Nonclassical Nucleation of Zinc Oxide from a Physically Motivated Machine-Learning Approach

A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer

(2021) Tsz Wai Ko et al.   Nature Communications

General-Purpose Machine Learning Potentials Capturing Nonlocal Charge Transfer

(2021) Tsz Wai Ko et al.   ACCOUNTS OF CHEMICAL RESEARCH

An Artificial Neural Network Reveals the Nucleation Mechanism of a Binary Colloidal AB13 Crystal

(2021) Gabriele M. Coli et al.   ACS Nano

Is Ice Nucleation by Organic Crystals Nonclassical? An Assessment of the Monolayer Hypothesis of Ice Nucleation

(2021) Atanu K. Metya et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Compact atomic descriptors enable accurate predictions via linear models

(2021) Claudio Zeni et al.   JOURNAL OF CHEMICAL PHYSICS

Nonclassical Nucleation Pathways in Stacking-Disordered Crystals

(2021) Fabio Leoni et al.   Physical Review X

Automated free-energy calculation from atomistic simulations

(2021) Sarath Menon et al.   Physical Review Materials

Direct Observation of Amorphous Precursor Phases in the Nucleation of Protein–Metal–Organic Frameworks

(2020) Alana F. Ogata et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide

(2020) Ganesh Sivaraman et al.   npj Computational Materials

Role of pre-ordered liquid in the selection mechanism of crystal polymorphs during nucleation

(2020) Sarath Menon et al.   JOURNAL OF CHEMICAL PHYSICS

Predicting oxidation and spin states by high-dimensional neural networks: Applications to lithium manganese oxide spinels

(2020) Marco Eckhoff et al.   JOURNAL OF CHEMICAL PHYSICS

Out-of-Equilibrium Polymorph Selection in Nanoparticle Freezing

(2020) Jonathan Amodeo et al.   Journal of Physical Chemistry Letters

Synthesis of Zinc Oxide Nanoparticles by Ecofriendly Routes: Adsorbent for Copper Removal From Wastewater

(2020) Julia de O. Primo et al.   Frontiers in Chemistry

Subtlety of TiO2 phase stability: Reliability of the density functional theory predictions and persistence of the self-interaction error

(2019) Yubo Zhang et al.   JOURNAL OF CHEMICAL PHYSICS

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

(2019) Max Veit et al.   Journal of Chemical Theory and Computation

Molecular force fields with gradient-domain machine learning: Construction and application to dynamics of small molecules with coupled cluster forces

(2019) Huziel E. Sauceda et al.   JOURNAL OF CHEMICAL PHYSICS

How Size and Aggregation of Ice-Binding Proteins Control Their Ice Nucleation Efficiency

(2019) Yuqing Qiu et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

How crystals form: A theory of nucleation pathways

(2019) James F. Lutsko   Science Advances

Moment tensor potentials as a promising tool to study diffusion processes

(2019) I.I. Novoselov et al.   COMPUTATIONAL MATERIALS SCIENCE

New Horizons of Nonclassical Crystallization

(2019) Marie Jehannin et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Phase Transitions of Hybrid Perovskites Simulated by Machine-Learning Force Fields Trained on the Fly with Bayesian Inference

(2019) Ryosuke Jinnouchi et al.   PHYSICAL REVIEW LETTERS

Towards better efficiency of interatomic linear machine learning potentials

(2019) Alexandra M. Goryaeva et al.   COMPUTATIONAL MATERIALS SCIENCE

Unsupervised learning for local structure detection in colloidal systems

(2019) Emanuele Boattini et al.   JOURNAL OF CHEMICAL PHYSICS

Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

(2018) Tristan Bereau et al.   JOURNAL OF CHEMICAL PHYSICS

New optimization scheme to obtain interaction potentials for oxide glasses

(2018) Siddharth Sundararaman et al.   JOURNAL OF CHEMICAL PHYSICS

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

(2018) Thuong T. Nguyen et al.   JOURNAL OF CHEMICAL PHYSICS

Linearized machine-learning interatomic potentials for non-magnetic elemental metals: Limitation of pairwise descriptors and trend of predictive power

(2018) Akira Takahashi et al.   JOURNAL OF CHEMICAL PHYSICS

Building machine learning force fields for nanoclusters

(2018) Claudio Zeni et al.   JOURNAL OF CHEMICAL PHYSICS

Extending the accuracy of the SNAP interatomic potential form

(2018) Mitchell A. Wood et al.   JOURNAL OF CHEMICAL PHYSICS

Realistic Atomistic Structure of Amorphous Silicon from Machine-Learning-Driven Molecular Dynamics

(2018) Volker L. Deringer et al.   Journal of Physical Chemistry Letters

Similarity Between Amorphous and Crystalline Phases: The Case of TiO2

(2018) Juraj Mavračić et al.   Journal of Physical Chemistry Letters

Understanding the thermal properties of amorphous solids using machine-learning-based interatomic potentials

(2018) Gabriele C. Sosso et al.   MOLECULAR SIMULATION

Lattice induced crystallization of nanodroplets: the role of finite-size effects and substrate properties in controlling polymorphism

(2018) Julien Lam et al.   Nanoscale

Growth Mechanism and Origin of High sp3 Content in Tetrahedral Amorphous Carbon

(2018) Miguel A. Caro et al.   PHYSICAL REVIEW LETTERS

Computational Surface Chemistry of Tetrahedral Amorphous Carbon by Combining Machine Learning and Density Functional Theory

(2018) Volker L. Deringer et al.   CHEMISTRY OF MATERIALS

Why Is It So Difficult to Identify the Onset of Ice Premelting?

(2018) Yuqing Qiu et al.   Journal of Physical Chemistry Letters

Molecular nucleation mechanisms and control strategies for crystal polymorph selection

(2018) Alexander E. S. Van Driessche et al.   NATURE

Towards exact molecular dynamics simulations with machine-learned force fields

(2018) Stefan Chmiela et al.   Nature Communications

Ice Nucleation on a Corrugated Surface

(2018) Chenfang Lin et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Machine Learning a General-Purpose Interatomic Potential for Silicon

(2018) Albert P. Bartók et al.   Physical Review X

Modeling Iron–Gold Nanoparticles Using a Dedicated Semi-Empirical Potential: Application to the Stability of Core–Shell Structures

(2017) F. Calvo et al.   Journal of Physical Chemistry C

Size dependent structural and polymorphic transitions in ZnO: from nanocluster to bulk

(2017) Francesc Viñes et al.   Nanoscale

Role of stacking disorder in ice nucleation

(2017) Laura Lupi et al.   NATURE

Navigating at Will on the Water Phase Diagram

(2017) S. Pipolo et al.   PHYSICAL REVIEW LETTERS

Two types of amorphous protein particles facilitate crystal nucleation

(2017) Tomoya Yamazaki et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Machine learning unifies the modeling of materials and molecules

(2017) Albert P. Bartók et al.   Science Advances

Machine learning of accurate energy-conserving molecular force fields

(2017) Stefan Chmiela et al.   Science Advances

Conceptual and practical bases for the high accuracy of machine learning interatomic potentials: Application to elemental titanium

(2017) Akira Takahashi et al.   PHYSICAL REVIEW MATERIALS

Crystal Nucleation in Liquids: Open Questions and Future Challenges in Molecular Dynamics Simulations

(2016) Gabriele C. Sosso et al.   CHEMICAL REVIEWS

An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO 2

(2016) Nongnuch Artrith et al.   COMPUTATIONAL MATERIALS SCIENCE

Machine Learning Force Fields: Construction, Validation, and Outlook

(2016) V. Botu et al.   Journal of Physical Chemistry C

Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials

(2016) Alexander V. Shapeev   MULTISCALE MODELING & SIMULATION

Phase stability of TiO2polymorphs from diffusion Quantum Monte Carlo

(2016) Ye Luo et al.   NEW JOURNAL OF PHYSICS

Neural network molecular dynamics simulations of solid–liquid interfaces: water at low-index copper surfaces

(2016) Suresh Kondati Natarajan et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Tersoff potential with improved accuracy for simulating graphene in molecular dynamics environment

(2016) G Rajasekaran et al.   Materials Research Express

Nonclassical nucleation and growth of inorganic nanoparticles

(2016) Jisoo Lee et al.   Nature Reviews Materials

The ReaxFF reactive force-field: development, applications and future directions

(2016) Thomas P Senftle et al.   npj Computational Materials

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

(2015) A.P. Thompson et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Classical interaction potentials for diverse materials fromab initiodata: a review ofpotfit

(2015) Peter Brommer et al.   MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING

Structural, electronic, and spectral properties of six ZnO bulk polymorphs

(2015) Lorenzo Sponza et al.   PHYSICAL REVIEW B

First-principles interatomic potentials for ten elemental metals via compressed sensing

(2015) Atsuto Seko et al.   PHYSICAL REVIEW B

First principles phonon calculations in materials science

(2015) Atsushi Togo et al.   SCRIPTA MATERIALIA

Heterogeneous Nucleation of Ice on Carbon Surfaces

(2014) Laura Lupi et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

New metastable form of ice and its role in the homogeneous crystallization of water

(2014) John Russo et al.   NATURE MATERIALS

Entropy-driven formation of large icosahedral colloidal clusters by spherical confinement

(2014) Bart de Nijs et al.   NATURE MATERIALS

Structure of molten titanium dioxide

(2014) O. L. G. Alderman et al.   PHYSICAL REVIEW B

Sparse representation for a potential energy surface

(2014) Atsuto Seko et al.   PHYSICAL REVIEW B

Role of clusters in nonclassical nucleation and growth of protein crystals

(2014) Mike Sleutel et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Observing classical nucleation theory at work by monitoring phase transitions with molecular precision

(2014) Mike Sleutel et al.   Nature Communications

Observation of the amorphous zinc oxide recrystalline process by molecular dynamics simulation

(2013) Ken-Huang Lin et al.   JOURNAL OF APPLIED PHYSICS

A Density-Functional Theory-Based Neural Network Potential for Water Clusters Including van der Waals Corrections

(2013) Tobias Morawietz et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Reactive potential for the study of phase-change materials: GeTe

(2013) Federico Zipoli et al.   NEW JOURNAL OF PHYSICS

Machine-learning approach for one- and two-body corrections to density functional theory: Applications to molecular and condensed water

(2013) Albert P. Bartók et al.   PHYSICAL REVIEW B

Nanofilm versus Bulk Polymorphism in Wurtzite Materials

(2013) Ilker Demiroglu et al.   PHYSICAL REVIEW LETTERS

Reversible Wurtzite-Tetragonal Reconstruction in ZnO(10$\bar 1$0) Surfaces

(2012) Mo-Rigen He et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

A neural network potential-energy surface for the water dimer based on environment-dependent atomic energies and charges

(2012) Tobias Morawietz et al.   JOURNAL OF CHEMICAL PHYSICS

Neural network potentials for metals and oxides - First applications to copper clusters at zinc oxide

(2012) Nongnuch Artrith et al.   PHYSICA STATUS SOLIDI B-BASIC SOLID STATE PHYSICS

The microscopic pathway to crystallization in supercooled liquids

(2012) John Russo et al.   Scientific Reports

Polymorphous Transformations of Nanometric Iron(III) Oxide: A Review

(2011) Libor Machala et al.   CHEMISTRY OF MATERIALS

Structural transformation in supercooled water controls the crystallization rate of ice

(2011) Emily B. Moore et al.   NATURE

High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide

(2011) Nongnuch Artrith et al.   PHYSICAL REVIEW B

Crystallization Mechanism of Hard Sphere Glasses

(2011) Eduardo Sanz et al.   PHYSICAL REVIEW LETTERS

Wurtzite-to-tetragonal structure phase transformation and size effect in ZnO nanorods

(2010) J. Wang et al.   JOURNAL OF APPLIED PHYSICS

Review of the anatase to rutile phase transformation

(2010) Dorian A. H. Hanaor et al.   JOURNAL OF MATERIALS SCIENCE

Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons

(2010) Albert P. Bartók et al.   PHYSICAL REVIEW LETTERS

Hard spheres: crystallization and glass formation

(2009) P. N. Pusey et al.   PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Preferential stability of the d-BCT phase in ZnO thin films

(2009) Benjamin J. Morgan   PHYSICAL REVIEW B

Interaction potentials for alumina and molecular dynamics simulations of amorphous and liquid alumina

(2008) Priya Vashishta et al.   JOURNAL OF APPLIED PHYSICS

Nanocrystalline transition aluminas: Nanostructure and features of x-ray powder diffraction patterns of low-temperatureAl2O3polymorphs

(2008) Sergey V. Tsybulya et al.   PHYSICAL REVIEW B

First-principles calculations of the ferroelastic transition between rutile-type andCaCl2-typeSiO2at high pressures

(2008) Atsushi Togo et al.   PHYSICAL REVIEW B

Size-Driven Structural and Thermodynamic Complexity in Iron Oxides

(2008) A. Navrotsky et al.   SCIENCE

A reactive force field (ReaxFF) for zinc oxide

(2008) David Raymand et al.   SURFACE SCIENCE