Zobrazeno 1 - 10
of 116
pro vyhledávání: '"Rossi, Kevin"'
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 energy storage devices more performant than the current Li-ion commercial o
Externí odkaz:
http://arxiv.org/abs/2112.11537
Publikováno v:
Phys. Rev. B 105, 165141, 2022
We show that, contrary to popular assumptions, predictions from machine learning potentials built upon high-dimensional atom-density representations almost exclusively occur in regions of the representation space which lie outside the convex hull def
Externí odkaz:
http://arxiv.org/abs/2112.10434
Autor:
Zeni, Claudio, Rossi, Kevin, Pavloudis, Theodore, Kioseoglou, Joseph, de Gironcoli, Stefano, Palmer, Richard, Baletto, Francesca
Publikováno v:
Nature Communications volume 12, Article number: 6056 (2021)
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, in conjunction with effective characterisation methods. In this work,
Externí odkaz:
http://arxiv.org/abs/2107.00330
Publikováno v:
J. Chem. Phys. 154, 224112 (2021)
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 framework in the prediction of formation energies and atomic forces in m
Externí odkaz:
http://arxiv.org/abs/2105.11231
Autor:
Imbalzano, Giulio, Zhuang, Yongbin, Kapil, Venkat, Rossi, Kevin, Engel, Edgar A., Grasselli, Federico, Ceriotti, Michele
Machine learning models have emerged as a very effective strategy to sidestep time-consuming electronic-structure calculations, enabling accurate simulations of greater size, time scale and complexity. Given the interpolative nature of these models,
Externí odkaz:
http://arxiv.org/abs/2011.08828
Autor:
Rossi, Kevin, Juraskova, Veronika, Wischert, Raphael, Garel, Laurent, Corminboeuf, Clemence, Ceriotti, Michele
Publikováno v:
J. Chem. Theory Comput. 16(8), 5139-5149 (2020)
We present a generally-applicable computational framework for the efficient and accurate characterization of molecular structural patterns and acid properties in explicit solvent using H$_2$O$_2$ and CH$_3$SO$_3$H in phenol as an example. In order to
Externí odkaz:
http://arxiv.org/abs/2006.12597
Publikováno v:
Advances in Physics: X, Volume 4, Number 1, 2019
Machine learning algorithms have recently emerged as a tool to generate force fields which display accuracies approaching the ones of the ab-initio calculations they are trained on, but are much faster to compute. The enhanced computational speed of
Externí odkaz:
http://arxiv.org/abs/1909.07080
Publikováno v:
In Carbon Trends June 2023 11
With a focus on platinum nanoparticles of different sizes (diameter of 1-9 nm) and shapes, we sequence their geometrical genome by recording the relative occurrence of all the non equivalent active site, classified according to the number of neighbou
Externí odkaz:
http://arxiv.org/abs/1805.09210
Autor:
Zeni, Claudio, Rossi, Kevin, Glielmo, Aldo, Fekete, Ádám, Gaston, Nicola, Baletto, Francesca, De Vita, Alessandro
Publikováno v:
The Journal of Chemical Physics 148, 241739 (2018)
We assess Gaussian process (GP) regression as a technique to model interatomic forces in metal nanoclusters by analysing the performance of 2-body, 3-body and many-body kernel functions on a set of 19-atom Ni cluster structures. We find that 2-body G
Externí odkaz:
http://arxiv.org/abs/1802.01417