activity
20162022
most citedAn Accurate and Transferable Machine Learning Potential for Carbon

278 citations · 358 across the 4 of their papers we have counts for

collaborators

6 papers

cond-mat.soft202215 cited

How do interfaces alter the dynamics of supercooled water?

Piero Gasparotto, Martin Fitzner, Stephen J. Cox +2

The structure of liquid water in the proximity of an interface can deviate significantly from that of bulk water, with surface-induced structural perturbations typically converging…

cond-mat.mtrl-sci2020

Mapping the Structure of Oxygen-Doped Wurtzite Aluminum Nitride Coatings From Ab Initio Random Structure Search and Experiments

Piero Gasparotto, Maria Fischer, Daniele Scopece +8

Machine learning is changing how we design and interpret experiments in materials science. In this work, we show how unsupervised learning, combined with ab initio modeling, improv…

physics.comp-ph2020278 cited

An Accurate and Transferable Machine Learning Potential for Carbon

Patrick Rowe, Volker L Deringer, Piero Gasparotto +2

We present an accurate machine learning (ML) model for atomistic simulations of carbon, constructed using the Gaussian approximation potential (GAP) methodology. The potential, nam…

physics.comp-ph2019

Using data-reduction techniques to analyse biomolecular trajectories

Gareth A. Tribello, Piero Gasparotto

This chapter discusses the way in which dimensionality reduction algorithms such as diffusion maps and sketch-map can be used to analyze molecular dynamics trajectories. The first…

physics.chem-ph201865 cited

Recognizing Local and Global Structural Motifs at the Atomic Scale

Piero Gasparotto, Robert Horst Meißner, Michele Ceriotti

Most of the current understanding of structure-property relations at the molecular and the supramolecular scales can be formulated in terms of the stability of and the interactions…

physics.chem-ph2016

Probing defects and correlations in the hydrogen-bond network of ab initio water

Piero Gasparotto, Ali A. Hassanali, Michele Ceriotti

The hydrogen-bond network of water is characterized by the presence of coordination defects relative to the ideal tetrahedral network of ice, whose fluctuations determine the stati…