most citedUnbiased Atomistic Predictions of Crystal Dislocation Dynamics using Bayesian Force Fields

2 citations · 2 across the 2 of their papers we have counts for

collaborators

6 papers

cond-mat.mtrl-sci2024

Hydrogen Diffusion in Magnesium Using Machine Learning Potentials: a comparative study

Andrea Angeletti, Luca Leoni, Dario Massa +3

Understanding and accurately predicting hydrogen diffusion in materials is challenging due to the complex interactions between hydrogen defects and the crystal lattice. These inter…

cs.LG2024

In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphs

Grzegorz Kaszuba, Amirhossein D. Naghdi, Dario Massa +3

Large language models manifest the ability of few-shot adaptation to a sequence of provided examples. This behavior, known as in-context learning, allows for performing nontrivial…

cond-mat.mtrl-sci20242 cited

Unbiased Atomistic Predictions of Crystal Dislocation Dynamics using Bayesian Force Fields

Cameron J. Owen, Amirhossein D. Naghdi, Anders Johansson +3

Crystal dislocation dynamics, especially at high temperatures, represents a subject where experimental phenomenological input is commonly required, and parameter-free predictions,…

cond-mat.mtrl-sci2024

Transfer Learning in Materials Informatics: structure-property relationships through minimal but highly informative multimodal input

Dario Massa, Grzegorz Kaszuba, Stefanos Papanikolaou +1

In this work we propose simple, effective and computationally efficient transfer learning approaches for structure-property relation predictions in the context of materials, with h…

cond-mat.mtrl-sci2023

Neural Network Interatomic Potentials For Open Surface Nano-mechanics Applications

Amirhossein D. Naghdi, Franco Pellegrini, Emine Küçükbenli +4

Material characterization in nano-mechanical tests requires precise interatomic potentials for the computation of atomic energies and forces with near-quantum accuracy. For such pu…

cond-mat.mtrl-sci2023

Alloy Informatics through Ab Initio Charge Density Profiles: Case Study of Hydrogen Effects in Face-Centered Cubic Crystals

Dario Massa, Efthimios Kaxiras, Stefanos Papanikolaou

Materials design has traditionally evolved through trial-error approaches, mainly due to the non-local relationship between microstructures and properties such as strength and toug…