data-driven magnetic materials inverse design M Cobelli Trinity College Dublin, 2024 | | 2024 |
Author Correction: A rule-free workflow for the automated generation of databases from scientific literature LPJ Gilligan, M Cobelli, V Taufour, S Sanvito NPJ Computational Materials 10 (1), 4, 2024 | | 2024 |
Electronic properties of phase change compounds in the liquid state: effective charges for electromigration and semiconductor-metal transition from first principles M Cobelli, M Galante, D Dragoni, S Sanvito, M Bernasconi | | 2020 |
First-Principles Study of Electromigration in the Metallic Liquid State of GeTe and Sb₂Te₃ Phase-Change Compounds M Cobelli, M Galante, S Gabardi, S Sanvito, M Bernasconi | | 2020 |
First-Principles Study of Electromigration in the Metallic Liquid State of the GeTe and Sb2Te3 Phase Change Compounds Supporting Information M Cobelli, M Galante, S Gabardi, S Sanvito, M Bernasconi | | |