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Michele Ceriotti

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Publications associées (162)

Inexpensive modeling of quantum dynamics using path integral generalized Langevin equation thermostats

Michele Ceriotti, Jinggang Lan, David Mark Wilkins, Venkat Kapil

The properties of molecules and materials containing light nuclei are affected by their quantum mechanical nature. Accurate modeling of these quantum nuclear effects requires computationally demanding path integral techniques. Considerable success has been ...

2020

Classical nucleation theory predicts the shape of the nucleus in homogeneous solidification

Michele Ceriotti, Bingqing Cheng, Gareth Aneurin Tribello

Macroscopic models of nucleation provide powerful tools for understanding activated phase transition processes. These models do not provide atomistic insights and can thus sometimes lack material-specific descriptions. Here, we provide a comprehensive fram ...

AMER INST PHYSICS2020

Recursive evaluation and iterative contraction of N-body equivariant features

Michele Ceriotti, Jigyasa Nigam, Sergey Pozdnyakov

Mapping an atomistic configuration to a symmetrized N-point correlation of a field associated with the atomic positions (e.g., an atomic density) has emerged as an elegant and effective solution to represent structures as the input of machine-learning algo ...

2020

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

Michele Ceriotti, David Mark Wilkins, Max David Veit, Yang Yang

The molecular dipole moment (mu) is a central quantity in chemistry. It is essential in predicting infrared and sum-frequency generation spectra as well as induction and long-range electrostatic interactions. Furthermore, it can be extracted directly-via t ...

AMER INST PHYSICS2020

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

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

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

Accurate Description of Nuclear Quantum Effects with High-Order Perturbed Path Integrals (HOPPI)

Michele Ceriotti, Venkat Kapil

Imaginary time path-integral (PI) simulations that account for nuclear quantum effects (NQE) beyond the harmonic approximation are increasingly employed together with modern electronic-structure calculations. Existing PI methods are applicable to molecules ...

AMER CHEMICAL SOC2020

3D Ordering at the Liquid-Solid Polar Interface of Nanowires

Cécile Hébert, Duncan Thomas Lindsay Alexander, Anna Fontcuberta i Morral, Gözde Tütüncüoglu, Nicolas Tappy, Martin George Friedl, Michele Ceriotti, Luca Francaviglia, Giulio Imbalzano, Mahdi Zamani, Lea Ghisalberti, Sara Marti Sanchez

The nature of the liquid-solid interface determines the characteristics of a variety of physical phenomena, including catalysis, electrochemistry, lubrication, and crystal growth. Most of the established models for crystal growth are based on macroscopic t ...

Wiley2020

Quantum kinetic energy and isotope fractionation in aqueous ionic solutions

Michele Ceriotti, Lu Wang

At room temperature, the quantum contribution to the kinetic energy of a water molecule exceeds the classical contribution by an order of magnitude. The quantum kinetic energy (QKE) of a water molecule is modulated by its local chemical environment and lea ...

ROYAL SOC CHEMISTRY2020

Chemiscope: interactive structure-property explorer for materials and molecules

Michele Ceriotti, Guillaume André Jean Fraux

The number of materials or molecules that can be created by combining different chemical elements in various proportions and spatial arrangements is enormous. Computational chemistry can be used to generate databases containing billions of potential struct ...

2020

Iterative Unbiasing of Quasi-Equilibrium Sampling

Michele Ceriotti, Bingqing Cheng, Gareth Aneurin Tribello, Federico Giberti

Atomistic modeling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an appropriately chosen s ...

AMER CHEMICAL SOC2020

Identifying and Tracking Defects in Dynamic Supramolecular Polymers

Michele Ceriotti, Piero Gasparotto

A central paradigm of self-assembly is to create ordered structures starting from molecular monomers that spontaneously recognize and interact with each other via noncovalent interactions. In recent years, great efforts have been directed toward perfecting ...

AMER CHEMICAL SOC2020

Structure-property maps with Kernel principal covariates regression

Michele Ceriotti, Benjamin Aaron Helfrecht, Guillaume André Jean Fraux

Data analyses based on linear methods constitute the simplest, most robust, and transparent approaches to the automatic processing of large amounts of data for building supervised or unsupervised machine learning models. Principal covariates regression (PC ...

2020

Understanding How Ligand Functionalization Influences CO2 and N-2 Adsorption in a Sodalite Metal-Organic Framework

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

In this work, a detailed study is conducted to understand how ligand substitution influences the CO, and N-2 adsorption properties of two highly crystalline sodalite metal-organic frameworks (MOFs) known as Cu-BTT (BTT-3 = 1,3,5-benzenetristetrazolate) and ...

AMER CHEMICAL SOC2020

Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems

Fabio Pietrucci, Michele Ceriotti

Machine learning encompasses tools and algorithms that are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as well, where machine learning offers promises of extracting valuable information from t ...

AMER CHEMICAL SOC2020

Evidence for supercritical behaviour of high-pressure liquid hydrogen

Michele Ceriotti, Bingqing Cheng

2020

Machine-Learning of Atomic-Scale Properties Based on Physical Principles

Michele Ceriotti, Michael John Willatt

We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the linear algebra framework can be used to both predict and train from linear fun ...

Springer International Publishing2020

Incompleteness of Atomic Structure Representations

Michele Ceriotti, Michael John Willatt, Sergey Pozdnyakov

Many-body descriptors are widely used to represent atomic environments in the construction of machine-learned interatomic potentials and more broadly for fitting, classification, and embedding tasks on atomic structures. There is a widespread belief in the ...

AMER PHYSICAL SOC2020

Learning the electronic density of states in condensed matter

Michele Ceriotti, Andrea Anelli, Chiheb Ben Mahmoud

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

AMER PHYSICAL SOC2020

Gas-sieving zeolitic membranes fabricated by condensation of precursor nanosheets

Yu Han, Michele Ceriotti, Kumar Varoon Agrawal, Claudia Esther Avalos, Pascal Alexander Schouwink, Mostapha Dakhchoune, Luis Francisco Villalobos Vazquez de la Parra, Rocio Semino Barbaresi

The synthesis of molecular-sieving zeolitic membranes by the assembly of building blocks, avoiding the hydrothermal treatment, is highly desired to improve reproducibility and scalability. Here we report exfoliation of the sodalite precursor RUB-15 into cr ...

2020

Atomic Motif Recognition in (Bio)Polymers: Benchmarks From the Protein Data Bank

Michele Ceriotti, Piero Gasparotto, Benjamin Aaron Helfrecht, Federico Giberti

Rationalizing the structure and structure–property relations for complex materials such as polymers or biomolecules relies heavily on the identification of local atomic motifs, e.g., hydrogen bonds and secondary structure patterns, that are seen as buildin ...

2019

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