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20122023
most citedPerspective on integrating machine learning into computational chemistry and materials science

203 citations · 1.6k across the 43 of their papers we have counts for

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15 papers · 1 filter

physics.chem-ph2023★ 23 cited

libMBD: A general-purpose package for scalable quantum many-body dispersion calculations

Jan Hermann, Martin Stöhr, Szabolcs Góger +4

Many-body dispersion (MBD) is a powerful framework to treat van der Waals (vdW) dispersion interactions in density-functional theory and related atomistic modeling methods. Several…

physics.chem-ph2023★ 26 cited

Assessing mixed quantum-classical molecular dynamics methods for nonadiabatic dynamics of molecules on metal surfaces

James Gardner, Scott Habershon, Reinhard J. Maurer

Mixed-quantum classical (MQC) methods for simulating the dynamics of molecules at metal surfaces have the potential to accurately and efficiently provide mechanistic insight into r…

physics.chem-ph2023

Machine learning interatomic potentials for reactive hydrogen dynamics at metal surfaces based on iterative refinement of reaction probabilities

Wojciech G. Stark, Julia Westermayr, Oscar A. Douglas-Gallardo +3

Reactive chemistry of molecular hydrogen at surfaces, notably dissociative sticking and hydrogen evolution, plays a crucial role in energy storage and fuel cells. Theoretical studi…

physics.chem-ph2023★ 20 cited

Efficient implementation and performance analysis of the independent electron surface hopping method for dynamics at metal surfaces

James Gardner, Daniel Corken, Svenja M. Janke +2

Independent electron surface hopping (IESH) is a computational algorithm for simulating the mixed quantum-classical molecular dynamics of adsorbate atoms and molecules interacting…

physics.chem-ph2022★ 79 cited

High-throughput property-driven generative design of functional organic molecules

Julia Westermayr, Joe Gilkes, Rhyan Barrett +1

The design of molecules and materials with tailored properties is challenging, as candidate molecules must satisfy multiple competing requirements that are often difficult to measu…

physics.chem-ph2022★ 13 cited

Dissipative Tunneling Rates through the Incorporation of First-Principles Electronic Friction in Instanton Rate Theory II: Benchmarks and Applications

Y. Litman, E. S. Pós, C. L. Box +3

In part I, we presented the ring-polymer instanton with explicit friction (RPI-EF) method and showed how it can be connected to the \textit{ab initio} electronic friction formalism…

physics.chem-ph2022★ 14 cited

Dissipative Tunneling Rates through the Incorporation of First-Principles Electronic Friction in Instanton Rate Theory I: Theory

Y. Litman, E. S. Pós, C. L. Box +3

Reactions involving adsorbates on metallic surfaces and impurities in bulk metals are ubiquitous in a wide range of technological applications. The theoretical modelling of such re…

physics.chem-ph2022

NQCDynamics.jl: A Julia Package for Nonadiabatic Quantum Classical Molecular Dynamics in the Condensed Phase

James Gardner, Oscar A. Douglas-Gallardo, Wojciech G. Stark +4

Accurate and efficient methods to simulate nonadiabatic and quantum nuclear effects in high-dimensional and dissipative systems are crucial for the prediction of chemical dynamics…

physics.chem-ph2021★ 67 cited

Physically inspired deep learning of molecular excitations and photoemission spectra

Julia Westermayr, Reinhard J. Maurer

Modern functional materials consist of large molecular building blocks with significant chemical complexity which limits spectroscopic property prediction with accurate first-princ…

physics.chem-ph2021★ 203 cited

Perspective on integrating machine learning into computational chemistry and materials science

Julia Westermayr, Michael Gastegger, Kristof T. Schütt +1

Machine learning (ML) methods are being used in almost every conceivable area of electronic structure theory and molecular simulation. In particular, ML has become firmly establish…

physics.chem-ph2019★ 64 cited

Symmetry-Adapted High Dimensional Neural Network Representation of Electronic Friction Tensor of Adsorbates on Metals

Yaolong Zhang, Reinhard J. Maurer, Bin Jiang

Nonadiabatic effects in chemical reaction at metal surfaces, due to excitation of electron-hole pairs, stand at the frontier of the studies of gas-surface reaction dynamics. Howeve…

physics.chem-ph2019★ 19 cited

Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions

K. T. Schütt, M. Gastegger, A. Tkatchenko +2

Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fa…

physics.chem-ph2017★ 36 cited

Interpretation of X-ray Absorption Spectroscopy in the Presence of Surface Hybridization

Katharina Diller, Reinhard J. Maurer, Moritz Müller +1

X-ray absorption spectroscopy yields direct access to the electronic and geometric structure of hybrid inorganic-organic interfaces formed upon adsorption of complex molecules at m…

physics.chem-ph2015★ 28 cited

Interfacial charge rearrangement and intermolecular interactions: Density-functional theory study of free-base porphine adsorbed on Ag(111) and Cu(111)

Moritz Müller, Katharina Diller, Reinhard J. Maurer +1

We employ dispersion-corrected density-functional theory to study the adsorption of tetrapyrrole 2H-porphine (2H-P) at Cu(111) and Ag(111). Various contributions to adsorbate-subst…

physics.chem-ph2012★ 64 cited

Assessing computationally efficient isomerization dynamics: Delta-SCF density-functional theory study of azobenzene molecular switching

Reinhard J. Maurer, Karsten Reuter

We present a detailed comparison of the S0, S1 (n -> π*) and S2 (π-> π*) potential energy surfaces (PESs) of the prototypical molecular switch azobenzene as obtained by Delta-self-…