Kevin Rossi

Cette personne n’est plus à l’EPFL

Publications associées (23)

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Well-Defined Copper-Based Nanocatalysts for Selective Electrochemical Reduction of CO2 to Ethylene and Ethanol

Raffaella Buonsanti, Ludovic Emile Frédy Zaza, Kevin Rossi

The electrochemical CO2 reduction reaction (CO2RR) holds the promise to revolutionize the chemical industry by producing value-added chemicals and fuels from CO2 and water while storing renewable energy. However, catalyst design still remains one of the ma ...

2022

Data-driven simulation and characterisation of gold nanoparticle melting

Kevin Rossi

Efficient theoretical methods for the structural analysis of nanoparticles are very much needed. Here the authors demonstrate the use of machine-learning force fields and of a data-driven approach to study the thermodynamical stability and elucidate the me ...

Nature Portfolio2021

A universal signature in the melting of metallic nanoparticles

Kevin Rossi

Predicting when phase changes occur in nanoparticles is fundamental for designing the next generation of devices suitable for catalysis, biomedicine, optics, chemical sensing and electronic circuits. The estimate of the temperature at which metallic nanopa ...

ROYAL SOC CHEMISTRY2021

Born to be different: the formation process of Cu nanoparticles tunes the size trend of the activity for CO2 to CH4 conversion

Kevin Rossi, Elena Gazzarrini

We investigate the impact of the formation process of Cu nanoparticles on the distribution of adsorption sites and hence on their activity. Using molecular dynamics, we model formation pathways characteristic of physical synthesis routes as the annealing o ...

ROYAL SOC CHEMISTRY2021

Compact atomic descriptors enable accurate predictions via linear models

Kevin Rossi

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 molecul ...

AIP Publishing2021

Elucidating the structure-dependent selectivity of CuZn towards methane and ethanol in CO2 electroreduction using tailored Cu/ZnO precatalysts

Raffaella Buonsanti, Seyedehbehnaz Varandili, Kevin Rossi, Dragos-Constantin Stoian, Jan Vávra, James Richard Pankhurst, Yannick Thomas Guntern

Understanding the catalyst compositional and structural features that control selectivity is of uttermost importance to target desired products in chemical reactions. In this joint experimental-computational work, we leverage tailored Cu/ZnO precatalysts a ...

2021

Uncertainty estimation for molecular dynamics and sampling

Michele Ceriotti, Venkat Kapil, Yongbin Zhuang, Kevin Rossi, Edgar Albert Engel, Federico Grasselli, Giulio Imbalzano

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, the r ...

2021

Structural Screening and Design of Platinum Nanosamples for Oxygen Reduction

Kevin Rossi

Nanocatalyst-by-design promises to empower the next generation of electrodes for energy devices. However, current numerical methods consider individual and often geometrical closed-shell nanoparticles, neglecting how the coexistence of several and structur ...

AMER CHEMICAL SOC2020

Simulating Solvation and Acidity in Complex Mixtures with First-Principles Accuracy: The Case of CH3SO3H and H2O2 in Phenol

Michele Ceriotti, Anne-Clémence Corminboeuf, Kevin Rossi, Veronika Juraskova

We present a generally applicable computational framework for the efficient and accurate characterization of molecular structural patterns and acid properties in an explicit solvent using H2O2 and CH3SO3H in phenol as an example. To address the challenges ...

AMER CHEMICAL SOC2020

On machine learning force fields for metallic nanoparticles

Kevin Rossi

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 machin ...

2019

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