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Michele Ceriotti

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Publications associées (162)

An In-Situ Neutron Diffraction and DFT Study of Hydrogen Adsorption in a Sodalite-Type Metal-Organic Framework, Cu-BTTri

Safak Bulut, Michele Ceriotti, Mehrdad Asgari, Wendy Lee Queen, Olga Trukhina, Pascal Alexander Schouwink, Ilia Kochetygov, Shuliang Yang, Rocio Semino Barbaresi

Herein we present a detailed study of the hydrogen adsorption properties of Cu‐BTTri, a robust crystalline metal–organic framework containing open metal‐coordination sites. Diffraction techniques, carried out on the activated framework, reveal a structure ...

2019

Quantum mechanical static dipole polarizabilities in the QM7b and AlphaML showcase databases

Michele Ceriotti, David Mark Wilkins, Andrea Grisafi, Yang Yang

While density functional theory (DFT) is often an accurate and efficient methodology for evaluating molecular properties such as energies and multipole moments, this approach often yields larger errors for response properties such as the dipole polarizabil ...

2019

Transferable Machine-Learning Model of the Electron Density

Anne-Clémence Corminboeuf, Alberto Fabrizio, Michele Ceriotti, David Mark Wilkins, Andrea Grisafi, Benjamin André René Meyer

The electronic charge density plays a central role in determining the behavior of matter at the atomic scale, but its computational evaluation requires demanding electronic-structure calculations. We introduce an atom-centered, symmetry-adapted framework t ...

2019

Nuclear quantum effects enter the mainstream

Michele Ceriotti

Atomistic simulations of chemical, biological and materials systems have become increasingly precise and predictive owing to the development of accurate and efficient techniques that describe the quantum mechanical behaviour of electrons. Nevertheless, the ...

2018

Data-driven many-body representations with chemical accuracy for molecular simulations from the gas to the condensed phase

Michele Ceriotti, Giulio Imbalzano

AMER CHEMICAL SOC2018

Applications of machine learning for studying local solvation environments

Michele Ceriotti, Sandip De

ACS2018

Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions

Michele Ceriotti, Giulio Imbalzano

The accurate representation of multidimensional potential energy surfaces is a necessary requirement for realistic computer simulations of molecular systems. The continued increase in computer power accompanied by advances in correlated electronic structur ...

2018

Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems

Michele Ceriotti, David Mark Wilkins, Andrea Grisafi

2018

Machine learning for the structure–energy–property landscapes of molecular crystals

Félix Benedito Clément Musil, Michele Ceriotti, Sandip De

2018

Recognizing Local and Global Structural Motifs at the Atomic Scale

Michele Ceriotti, Piero Gasparotto, Robert Horst Meissner

2018

Computing the absolute Gibbs free energy in atomistic simulations: Applications to defects in solids

Michele Ceriotti, Bingqing Cheng

2018

Analyzing Fluxional Molecules Using DORI

Laurent Alexis Clément Vannay, Riccardo Petraglia, Michele Ceriotti, Giuseppe Sforazzini, Benjamin André René Meyer

2018

Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials

Michele Ceriotti, Daniele Giofré, Giulio Imbalzano, Andrea Anelli, Sinja Klees

2018

Fast-forward Langevin dynamics with momentum flips

Michele Ceriotti, David Mark Wilkins, Mahdi Hijazi

2018

Anisotropy of the Proton Momentum Distribution in Water

Michele Ceriotti, Venkat Kapil, Alice Cuzzocrea

2018

Mapping uncharted territory in ice from zeolite networks to ice structures

Michele Ceriotti, Andrea Anelli, Edgar Albert Engel

Nature Research2018

Communication: Computing the Tolman length for solid-liquid interfaces

Michele Ceriotti, Bingqing Cheng

2018

Chemical shifts in molecular solids by machine learning

Félix Benedito Clément Musil, Michele Ceriotti, Maxime Lagier, David Lyndon Emsley, Sandip De, Albert Hofstetter, Federico Maria Paruzzo

Due to their strong dependence on local atonic environments, NMR chemical shifts are among the most powerful tools for strucutre elucidation of powdered solids or amorphous materials. Unfortunately, using them for structure determination depends on the abi ...

Nature Research2018

Large-Scale Computational Screening of Molecular Organic Semiconductors Using Crystal Structure Prediction

Michele Ceriotti, Sandip De

Predictive computational methods have the potential to significantly accelerate the discovery of new materials with targeted properties by guiding the choice of candidate materials for synthesis. Recently, a planar pyrrole-based azaphenacene molecule (pyri ...

2018

Nuclear Quantum Effects in Sodium Hydroxide Solutions from Neural Network Molecular Dynamics Simulations

Michele Ceriotti

Nuclear quantum effects (NQEs) cause the nuclei of light elements like hydrogen to delocalize, affecting numerous properties of water and aqueous solutions, such as hydrogen-bonding and proton transfer barriers. Here, we address the prototypical case of aq ...

2018

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