Citation Impact

Citing Papers

Perspective: Machine learning potentials for atomistic simulations
2016
State-of-the-art in artificial neural network applications: A survey
2018 Standout
A review of uncertainty quantification in deep learning: Techniques, applications and challenges
2021 Standout
LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales
2021 Standout
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
2012 Standout
A transferable model for singlet-fission kinetics
2014 StandoutNobel
Machine learning for molecular and materials science
2018 StandoutNature
Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations
2011
Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons
2010 Standout
Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties
2018 Standout
Density functional theory for transition metals and transition metal chemistry
2009
The EVB as a quantitative tool for formulating simulations and analyzing biological and chemical reactions
2009 StandoutNobel
Energy-free machine learning force field for aluminum
2017
Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces
2007 Standout
On-the-Fly Machine Learning of Atomic Potential in Density Functional Theory Structure Optimization
2018
Pushing the frontiers of density functionals by solving the fractional electron problem
2021 StandoutScienceNobel
Application of Artificial Neural Networks for Catalysis: A Review
2017
Charge constrained density functional molecular dynamics for simulation of condensed phase electron transfer reactions
2009
High-dimensional neural network potentials for metal surfaces: A prototype study for copper
2012
Machine learning based interatomic potential for amorphous carbon
2017
Configuration interaction based on constrained density functional theory: A multireference method
2007
Neural network interatomic potential for the phase change material GeTe
2012
Understanding the Composition and Activity of Electrocatalytic Nanoalloys in Aqueous Solvents: A Combination of DFT and Accurate Neural Network Potentials
2014
MoleculeNet: a benchmark for molecular machine learning
2017 Standout
Mechanism of Methanol Synthesis on Cu through CO2and CO Hydrogenation
2011 Standout
Mechanisms of Oxidase and Superoxide Dismutation-like Activities of Gold, Silver, Platinum, and Palladium, and Their Alloys: A General Way to the Activation of Molecular Oxygen
2015
Computer Simulation of Liquids
2017 Standout
A Nested Molecule-Independent Neural Network Approach for High-Quality Potential Fits
2005
Using neural networks to represent potential surfaces as sums of products
2006
Universality in Oxygen Evolution Electrocatalysis on Oxide Surfaces
2011 Standout
Nanozymes: Classification, Catalytic Mechanisms, Activity Regulation, and Applications
2019 Standout
Status and perspectives of CO2 conversion into fuels and chemicals by catalytic, photocatalytic and electrocatalytic processes
2013 Standout
Copper Active Sites in Biology
2014 Standout
Progress and Perspectives of Electrochemical CO2 Reduction on Copper in Aqueous Electrolyte
2019 Standout
Metadynamics Simulations of the High-Pressure Phases of Silicon Employing a High-Dimensional Neural Network Potential
2008
Using redundant coordinates to represent potential energy surfaces with lower-dimensional functions
2007
A neural network potential-energy surface for the water dimer based on environment-dependent atomic energies and charges
2012
Nonadiabatic potential-energy surfaces by constrained density-functional theory
2007
Lanthanide-Activated Phosphors Based on 4f-5d Optical Transitions: Theoretical and Experimental Aspects
2017 Standout
Direct Calculation of Electron Transfer Parameters through Constrained Density Functional Theory
2006
Crystal structure prediction via particle-swarm optimization
2010 Standout
Extracting electron transfer coupling elements from constrained density functional theory
2006
Stratified construction of neural network based interatomic models for multicomponent materials
2017
First-principles interatomic potentials for ten elemental metals via compressed sensing
2015
Challenges for Density Functional Theory
2011 Standout
Representation of compounds for machine-learning prediction of physical properties
2017
Constrained density functional theory based configuration interaction improves the prediction of reaction barrier heights
2009
Quantifying Free Energy Profiles of Proton Transfer Reactions in Solution and Proteins by Using a Diabatic FDFT Mapping
2008 StandoutNobel
Neural Network Models of Potential Energy Surfaces:  Prototypical Examples
2004
Interpolating moving least-squares methods for fitting potential energy surfaces: Using classical trajectories to explore configuration space
2009
First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems
2017
CO Oxidation by Rutile TiO2(110) Doped with V, W, Cr, Mo, and Mn
2008
Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO2 Reduction
2017
Interpolating moving least-squares methods for fitting potential energy surfaces: Computing high-density potential energy surface data from low-densityab initiodata points
2007
Potential Energy Surfaces Fitted by Artificial Neural Networks
2010
Design of electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions
2015 Standout
Recent advances and applications of machine learning in solid-state materials science
2019 Standout
Ab initio molecular simulations with numeric atom-centered orbitals
2009 Standout
Deep Eutectic Solvents: A Review of Fundamentals and Applications
2020 Standout
Coarse-Grained (Multiscale) Simulations in Studies of Biophysical and Chemical Systems
2011 StandoutNobel
An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO2
2016
Nanomaterials with enzyme-like characteristics (nanozymes): next-generation artificial enzymes (II)
2018 Standout
Controlling spin contamination using constrained density functional theory
2008
A consistent and accurateab initioparametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu
2010 Standout
Ab initioquality neural-network potential for sodium
2010
Dissociative dynamics of spin-triplet and spin-singlet O2 on Ag(100)
2008
Interpolating moving least-squares methods for fitting potential energy surfaces: A strategy for efficient automatic data point placement in high dimensions
2008
Speed Limit for Triplet-Exciton Transfer in Solid-State PbS Nanocrystal-Sensitized Photon Upconversion
2017 StandoutNobel
Physics-informed machine learning
2021 Standout
The empirical valence bond model: theory and applications
2011 StandoutNobel
Group-theoretical high-order rotational invariants for structural representations: Application to linearized machine learning interatomic potential
2019
Reactive Oxygen Species (ROS)-Based Nanomedicine
2019 Standout
Electronic coupling matrix elements from charge constrained density functional theory calculations using a plane wave basis set
2010
Deep learning and density-functional theory
2019
On Unjustifiably Misrepresenting the EVB Approach While Simultaneously Adopting It
2009 StandoutNobel
High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide
2011
On representing chemical environments
2013 Standout
Methods for interpreting and understanding deep neural networks
2017 Standout
Direct optimization method to study constrained systems within density-functional theory
2005
Designing materials for electrochemical carbon dioxide recycling
2019 Standout
Tuned Range-Separated Hybrids in Density Functional Theory
2010
Atom-centered symmetry functions for constructing high-dimensional neural network potentials
2011
Data-driven prediction of battery cycle life before capacity degradation
2019 Standout
Characterising performance of environmental models
2012 Standout
Origin of Linear Free Energy Relationships: Exploring the Nature of the Off-Diagonal Coupling Elements in SN2 Reactions
2012 StandoutNobel
O2Activation by Metal Surfaces: Implications for Bonding and Reactivity on Heterogeneous Catalysts
2017
Simultaneous fitting of a potential-energy surface and its corresponding force fields using feedforward neural networks
2009
Permutationally invariant potential energy surfaces in high dimensionality
2009 Standout
Addressing uncertainty in atomistic machine learning
2017
Assessment of a long-range corrected hybrid functional
2006 Standout
Algebraic sensitivity analysis of environmental models
2008
Efficient and accurate machine-learning interpolation of atomic energies in compositions with many species
2017
Constrained Density Functional Theory and Its Application in Long-Range Electron Transfer
2006
Perovskites in catalysis and electrocatalysis
2017 StandoutScience
Acceleration of saddle-point searches with machine learning
2016
Machine learning of molecular electronic properties in chemical compound space
2013

Works of Sönke Lorenz being referenced

Reactions on Surfaces with Neural Networks
2001
Dissociation ofO2at Al(111): The Role of Spin Selection Rules
2005
Adaptive approach for nonlinear sensitivity analysis of reaction kinetics
2005
Descriptions of surface chemical reactions using a neural network representation of the potential-energy surface
2006
Representing high-dimensional potential-energy surfaces for reactions at surfaces by neural networks
2004
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2026