Publications

Wandering principal optical axes in van der Waals triclinic materials

G. A. Ermolaev; K. V. Voronin; A. N. Toksumakov; D. V. Grudinin; I. M. Fradkin et al. 

Thermal transport of glasses via machine learning driven simulations

P. Pegolo; F. Grasselli 

Surface segregation in high-entropy alloys from alchemical machine learning

A. Mazitov; M. A. Springer; N. Lopanitsyna; G. Fraux; S. De et al. 

Efficient and insightful descriptors for representing molecular and material space

Self-interaction and transport of solvated electrons in molten salts

P. Pegolo; S. Baroni; F. Grasselli 

Multiscale Modeling of Aqueous Electric Double Layers

M. Becker; P. R. Loche; M. Rezaei; A. Wolde-Kidan; Y. Uematsu et al. 

Accuracy Assessment of Atomistic Neural Network Potentials: The Impact of Cutoff Radius and Message Passing

J. Xia; Y. Zhang; B. Jiang 

Accelerated chemical science with AI

S. Back; A. Aspuru-Guzik; M. Ceriotti; G. Gryn’ova; B. Grzybowski et al. 

Natural aging and vacancy trapping in Al-6xxx

A. C. P. Jain; M. Ceriotti; W. A. Curtin 

Physics-Inspired Equivariant Descriptors of Nonbonded Interactions

K. K. Huguenin-Dumittan; P. R. Loche; N. Haoran; M. Ceriotti 

Revealing the Formation Dynamics of Janus Polymer Particles: Insights from Experiments and Molecular Dynamics

M. Nedyalkova; G. Russo; P. R. Loche; M. Lattuada 

Robustness of Local Predictions in Atomistic Machine Learning Models

S. Chong; F. Grasselli; C. Ben Mahmoud; J. D. Morrow; V. L. Deringer et al. 

Divide-and-conquer potentials enable scalable and accurate predictions of forces and energies in atomistic systems

C. Zeni; A. Anelli; A. Glielmo; S. de Gironcoli; K. Rossi 

Universal machine learning for the response of atomistic systems to external fields

Y. Zhang; B. Jiang 

van der Waals Materials for Overcoming Fundamental Limitations in Photonic Integrated Circuitry

A. A. Vyshnevyy; G. A. Ermolaev; D. V. Grudinin; K. V. Voronin; I. Kharichkin et al. 

Fast evaluation of spherical harmonics with sphericart

F. Bigi; G. Fraux; N. J. Browning; M. Ceriotti 

Modelling of metal alloys in realistic conditions with machine learning

Effect of a temperature gradient on the screening properties of ionic fluids

A. Grisafi; F. Grasselli 

Modeling high-entropy transition metal alloys with alchemical compression

N. Lopanitsyna; G. Fraux; M. A. Springer; S. De; M. Ceriotti 

Machine-learning the electronic density of states: electronic properties without quantum mechanics

A data-driven interpretation of the stability of organic molecular crystals

R. K. Cersonsky; M. Pakhnova; E. A. Engel; M. Ceriotti 

Ranking the synthesizability of hypothetical zeolites with the sorting hat

B. A. Helfrecht; G. Pireddu; R. Semino; S. Auerbach; M. Ceriotti 

Roadmap on Machine learning in electronic structure

H. J. Kulik; T. Hammerschmidt; J. Schmidt; S. Botti; M. A. L. Marques et al. 

Electrokinetic, electrochemical, and electrostatic surface potentials of the pristine water liquid-vapor interface

M. R. Becker; P. Loche; R. R. Netz 

A smooth basis for atomistic machine learning

F. Bigi; K. K. Huguenin-Dumittan; M. Ceriotti; D. E. Manolopoulos 

Beyond potentials: Integrated machine learning models for materials

M. Ceriotti 

Incompleteness of graph neural networks for points clouds in three dimensions

S. N. Pozdnyakov; M. Ceriotti 

Effects of surface rigidity and metallicity on dielectric properties and ion interactions at aqueous hydrophobic interfaces

P. Loche; L. Scalfi; M. A. Amu; O. Schullian; D. J. Bonthuis et al. 

Comment on “Manifolds of quasi-constant SOAP and ACSF fingerprints and the resulting failure to machine learn four-body interactions” [J. Chem. Phys. 156, 034302 (2022)]

S. N. N. Pozdnyakov; M. J. J. Willatt; A. P. P. Bartok; C. Ortner; G. Csanyi et al. 

Predicting hot-electron free energies from ground-state data

C. Ben Mahmoud; F. Grasselli; M. Ceriotti 

Thermodynamics and dielectric response of BaTiO3 by data-driven modeling

L. Gigli; M. Veit; M. Kotiuga; G. Pizzi; N. Marzari et al. 

A Machine Learning Model of Chemical Shifts for Chemically and Structurally Diverse Molecular Solids

M. Cordova; E. A. Engel; A. Stefaniuk; F. Paruzzo; A. Hofstetter et al. 

Topology, Oxidation States, and Charge Transport in Ionic Conductors

P. Pegolo; S. Baroni; F. Grasselli 

Characterization and prediction of peptide structures on inorganic surfaces

Unified theory of atom-centered representations and message-passing machine-learning schemes

J. Nigam; S. Pozdnyakov; G. Fraux; M. Ceriotti 

Investigating finite-size effects in molecular dynamics simulations of ion diffusion, heat transport, and thermal motion in superionic materials

F. Grasselli 

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

R. Fabregat; A. Fabrizio; E. A. Engel; B. Meyer; V. Juraskova et al. 

Molecular dynamics simulations of the evaporation of hydrated ions from aqueous solution

P. Loche; D. J. Bonthuis; R. R. Netz 

A complete description of thermodynamic stabilities of molecular crystals

V. Kapil; E. A. Engel 

Temperature- and vacancy-concentration-dependence of heat transport in Li3ClO from multi-method numerical simulations

P. Pegolo; S. Baroni; F. Grasselli 

Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties

J. Nigam; M. J. Willatt; M. Ceriotti 

A route to hierarchical assembly of colloidal diamond

Y. Zhou; R. K. Cersonsky; S. C. Glotzer 

Local invertibility and sensitivity of atomic structure-feature mappings

S. N. Pozdnyakov; L. Zhang; C. Ortner; G. Csányi; M. Ceriotti 

2020 JCP Emerging Investigator Special Collection

M. Ceriotti; L. Jensen; D. E. Manolopoulos; T. J. Martinez; A. Michaelides et al. 

Reply to: On the liquid-liquid phase transition of dense hydrogen

B. Cheng; G. Mazzola; C. J. Pickard; M. Ceriotti 

Learning Electron Densities in the Condensed Phase

A. M. Lewis; A. Grisafi; M. Ceriotti; M. Rossi 

Bayesian probabilistic assignment of chemical shifts in organic solids

M. Cordova; M. Balodis; B. S. de Almeida; M. Ceriotti; L. Emsley 

Transferable machine-learning models of complex materials: the case of GaAs

Optimal radial basis for density-based atomic representations

A. Goscinski; F. Musil; S. Pozdnyakov; J. Nigam; M. Ceriotti 

Introduction: Machine Learning at the Atomic Scale

M. Ceriotti; C. Clementi; O. A. von Lilienfeld 

Gaussian Process Regression for Materials and Molecules

V. L. Deringer; A. P. Bartok; N. Bernstein; D. M. Wilkins; M. Ceriotti et al. 

Chemical physics software

C. D. Sherrill; D. E. Manolopoulos; T. J. Martinez; M. Ceriotti; A. Michaelides 

Physics-Inspired Structural Representations for Molecules and Materials

F. Musil; A. Grisafi; A. P. Bartok; C. Ortner; G. Csanyi et al. 

Importance of Nuclear Quantum Effects for NMR Crystallography

E. A. Engel; V. Kapil; M. Ceriotti 

Quantum vibronic effects on the electronic properties of solid and molecular carbon

A. Kundu; M. Govoni; H. Yang; M. Ceriotti; F. Gygi et al. 

Invariance principles in the theory and computation of transport coefficients

F. Grasselli; S. Baroni 

Improving sample and feature selection with principal covariates regression

R. K. Cersonsky; B. A. Helfrecht; E. A. Engel; S. Kliavinek; M. Ceriotti 

Modeling the Ga/As binary system across temperatures and compositions from first principles

G. Imbalzano; M. Ceriotti 

Structure-Property Relationships in Complex Materials by Combining Supervised and Unsupervised Machine Learning

Global Free-Energy Landscapes as a Smoothly Joined Collection of Local Maps

F. Giberti; G. A. Tribello; M. Ceriotti 

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Machine learning for metallurgy III: A neural network potential for Al-Mg-Si

A. C. P. Jain; D. Marchand; A. Glensk; M. Ceriotti; W. A. Curtin 

The role of feature space in atomistic learning

A. Goscinski; G. Fraux; G. Imbalzano; M. Ceriotti 

Machine learning meets chemical physics

M. Ceriotti; C. Clementi; O. Anatole von Lilienfeld 

Finite-temperature materials modeling from the quantum nuclei to the hot electron regime

N. Lopanitsyna; C. Ben Mahmoud; M. Ceriotti 

A general and efficient framework for atomistic machine learning

Uncertainty estimation for molecular dynamics and sampling

G. Imbalzano; Y. Zhuang; V. Kapil; K. Rossi; E. A. Engel et al. 

Efficient implementation of atom-density representations

F. Musil; M. Veit; A. Goscinski; G. Fraux; M. J. Willatt et al. 

Simulating the ghost: quantum dynamics of the solvated electron

J. Lan; V. Kapil; P. Gasparotto; M. Ceriotti; M. Iannuzzi et al. 

Multi-scale approach for the prediction of atomic scale properties

A. Grisafi; J. Nigam; M. Ceriotti 

Origins of structural and electronic transitions in disordered silicon

V. L. Deringer; N. Bernstein; G. Csányi; C. Ben Mahmoud; M. Ceriotti et al. 

Structure-property maps with Kernel principal covariates regression

B. A. Helfrecht; R. K. Cersonsky; G. Fraux; M. Ceriotti 

Learning the electronic density of states in condensed matter

C. Ben Mahmoud; A. Anelli; G. Csanyi; M. Ceriotti 

Oxidation States, Thouless’ Pumps, and Nontrivial Ionic Transport in Nonstoichiometric Electrolytes

P. Pegolo; F. Grasselli; S. Baroni 

Characterising Structure and Stability of Materials using Machine Learning

DUBS: A Framework for Developing Directory of Useful Benchmarking Sets for Virtual Screening

J. Fine; M. Muhoberac; G. Fraux; G. Chopra 

Incompleteness of Atomic Structure Representations

S. N. Pozdnyakov; M. J. Willatt; A. P. Bartok; C. Ortner; G. Csanyi et al. 

Gas-sieving zeolitic membranes fabricated by condensation of precursor nanosheets

M. Dakhchoune; L. F. Villalobos; R. Semino; L. Liu; M. Rezaei et al. 

Evidence for supercritical behaviour of high-pressure liquid hydrogen

B. Cheng; G. Mazzola; C. J. Pickard; M. Ceriotti 

Chemiscope: interactive structure-property explorer for materials and molecules

G. Fraux; R. Cersonsky; M. Ceriotti 

Recursive evaluation and iterative contraction of N-body equivariant features

J. Nigam; S. Pozdnyakov; M. Ceriotti 

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

G. Csányi; M. J. Willatt; M. Ceriotti 

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

P. Gkeka; G. Stoltz; A. B. Farimani; Z. Belkacemi; M. Ceriotti et al. 

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

K. Rossi; V. Juraskova; R. Wischert; L. Garel; C. Corminboeuf et al. 

Nuclear Quantum Effects: Fast and Accurate

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

M. Zamani; G. Imbalzano; N. Tappy; D. T. L. Alexander; S. Marti-Sanchez et al. 

Heat and charge transport in H2O at ice-giant conditions from ab initio molecular dynamics simulations

F. Grasselli; L. Stixrude; S. Baroni 

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

M. Veit; D. M. Wilkins; Y. Yang; R. A. DiStasio; M. Ceriotti 

Quantum kinetic energy and isotope fractionation in aqueous ionic solutions

L. Wang; M. Ceriotti; T. E. Markland 

Structural Screening and Design of Platinum Nanosamples for Oxygen Reduction

K. Rossi; G. G. Asara; F. Baletto 

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

V. Kapil; D. M. Wilkins; J. Lan; M. Ceriotti 

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

B. Cheng; M. Ceriotti; G. A. Tribello 

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

M. Asgari; R. Semino; P. A. Schouwink; I. Kochetygov; J. Tarver et al. 

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

I. Poltaysky; V. Kapil; M. Ceriotti; K. S. Kim; A. Tkatchenko 

Machine Learning-Guided Approach for Studying Solvation Environments

Y. Basdogan; M. C. Groenenboom; E. Henderson; S. De; S. B. Rempe et al. 

Identifying and Tracking Defects in Dynamic Supramolecular Polymers

P. Gasparotto; D. Bochicchio; M. Ceriotti; G. M. Pavan 

Iterative Unbiasing of Quasi-Equilibrium Sampling

F. Giberti; B. Cheng; G. A. Tribello; M. Ceriotti 

Atomistic modeling of the solid-liquid interface of metals and alloys

Learning (from/about) the ground-state electron density

C. Corminboeuf; M. Ceriotti; A. Fabrizio; A. Grisafi; B. Meyer et al. 

Machine Learning at the Atomic Scale

F. Musil; M. Ceriotti 

Representations and descriptors unifying the study of molecular and bulk systems

K. Rossi; J. Cumby 

Determination and evaluation of the nonadditivity in wetting of molecularly heterogeneous surfaces

Z. Luo; A. Murello; D. M. Wilkins; F. Kovacik; J. Kohlbrecher et al. 

Phonon Lifetimes Throughout the Brillouin Zone at Elevated Temperatures from Experiment and ab initio

A. Glensk; B. Grabowski; T. Hickel; J. Neugebauer; J. Neuhaus et al. 

Multi-Scale Electrolyte Transport Simulations for Lithium Ion Batteries

F. Hanke; N. Modrow; R. L. C. Akkermans; I. Korotkin; F. C. Mocanu et al. 

Atomic-Scale Representation and Statistical Learning of Tensorial Properties

A. Grisafi; D. M. Wilkins; M. J. Willatt; M. Ceriotti 

Incorporating long-range physics in atomic-scale machine learning

A. Grisafi; M. Ceriotti 

Assessment of Approximate Methods for Anharmonic Free Energies

V. Kapil; E. A. Engel; M. Rossi; M. Ceriotti 

A Bayesian approach to NMR crystal structure determination

E. A. Engel; A. Anelli; A. Hofstetter; F. M. Paruzzo; L. Emsley et al. 

A new kind of atlas of zeolite building blocks

B. A. Helfrecht; R. Semino Barbaresi; G. Pireddu; S. M. Auerbach; M. Ceriotti 

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

B. A. Helfrecht; P. Gasparotto; F. Giberti; M. Ceriotti 

Barely porous organic cages for hydrogen isotope separation

M. Liu; L. Zhang; M. A. Little; V. Kapil; M. Ceriotti et al. 

Unsupervised machine learning in atomistic simulations, between predictions and understanding

M. Ceriotti 

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

M. Asgari; R. Semino; P. Schouwink; I. Kochetygov; O. Trukhina et al. 

Atom-density representations for machine learning

M. J. Willatt; F. Musil; M. Ceriotti 

Fast and Accurate Uncertainty Estimation in Chemical Machine Learning

M. J. Willatt; F. Musil; M. Ceriotti; M. A. Langovoy 

Using Gaussian process regression to simulate the vibrational Raman spectra of molecular crystals

N. Raimbault; A. Grisafi; M. Ceriotti; M. Rossi 

Electron density learning of non-covalent systems

A. Fabrizio; A. Grisafi; B. Meyer; M. Ceriotti; C. Corminboeuf 

Thermal Engineering of Metal-Organic Frameworks for Adsorption Applications: A Molecular Simulation Perspective

J. Wieme; S. Vandenbrande; A. Lamaire; V. Kapil; L. Vanduyfhuys et al. 

Modeling the Structural and Thermal Properties of Loaded Metal–Organic Frameworks. An Interplay of Quantum and Anharmonic Fluctuations

V. Kapil; J. Wieme; S. Vandenbrande; A. Lamaire; V. Van Speybroeck et al. 

Correlating Oxygen Reduction Reaction Activity and Structural Rearrangements in MgO-Supported Platinum Nanoparticles

K. Rossi; G. G. Asara; F. Baletto 

Accurate molecular polarizabilities with coupled cluster theory and machine learning

D. M. Wilkins; A. Grisafi; Y. Yang; K. U. Lao; R. A. DiStasio et al. 

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

Y. Yang; K. U. Lao; D. M. Wilkins; A. Grisafi; M. Ceriotti et al. 

Path-integral dynamics of water using curvilinear centroids

G. Trenins; M. J. Willatt; S. C. Althorpe 

Physics-based machine learning for materials and molecules

M. Ceriotti; E. Engel; M. Willatt 

Energy Relaxation and Thermal Diffusion in Infrared Pump-Probe Spectroscopy of Hydrogen-Bonded Liquids

R. Dettori; M. Ceriotti; J. Hunger; L. Colombo; D. Donadio 

Modeling Superlattices of Dipolar and Polarizable Semiconducting Nanoparticles

S. Mazzotti; F. Giberti; G. Galli 

i-PI 2.0: A universal force engine for advanced molecular simulations

V. Kapil; M. Rossi; O. Marsalek; R. Petraglia; Y. Litman et al. 

Data Science Based Mg Corrosion Engineering

T. Wuerger; C. Feiler; F. Musil; G. B. V. Feldbauer; D. Hoeche et al. 

Equation of State of Fluid Methane from First Principles with Machine Learning Potentials

M. Veit; S. K. Jain; S. Bonakala; I. Rudra; D. Hohl et al. 

Chemical machine learning with kernels: The impact of loss functions

Quang Van Nguyen; S. De; J. Lin; V. Cevher 

Transferable Machine-Learning Model of the Electron Density

A. Grisafi; A. Fabrizio; B. Meyer; D. M. Wilkins; C. Corminboeuf et al. 

Ab initio thermodynamics of liquid and solid water

B. Cheng; E. A. Engel; J. Behler; C. Dellago; M. Ceriotti 

Predicting homogeneous nucleation rate from atomistic simulations

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

M. Hellström; M. Ceriotti; J. Behler 

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

J. Yang; S. De; J. E. Campbell; S. Li; M. Ceriotti et al. 

Chemical shifts in molecular solids by machine learning

F. M. Paruzzo; A. Hofstetter; F. Musil; S. De; M. Ceriotti et al. 

Generalized convex hull construction for materials discovery

A. Anelli; E. A. Engel; C. J. Pickard; M. Ceriotti 

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

T. T. Nguyen; E. Székely; G. Imbalzano; J. Behler; G. Csányi et al. 

Decisive role of nuclear quantum effects on surface mediated water dissociation at finite temperature

Y. Litman; D. Donadio; M. Ceriotti; M. Rossi 

Feature optimization for atomistic machine learning yields a data-driven construction of the periodic table of the elements

M. J. Willatt; F. Musil; M. Ceriotti 

Approximating Matsubara dynamics using the planetary model: Tests on liquid water and ice

M. J. Willatt; M. Ceriotti; S. C. Althorpe 

Hydrogen Diffusion and Trapping in α-Iron: The Role of Quantum and Anharmonic Fluctuations

B. Cheng; A. T. Paxton; M. Ceriotti 

Hydrogen dynamics in solid formic acid: insights from simulations with quantum colored-noise thermostats

K. Druzbicki; M. Krzystyniak; D. Hollas; V. Kapil; P. Slavicek et al. 

Comment on “Water- water correlations in electrolyte solutions probed by hyper-Rayleigh scattering” [J. Chem. Phys. 147, 214505 (2017)]

Y. Chen; H. I. Okur; N. Dupertuis; J. Dedic; D. M. Wilkins et al. 

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

Thuong Nguyen; E. Szekely; G. Imbalzano; J. Behler; G. Csanyi et al. 

Theoretical prediction of the homogeneous ice nucleation rate: disentangling thermodynamics and kinetics

B. Cheng; C. Dellago; M. Ceriotti 

Machine learning across the periodic table

M. Willatt 

Revealing the Transient Concentration of CO2 in a Mixed-Matrix Membrane by IR Microimaging and Molecular Modeling

S. Hwang; R. Semino; B. Seoane; M. Zahan; C. Chmelik et al. 

Enhanced gas separation performance of 6FDA-DAM based mixed matrix membranes by incorporating MOF UiO-66 and its derivatives

M. Ahmad; M. Navarro; M. Lhotka; B. Zornoza; C. Tellez et al. 

Applications of machine learning for studying local solvation environments

M. Groenonboom; S. De; M. Ceriotti; J. Keith 

Early Stages of Precipitation In Aluminum Alloys by First-Principles and Machine-Learning Atomistic Simulations

Communication: Computing the Tolman length for solid-liquid interfaces

B. Cheng; M. Ceriotti 

Mapping uncharted territory in ice from zeolite networks to ice structures

E. A. Engel; A. Anelli; M. Ceriotti; C. J. Pickard; R. J. Needs 

Anisotropy of the Proton Momentum Distribution in Water

V. Kapil; A. Cuzzocrea; M. Ceriotti 

Fast-forward Langevin dynamics with momentum flips

M. Hijazi; D. M. Wilkins; M. Ceriotti 

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

G. Imbalzano; A. Anelli; D. Giofré; S. Klees; J. Behler et al. 

An Automatic, Data-Driven Definition of Atomic-Scale Structural Motifs

Analyzing Fluxional Molecules Using DORI

L. Vannay; B. Meyer; R. Petraglia; G. Sforazzini; M. Ceriotti et al. 

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

B. Cheng; M. Ceriotti 

Recognizing Local and Global Structural Motifs at the Atomic Scale

P. Gasparotto; R. H. Meißner; M. Ceriotti 

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

F. Musil; S. De; J. Yang; J. E. Campbell; G. M. Day et al. 

Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems

A. Grisafi; D. M. Wilkins; G. Csányi; M. Ceriotti 

Nuclear quantum effects enter the mainstream

T. E. Markland; M. Ceriotti 

Chemical machine learning with kernels: The key impact of loss functions

V. Q. Nguyen; S. De; J. Lin; V. Cevher 

Fine tuning classical and quantum molecular dynamics using a generalized Langevin equation

M. Rossi; V. Kapil; M. Ceriotti 

Machine learning unifies the modeling of materials and molecules

A. P. Bartok; S. De; C. Poelking; N. Bernstein; J. R. Kermode et al. 

Atomistic Simulations of the Crystallization and Aging of GeTe Nanowires

S. Gabardi; E. Baldi; E. Bosoni; D. Campi; S. Caravati et al. 

Extracting the interfacial free energy and anisotropy from a smooth fluctuating dividing surface

E. Baldi; M. Ceriotti; G. A. Tribello 

The Gibbs free energy of homogeneous nucleation: From atomistic nuclei to the planar limit

B. Cheng; G. A. Tribello; M. Ceriotti 

Solvent fluctuations and nuclear quantum effects modulate the molecular hyperpolarizability of water

C. Liang; G. Tocci; D. M. Wilkins; A. Grisafi; S. Roke et al. 

Nuclear Quantum Effects in Water Reorientation and Hydrogen-Bond Dynamics

D. M. Wilkins; D. E. Manolopoulos; S. Pipolo; D. Laage; J. T. Hynes 

Mapping the conformational free energy of aspartic acid in the gas phase and in aqueous solution

F. Comitani; K. Rossi; M. Ceriotti; M. E. Sanz; C. Molteni 

Communication: Mean-field theory of water-water correlations in electrolyte solutions

D. M. Wilkins; D. E. Manolopoulos; S. Roke; M. Ceriotti 

Simulating Energy Relaxation in Pump-Probe Vibrational Spectroscopy of Hydrogen-Bonded Liquids

R. Dettori; M. Ceriotti; J. Hunger; C. Melis; L. Colombo et al. 

Structure of a model TiO2 photocatalytic interface

H. Hussain; G. Tocci; T. Woolcot; X. Torrelles; C. L. Pang et al. 

Mapping and classifying molecules from a high-throughput structural database

S. De; F. Musil; T. Ingram; C. Baldauf; M. Ceriotti 

Bridging the gap between atomistic and macroscopic models of homogeneous nucleation

B. Cheng; M. Ceriotti 

High order path integrals made easy

V. Kapil; J. Behler; M. Ceriotti 

Second-Harmonic Scattering as a Probe of Structural Correlations in Liquids

G. Tocci; C. Liang; D. M. Wilkins; S. Roke; M. Ceriotti 

Nuclear Quantum Effects in H+ and OH- Diffusion along Confined Water Wires

M. Rossi; M. Ceriotti; D. E. Manolopoulos 

Accelerated path integral methods for atomistic simulations at ultra-low temperatures

F. Uhl; D. Marx; M. Ceriotti 

Nuclear Quantum Effects in Water and Aqueous Systems: Experiment, Theory, and Current Challenges

M. Ceriotti; W. Fang; P. G. Kusalik; R. H. Mckenzie; A. Michaelides et al. 

Thermally-nucleated self-assembly of water and alcohol into stable structures at hydrophobic interfaces

K. Voïtchovsky; D. Giofrè; J. José Segura; F. Stellacci; M. Ceriotti 

Anharmonic and Quantum Fluctuations in Molecular Crystals: A First-Principles Study of the Stability of Paracetamol

M. Rossi; P. Gasparotto; M. Ceriotti 

Vitrification: Machines learn to recognize glasses

M. Ceriotti; V. Vitelli 

Electronic transport in B-N substituted bilayer graphene nanojunctions

D. Giofre; D. Ceresoli; G. Fratesi; M. I. Trioni 

Nuclear Quantum Effects in Water at the Triple Point: Using Theory as a Link Between Experiments

B. Cheng; J. Behler; M. Ceriotti 

Probing Defects and Correlations in the Hydrogen-Bond Network of ab Initio Water

P. Gasparotto; A. A. Hassanali; M. Ceriotti 

Comparing molecules and solids across structural and alchemical space

S. De; A. P. Bartók; G. Csányi; M. Ceriotti 

Electrolytes induce long-range orientational order and free energy changes in the H-bond network of bulk water

Y. Chen; H. I. Okur; N. Gomopoulos; C. Macias-Romero; P. S. Cremer et al. 

Fast diffusion of water nanodroplets on graphene

M. Ma; G. Tocci; A. Michaelides; G. Aeppli 

Accurate molecular dynamics and nuclear quantum effects at low cost by multiple steps in real and imaginary time: Using density functional theory to accelerate wavefunction methods

V. Kapil; J. Vandevondele; M. Ceriotti 

Beyond Static Structures: Putting Forth REMD as a Tool to Solve Problems in Computational Organic Chemistry

R. Petraglia; A. G. Nicolai; M. Wodrich; M. Ceriotti; C. Corminboeuf 

Solid-liquid interfacial free energy out of equilibrium

B. Cheng; G. A. Tribello; M. Ceriotti 

Probing the Unfolded Configurations of a β-Hairpin Using Sketch-Map

A. Ardevol; G. A. Tribello; M. Ceriotti; M. Parrinello 

Modeling the Quantum Nature of Atomic Nuclei by Imaginary Time Path Integrals and Colored Noise

M. Ceriotti 

Direct path integral estimators for isotope fractionation ratios

B. Cheng; M. Ceriotti 

Discussion: Theoretical Horizons and Calculation

M. Ceriotti; C. Drechsel-Grau; F. Fernandez-Alonso; N. Greaves; M. Krzystyniak et al. 

The Role of Quantum Effects on Structural and Electronic Fluctuations in Neat and Charged Water

F. Giberti; A. A. Hassanali; M. Ceriotti; M. Parrinello 

Ab initio simulation of particle momentum distributions in high-pressure water

M. Ceriotti 

Communication: On the consistency of approximate quantum dynamics simulation methods for vibrational spectra in the condensed phase

M. Rossi; H. Liu; F. Paesani; J. Bowman; M. Ceriotti 

Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond

P. Gasparotto; M. Ceriotti 

Quantum fluctuations and isotope effects in ab initio descriptions of water

L. Wang; M. Ceriotti; T. E. Markland 

How to remove the spurious resonances from ring polymer molecular dynamics

M. Rossi; M. Ceriotti; D. E. Manolopoulos 

Evaluating functions of positive-definite matrices using colored-noise thermostats

M. Nava; M. Ceriotti; C. Dryzun; M. Parrinello 

i-PI: A Python interface for ab initio path integral molecular dynamics simulations

M. Ceriotti; J. More; D. E. Manolopoulos 

Effects of High Angular Momentum on the Unimolecular Dissociation of CD2CD2OH: Theory and Comparisons with Experiment

B. G. Mckown; M. Ceriotti; C. C. Womack; E. Kamarchik; L. J. Butler et al. 

Direct Measurement of Competing Quantum Effects on the Kinetic Energy of Heavy Water upon Melting

G. Romanelli; M. Ceriotti; D. E. Manolopoulos; C. Pantalei; R. Senesi et al. 

Nuclear quantum effects and hydrogen bond fluctuations in water

M. Ceriotti; J. Cuny; M. Parrinello; D. E. Manolopoulos 

A Surface-Specific Isotope Effect in Mixtures of Light and Heavy Water

J. Liu; R. S. Andino; C. M. Miller; X. Chen; D. M. Wilkins et al. 

Efficient methods and practical guidelines for simulating isotope effects

M. Ceriotti; T. E. Markland 

Demonstrating the Transferability and the Descriptive Power of Sketch-Map

M. Ceriotti; G. A. Tribello; M. Parrinello 

The inefficiency of re-weighted sampling and the curse of system size in high-order path integration

M. Ceriotti; G. A. R. Brain; O. Riordan; D. E. Manolopoulos 

Using sketch-map coordinates to analyze and bias molecular dynamics simulations

G. A. Tribello; M. Ceriotti; M. Parrinello 

Simultaneous measurement of lithium and fluorine momentum in

A. G. Seel; M. Ceriotti; P. P. Edwards; J. Mayers 

The Fuzzy Quantum Proton in the Hydrogen Chloride Hydrates

A. A. Hassanali; J. Cuny; M. Ceriotti; C. J. Pickard; M. Parrinello 

Efficient First-Principles Calculation of the Quantum Kinetic Energy and Momentum Distribution of Nuclei

M. Ceriotti; D. E. Manolopoulos 

Efficient multiple time scale molecular dynamics: Using colored noise thermostats to stabilize resonances

J. A. Morrone; T. E. Markland; M. Ceriotti; B. J. Berne 

Static disorder and structural correlations in the low-temperature phase of lithium imide

G. Miceli; M. Ceriotti; M. Bernasconi; M. Parrinello 

First-Principles Study of the High-Temperature Phase of Li

G. Miceli; M. Ceriotti; S. Angioletti-Uberti; M. Bernasconi; M. Parrinello 

From the Cover: Simplifying the representation of complex free-energy landscapes using sketch-map

M. Ceriotti; G. A. Tribello; M. Parrinello 

Accelerating the convergence of path integral dynamics with a generalized Langevin equation

M. Ceriotti; D. E. Manolopoulos; M. Parrinello 

Solid-liquid interface free energy through metadynamics simulations

S. Angioletti-Uberti; M. Ceriotti; P. D. Lee; M. W. Finnis 

Colored-Noise Thermostats à la Carte

M. Ceriotti; G. Bussi; M. Parrinello 

Nuclear quantum effects in ab initio dynamics: Theory and experiments for lithium imide

M. Ceriotti; G. Miceli; A. Pietropaolo; D. Colognesi; A. Nale et al. 

The -thermostat: selective normal-modes excitation by colored-noise Langevin dynamics

M. Ceriotti; M. Parrinello 

Efficient stochastic thermostatting of path integral molecular dynamics

M. Ceriotti; M. Parrinello; T. E. Markland; D. E. Manolopoulos 

A self-learning algorithm for biased molecular dynamics

G. A. Tribello; M. Ceriotti; M. Parrinello 

Nuclear Quantum Effects in Solids Using a Colored-Noise Thermostat

M. Ceriotti; G. Bussi; M. Parrinello 

Langevin Equation with Colored Noise for Constant-Temperature Molecular Dynamics Simulations

M. Ceriotti; G. Bussi; M. Parrinello 

Ab initio study of the diffusion and decomposition pathways of SiHx species on Si(100)

M. Ceriotti; S. Cereda; F. Montalenti; L. Miglio; M. Bernasconi 

An efficient and accurate decomposition of the Fermi operator

M. Ceriotti; T. D. KüHne; M. Parrinello 

First principles study of Ge∕Si exchange mechanisms at the Si(001) surface

F. Zipoli; S. Cereda; M. Ceriotti; M. Bernasconi; L. Miglio et al. 

Quantitative estimate of H abstraction by thermal SiH3 on hydrogenated Si(001)(2×1)

S. Cereda; M. Ceriotti; F. Montalenti; M. Bernasconi; L. Miglio 

Diffusion and desorption of SiH3 on hydrogenated H:Si(100)-(2×1) from first principles

M. Ceriotti; M. Bernasconi 

Conjugate gradient heat bath for ill-conditioned actions

M. Ceriotti; G. Bussi; M. Parrinello 

Impact-driven effects in thin-film growth: steering and transient mobility at the Ag(110) surface

M. Ceriotti; R. Ferrando; F. Montalenti 

Ab initio study of the vibrational properties of crystalline TeO2: The α, β, and γ phases

M. Ceriotti; F. Pietrucci; M. Bernasconi