Unified Approach for Molecular Dynamics and Density-Functional Theory

Self-Consistent Equations Including Exchange and Correlation Effects

Kohn, W., & Sham, L. J. (1965) · Physical Review · doi:10.1103/physrev.140.a1133 · Cited by 64,135

Self-interaction correction to density-functional approximations for many-electron systems

Perdew, J. P., & Zunger, A. (1981) · Physical Review B · doi:10.1103/physrevb.23.5048 · Cited by 20,887

Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set

Kresse, G., & Furthmüller, J. (1996) · Physical Review B · doi:10.1103/physrevb.54.11169 · Cited by 123,652

Projector augmented-wave method

Blöchl, P. E. (1994) · Physical Review B · doi:10.1103/physrevb.50.17953 · Cited by 92,732

From ultrasoft pseudopotentials to the projector augmented-wave method

Kresse, G., & Joubert, D. (1999) · Physical Review B · doi:10.1103/physrevb.59.1758 · Cited by 85,307

Soft self-consistent pseudopotentials in a generalized eigenvalue formalism

Vanderbilt, D. (1990) · Physical Review B · doi:10.1103/physrevb.41.7892 · Cited by 23,185

Computer Simulation of Liquids

Allen, M. P., & Tildesley, D. J. (2017) · doi:10.1093/oso/9780198803195.001.0001 · Cited by 20,945

LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales

Thompson, A. P., Aktulga, H. M., Berger, R., Bolintineanu, D. S., Brown, W. M., Crozier, P. S., in 't Veld, P. J., Kohlmeyer, A., Moore, S. G., Nguyen, T. D., et al. (2022) · Computer Physics Communications · doi:10.1016/j.cpc.2021.108171 · Cited by 12,598

Advanced capabilities for materials modelling with Q uantum ESPRESSO

Giannozzi, P., Andreussi, O., Brumme, T., Bunau, O., Buongiorno Nardelli, M., Calandra, M., Car, R., Cavazzoni, C., Ceresoli, D., Cococcioni, M., et al. (2017) · Journal of Physics: Condensed Matter · doi:10.1088/1361-648x/aa8f79 · Cited by 8,361

Cp2k: An electronic structure and molecular dynamics software package-quickstep: Efficient and accurate electronic structure calculations

Kühne, T. D., Iannuzzi, M., Del Ben, M., Rybkin, V. V., Seewald, P., Stein, F., Laino, T., Khaliullin, R. Z., Schütt, O., Schiffmann, F., et al. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0007045 · Cited by 4,468

Optimized norm-conserving Vanderbilt pseudopotentials

Hamann, D. R. (2013) · Physical Review B · doi:10.1103/physrevb.88.085117 · Cited by 3,379

Maximally localized Wannier functions: Theory and applications

Marzari, N., Mostofi, A. A., Yates, J. R., Souza, I., & Vanderbilt, D. (2012) · Reviews of Modern Physics · doi:10.1103/revmodphys.84.1419 · Cited by 3,283

The General Utility Lattice Program ( GULP )

Gale, J. D., & Rohl, A. L. (2003) · Molecular Simulation · doi:10.1080/0892702031000104887 · Cited by 2,265

Transport in Proton Conductors for Fuel-Cell Applications: Simulations, Elementary Reactions, and Phenomenology

Kreuer, K.-D., Paddison, S. J., Spohr, E., & Schuster, M. (2004) · Chemical Reviews · doi:10.1021/cr020715f · Cited by 2,187

T RANSITION P ATH S AMPLING : Throwing Ropes Over Rough Mountain Passes, in the Dark

Bolhuis, P. G., Chandler, D., Dellago, C., & Geissler, P. L. (2002) · Annual Review of Physical Chemistry · doi:10.1146/annurev.physchem.53.082301.113146 · Cited by 1,972

Structural properties of nanoclusters: Energetic, thermodynamic, and kinetic effects

Baletto, F., & Ferrando, R. (2005) · Reviews of Modern Physics · doi:10.1103/revmodphys.77.371 · Cited by 1,811

Metadynamics: a method to simulate rare events and reconstruct the free energy in biophysics, chemistry and material science

Laio, A., & Gervasio, F. L. (2008) · Reports on Progress in Physics · doi:10.1088/0034-4885/71/12/126601 · Cited by 1,619

Quantum Chemistry in the Age of Quantum Computing

Cao, Y., Romero, J., Olson, J. P., Degroote, M., Johnson, P. D., Kieferová, M., Kivlichan, I. D., Menke, T., Peropadre, B., Sawaya, N. P. D., et al. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00803 · Cited by 1,560

Interatomic Potentials from First-Principles Calculations: The Force-Matching Method

Ercolessi, F., & Adams, J. B. (1994) · Europhysics Letters (EPL) · doi:10.1209/0295-5075/26/8/005 · Cited by 1,455

Proton Transfer 200 Years after von Grotthuss: Insights from Ab Initio Simulations

Marx, D. (2006) · ChemPhysChem · doi:10.1002/cphc.200600128 · Cited by 920

Constructing high‐dimensional neural network potentials: A tutorial review

Behler, J. (2015) · International Journal of Quantum Chemistry · doi:10.1002/qua.24890 · Cited by 884

Calculation of effective interaction potentials from radial distribution functions: A reverse Monte Carlo approach

Lyubartsev, A. P., & Laaksonen, A. (1995) · Physical Review E · doi:10.1103/physreve.52.3730 · Cited by 852

Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems

Keith, J. A., Vassilev-Galindo, V., Cheng, B., Chmiela, S., Gastegger, M., Müller, K.-R., & Tkatchenko, A. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00107 · Cited by 849

Quantum Algorithms for Quantum Chemistry and Quantum Materials Science

Bauer, B., Bravyi, S., Motta, M., & Chan, G. K.-L. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00829 · Cited by 848

Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations

Behler, J. (2011) · Physical Chemistry Chemical Physics · doi:10.1039/c1cp21668f · Cited by 781

Recent Advances and Perspectives on Nonadiabatic Mixed Quantum–Classical Dynamics

Crespo-Otero, R., & Barbatti, M. (2018) · Chemical Reviews · doi:10.1021/acs.chemrev.7b00577 · Cited by 733

Machine learning unifies the modeling of materials and molecules

Bartók, A. P., De, S., Poelking, C., Bernstein, N., Kermode, J. R., Csányi, G., & Ceriotti, M. (2017) · Science Advances · doi:10.1126/sciadv.1701816 · Cited by 764

Heat transport in silicon from first-principles calculations

Esfarjani, K., Chen, G., & Stokes, H. T. (2011) · Physical Review B · doi:10.1103/physrevb.84.085204 · Cited by 759

Born-Oppenheimer molecular-dynamics simulations of finite systems: Structure and dynamics of ( H 2 O ) 2

Barnett, R. N., & Landman, U. (1993) · Physical Review B · doi:10.1103/physrevb.48.2081 · Cited by 629

Analysis of separable potentials

Gonze, X., Stumpf, R., & Scheffler, M. (1991) · Physical Review B · doi:10.1103/physrevb.44.8503 · Cited by 605

Revealing the role of interfacial water and key intermediates at ruthenium surfaces in the alkaline hydrogen evolution reaction

Chen, X., Wang, X.-T., Le, J.-B., Li, S.-M., Wang, X., Zhang, Y.-J., Radjenovic, P., Zhao, Y., Wang, Y.-H., Lin, X.-M., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41030-1 · Cited by 600

Assessing the Accuracy of Metadynamics

Laio, A., Rodriguez-Fortea, A., Gervasio, F. L., Ceccarelli, M., & Parrinello, M. (2005) · The Journal of Physical Chemistry B · doi:10.1021/jp045424k · Cited by 517

Rare-earth nickelates R NiO 3 : thin films and heterostructures

Catalano, S., Gibert, M., Fowlie, J., Íñiguez, J., Triscone, J.-M., & Kreisel, J. (2018) · Reports on Progress in Physics · doi:10.1088/1361-6633/aaa37a · Cited by 453

Microscopic Simulations of Electrochemical Double-Layer Capacitors

Jeanmairet, G., Rotenberg, B., & Salanne, M. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00925 · Cited by 303

Two Dimensional Ice Adsorbed on Mica Surface

Odelius, M., Bernasconi, M., & Parrinello, M. (1997) · Physical Review Letters · doi:10.1103/physrevlett.78.2855 · Cited by 299

Hydroxide diffuses slower than hydronium in water because its solvated structure inhibits correlated proton transfer

Chen, M., Zheng, L., Santra, B., Ko, H.-Y., DiStasio Jr, R. A., Klein, M. L., Car, R., & Wu, X. (2018) · Nature Chemistry · doi:10.1038/s41557-018-0010-2 · Cited by 283

The Properties of Water: Insights from Quantum Simulations

Paesani, F., & Voth, G. A. (2009) · The Journal of Physical Chemistry B · doi:10.1021/jp810590c · Cited by 256

Spectral gap optimization of order parameters for sampling complex molecular systems

Tiwary, P., & Berne, B. J. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1600917113 · Cited by 259

Fenton-like Chemistry in Water: Oxidation Catalysis by Fe(III) and H2O2

Ensing, B., Buda, F., & Baerends, E. J. (2003) · The Journal of Physical Chemistry A · doi:10.1021/jp0267149 · Cited by 216

Structure and Vibrations of Small Carbon Clusters from Coupled-Cluster Calculations

Martin, J. M. L., & Taylor, P. R. (1996) · The Journal of Physical Chemistry · doi:10.1021/jp952471r · Cited by 171

Recent Progress in Quantum Chemistry Modeling on the Pyrolysis Mechanisms of Lignocellulosic Biomass

Hu, B., Zhang, B., Xie, W.-L., Jiang, X.-Y., Liu, J., & Lu, Q. (2020) · Energy & Fuels · doi:10.1021/acs.energyfuels.0c01948 · Cited by 161

DPA-2: a large atomic model as a multi-task learner

Zhang, D., Liu, X., Zhang, X., Zhang, C., Cai, C., Bi, H., Du, Y., Qin, X., Peng, A., Huang, J., et al. (2023) · arXiv · doi:10.48550/arxiv.2312.15492 · Cited by 155

Polarizability of the nitrate anion and its solvation at the air/water interface

Salvador, P., Curtis, J. E., Tobias, D. J., & Jungwirth, P. (2003) · Physical Chemistry Chemical Physics · doi:10.1039/b304537d · Cited by 143

Structure and dynamics of the hydrated magnesium ion and of the solvated magnesium carbonates: insights from first principles simulations

Tommaso, D. D., & de Leeuw, N. H. (2010) · Phys. Chem. Chem. Phys. · doi:10.1039/b915329b · Cited by 139

Zinc complexation in chloride-rich hydrothermal fluids (25–600 °C): A thermodynamic model derived from ab initio molecular dynamics

Mei, Y., Sherman, D. M., Liu, W., Etschmann, B., Testemale, D., & Brugger, J. (2015) · Geochimica et Cosmochimica Acta · doi:10.1016/j.gca.2014.09.023 · Cited by 124

Exploiting Locality in Quantum Computation for Quantum Chemistry

McClean, J. R., Babbush, R., Love, P. J., & Aspuru-Guzik, A. (2014) · The Journal of Physical Chemistry Letters · doi:10.1021/jz501649m · Cited by 125

Fault-tolerant quantum simulations of chemistry in first quantization

Su, Y., Berry, D. W., Wiebe, N., Rubin, N., & Babbush, R. (2021) · PRX Quantum · doi:10.1103/prxquantum.2.040332 · Cited by 123

Frontiers of stable isotope geoscience

Eiler, J. M., Bergquist, B., Bourg, I., Cartigny, P., Farquhar, J., Gagnon, A., Guo, W., Halevy, I., Hofmann, A., Larson, T. E., et al. (2014) · Chemical Geology · doi:10.1016/j.chemgeo.2014.02.006 · Cited by 121

Water Formation on Pt and Pt‐based Alloys: A Theoretical Description of a Catalytic Reaction

Jacob, T., & Goddard, W. A. (2006) · ChemPhysChem · doi:10.1002/cphc.200500613 · Cited by 115

Quantum-Chemical Calculations of Carbon-Isotope Fractionation in CO2(g), Aqueous Carbonate Species, and Carbonate Minerals

Rustad, J. R., Nelmes, S. L., Jackson, V. E., & Dixon, D. A. (2008) · The Journal of Physical Chemistry A · doi:10.1021/jp076103m · Cited by 96

Mechanisms of Organocatalytic Amidation and Trans-Esterification of Aromatic Esters As a Model for the Depolymerization of Poly(ethylene) Terephthalate

Horn, H. W., Jones, G. O., Wei, D. S., Fukushima, K., Lecuyer, J. M., Coady, D. J., Hedrick, J. L., & Rice, J. E. (2012) · The Journal of Physical Chemistry A · doi:10.1021/jp304212y · Cited by 97

Ab initio molecular dynamics simulation and free energy exploration of copper(I) complexation by chloride and bisulfide in hydrothermal fluids

Mei, Y., Sherman, D. M., Liu, W., & Brugger, J. (2013) · Geochimica et Cosmochimica Acta · doi:10.1016/j.gca.2012.10.027 · Cited by 96

Biomolecular simulation and modelling: status, progress and prospects

van der Kamp, M. W., Shaw, K. E., Woods, C. J., & Mulholland, A. J. (2008) · Journal of The Royal Society Interface · doi:10.1098/rsif.2008.0105.focus · Cited by 90

Identification of the dominant photochemical pathways and mechanistic insights to the ultrafast ligand exchange of Fe(CO)5 to Fe(CO)4EtOH

Kunnus, K., Josefsson, I., Rajkovic, I., Schreck, S., Quevedo, W., Beye, M., Weniger, C., Grübel, S., Scholz, M., Nordlund, D., et al. (2016) · Structural Dynamics · doi:10.1063/1.4941602 · Cited by 60

A computational study of Mg2+ dehydration in aqueous solution in the presence of HS− and other monovalent anions – Insights to dolomite formation

Yang, Y., Sahai, N., Romanek, C. S., & Chakraborty, S. (2012) · Geochimica et Cosmochimica Acta · doi:10.1016/j.gca.2012.03.018 · Cited by 33

Reaction Mechanism for Direct Proton Transfer from Carbonic Acid to a Strong Base in Aqueous Solution I: Acid and Base Coordinate and Charge Dynamics

Daschakraborty, S., Kiefer, P. M., Miller, Y., Motro, Y., Pines, D., Pines, E., & Hynes, J. T. (2016) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.5b12742 · Cited by 30

RNA targeting and cleavage by the type III-Dv CRISPR effector complex

Schwartz, E. A., Bravo, J. P. K., Ahsan, M., Macias, L. A., McCafferty, C. L., Dangerfield, T. L., Walker, J. N., Brodbelt, J. S., Palermo, G., Fineran, P. C., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-47506-y · Cited by 30

DFT Study on the Effect of Water on the Carbonation of Portlandite

Funk, A., & Trettin, H. F. R. (2013) · Industrial & Engineering Chemistry Research · doi:10.1021/ie302972k · Cited by 29

‘Asynchronous reciprocal coupling of Martini 2.2 coarse-grained and CHARMM36 all-atom simulations in an automated multiscale framework’

López, C. A., Zhang, X., Aydin, F., Shrestha, R., Van, Q. N., Stanley, C. B., Carpenter, T. S., Nguyen, K., Patel, L. A., Chen, D., et al. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00168 · Cited by 18

A Rigorous Framework for Calculating Protein–Protein Binding Affinities in Membranes

Blazhynska, M., Gumbart, J. C., Chen, H., Tajkhorshid, E., Roux, B., & Chipot, C. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00941 · Cited by 22

Lyophobicity and slagging resistance mechanism of h-BN based coating for coal-fired boilers

Wang, J., Zhang, G., Li, F., & Chi, Z. (2019) · Fuel Processing Technology · doi:10.1016/j.fuproc.2019.02.012 · Cited by 15

First-principles simulation of photoreactions in biological systems

Rossle, S. (2009) · Frontiers in Bioscience · doi:10.2741/3574 · Cited by 9

Computational Studies of Prebiotic Chemistry at the Age of Machine Learning: From Recent Breakthroughs to Future Revolutions

Anton, O., & Stirnemann, G. (2026) · ChemSystemsChem · doi:10.1002/syst.202500057 · Cited by 4

Using Deep Graph Neural Networks Improves Physics-Based Hydration Free Energy Predictions Even for Molecules Outside of the Training Set Distribution

Elder, L. H., & Onufriev, A. V. (2025) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.5c02263 · Cited by 2

Reactive calcium carbonate precipitation from an atomic cluster expansion potential and enhanced sampling

Ibrahim, E., Lysogorskiy, Y., Drautz, R., & Piaggi, P. M. (2026) · arXiv · doi:10.48550/arxiv.2609.03044