101 citations · 404 across the 12 of their papers we have counts for
14 papers
'pySNOW': a Python Suite for the NanO-World
Sofia Zinzani, Gilberto Nardi, Giacomo Becatti +4
In computational materials science, numerical simulations are indispensable tools for revealing atomic-scale processes. For building blocks of the nanoworld, such as nanoparticles…
Bridging Structure and Activity in Nanocatalysts via Machine Learning and Global Structure Representations
Sofia Zinzani, Francesca Baletto, Kevin Rossi
Establishing a mapping between nanocatalysts structure and their catalytic properties is essential for efficient design. To this end, we demonstrate the accuracy of a general machi…
Accelerating the theoretical study of Li-polysulphide adsorption on single-atom catalysts via machine learning approaches
Eleftherios I. Andritsos, Kevin Rossi
Unlocking the design of Li-S batteries where no shuttle effects appears, and thus their energy storage capacity does not diminish over time, would enable the manufacturing of energ…
Exploring the robust extrapolation of high-dimensional machine learning potentials
Claudio Zeni, Andrea Anelli, Aldo Glielmo +1
We show that, contrary to popular assumptions, predictions from machine learning potentials built upon high-dimensional atom-density representations almost exclusively occur in reg…
Data-driven simulation and characterisation of gold nanoparticle melting
Claudio Zeni, Kevin Rossi, Theodore Pavloudis +4
The simulation and analysis of the thermal stability of nanoparticles, a stepping stone towards their application in technological devices, require fast and accurate force fields,…
Compact atomic descriptors enable accurate predictions via linear models
Claudio Zeni, Kevin Rossi, Aldo Glielmo +1
We probe the accuracy of linear ridge regression employing a three-body local density representation derived from the atomic cluster expansion. We benchmark the accuracy of this fr…