Publications

Fast evaluation of spherical harmonics with sphericart

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

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 

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

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

Modelling of metal alloys in realistic conditions with machine learning

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

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 

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. 

Thermodynamics and dielectric response of BaTiO3 by data-driven modeling

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

Predicting hot-electron free energies from ground-state data

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

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. 

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. 

Topology, Oxidation States, and Charge Transport in Ionic Conductors

P. Pegolo; S. Baroni; F. Grasselli 

Roadmap on Machine learning in electronic structure

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

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

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

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

P. Loche; D. J. Bonthuis; R. R. Netz 

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

F. Grasselli 

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 

Ranking the synthesizability of hypothetical zeolites with the sorting hat

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

Characterization and prediction of peptide structures on inorganic surfaces

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. 

A route to hierarchical assembly of colloidal diamond

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

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 

Optimal radial basis for density-based atomic representations

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

Improving sample and feature selection with principal covariates regression

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

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 

Invariance principles in the theory and computation of transport coefficients

F. Grasselli; S. Baroni 

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

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

Chemical physics software

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

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

G. Imbalzano; M. Ceriotti 

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

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

The role of feature space in atomistic learning

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

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 

Machine learning meets chemical physics

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

Origins of structural and electronic transitions in disordered silicon

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

Local invertibility and sensitivity of atomic structure-feature mappings

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

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

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

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

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 

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 

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. 

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

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

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. 

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 

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

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

Structural Screening and Design of Platinum Nanosamples for Oxygen Reduction

K. Rossi; G. G. Asara; F. Baletto 

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 

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

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

Identifying and Tracking Defects in Dynamic Supramolecular Polymers

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

Structure-property maps with Kernel principal covariates regression

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

Characterising Structure and Stability of Materials using Machine Learning

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 

Nuclear Quantum Effects: Fast and Accurate

Machine Learning-Guided Approach for Studying Solvation Environments

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

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

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. 

Machine Learning at the Atomic Scale

F. Musil; M. Ceriotti 

Multi-Scale Electrolyte Transport Simulations for Lithium Ion Batteries

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

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. 

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

K. Rossi; G. G. Asara; F. Baletto 

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

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

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 

Chemical machine learning with kernels: The impact of loss functions

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

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. 

Physics-based machine learning for materials and molecules

M. Ceriotti; E. Engel; M. Willatt 

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

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

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 

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 

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. 

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. 

Predicting homogeneous nucleation rate from atomistic simulations

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

B. Cheng; C. Dellago; M. Ceriotti 

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. 

Machine learning across the periodic table

M. Willatt 

Analyzing Fluxional Molecules Using DORI

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

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. 

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

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 

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. 

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 

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