GK
Georg Kresse
cond-mat.mtrl-sciphysics.chem-phcond-mat.str-elphysics.comp-phcond-mat.softcond-mat.othercond-mat.stat-mechadsorptionaggregate statesanatase
On Valency
published · living versionsW_6hs6zc7g·v1 · currentpublished
A direct view at excess electrons in TiO rutile and anatase
with Martin Setvin, Cesare Franchini, Xianfeng Hao, Michael Schmid +4
1 version
W_ddgtjprq·v1published
Preprints & journals
194 papers in the corpus · 1993–2026Dynamical properties of ab initio water from machine-learning potentials.42607172 · Montero de Hijes, P, Neubeck, L, Kresse, G et al.2026 · 0 citationsThe Journal of chemical physics. 2026;165(7)
VASP Plugins: Linking the Vienna ab-initio Simulation Package with Python2607.04622v1 · Sudarshan Vijay, Martijn Marsman, Georg Kresse et al.2026 · 0 citationsarXiv
Scalar machine learning of tensorial quantities-Born effective charges from monopole models.42335409 · Schmiedmayer, Bernhard, Rittsteuer, Angela, Hilpert, Tobias et al.2026 · 2 citationsThe Journal of chemical physics. 2026;164(24)
Extending SHARC to Periodic Systems: A SHARC–VASP Interface for First-Principles Nonadiabatic Dynamics10.26434/chemrxiv.15004801/v1 · Marco Romanelli, Michael Sahre, Georg Kresse et al.2026 · 1 citationChemRxiv
Excited States from Restricted Open Shell Plane-Wave DFT2605.28637v2 · Michael J. Sahre, Marco Romanelli, Martijn Marsman et al.2026 · 0 citationsarXiv
Accurate thermophysical properties of water using machine-learned potentials.42159333 · Hilpert, Tobias, Kresse, Georg2026 · 1 citationThe Journal of chemical physics. 2026;164(19)
Auxiliary field quantum Monte Carlo at the basis set limit: application to lattice constants2602.14923v1 · Moritz Humer, Martin Schlipf, Zoran Sukurma et al.2026 · 0 citationsarXiv
Equivariant machine learning of electric field gradients-Predicting the quadrupolar coupling constant in the MAPbI3 phase transition.41328969 · Schmiedmayer, Bernhard, Wolffs, Jop W, de Wijs, Gilles A et al.2025 · 5 citationsThe Journal of chemical physics. 2025;163(21)
Spin Frustration Determines the Stability and Reactivity of Metal-Organic Frameworks with Triangular Iron(III)-Oxo Clusters.40926383 · Lechner, Patrick, Ganguly, Gaurab, Sahre, Michael J et al.2025 · 2 citationsAngewandte Chemie (International ed. in English). 2025;64(41):e202514014
Constrained Random Phase Approximation: the spectral method2508.15368v3 · Merzuk Kaltak, Alexander Hampel, Martin Schlipf et al.2025 · 3 citationsPhys. Rev. B 112, 245102 (2024)
Evaluating First-Principles Electron-Phonon Couplings: Consistency Across Methods and Implementations2507.20585v1 · Konrad Merkel, Maximilian F. X. Dorfner, Manuel Engel et al.2025 · 0 citationsarXiv
Machine Learning Study of Surface Reconstructions of the CuO(111) Surface2507.05026v3 · Payal Wadhwa, Michael Schmid, Georg Kresse2025 · 1 citationPhys. Rev. B, 112, 205420, 2025
Correction: Absolute standard hydrogen electrode potential and redox potentials of atoms and molecules: machine learning aided first principles calculations.40406208 · Jinnouchi, Ryosuke, Karsai, Ferenc, Kresse, Georg2025 · 1 citationChemical science. 2025;16(22):10061-10062
Quantum Delocalization Enables Water Dissociation on Ru(0001).40408746 · Cao, Yu, Wang, Jiantao, Liu, Mingfeng et al.2025 · 7 citationsPhysical review letters. 2025;134(17):178001
Self-Refinement of Auxiliary-Field Quantum Monte Carlo via Non-Orthogonal Configuration Interaction.40294435 · Sukurma, Zoran, Schlipf, Martin, Kresse, Georg2025 · 7 citationsJournal of chemical theory and computation. 2025;21(9):4481-4493
Structure and Dynamics of the Magnetite(001)/Water Interface from Molecular Dynamics Simulations Based on a Neural Network Potential.39946686 · Romano, Salvatore, Montero de Hijes, Pablo, Meier, Matthias et al.2025 · 12 citationsJournal of chemical theory and computation. 2025;21(4):1951-1960
Exploring the accuracy of the equation-of-motion coupled-cluster band gap of solids2501.18667v1 · Evgeny Moerman, Henrique Miranda, Alejandro Gallo et al.2025 · 9 citationsarXiv
Author Correction: Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations.39848959 · Liu, Mingfeng, Wang, Jiantao, Hu, Junwei et al.2025 · 1 citationNature communications. 2025;16(1):969
Efficient periodic density functional theory calculations of charged molecules and surfaces using Coulomb kernel truncation2501.02435v1 · Sudarshan Vijay, Martin Schlipf, Henrique Miranda et al.2025 · 8 citationsarXiv
Absolute standard hydrogen electrode potential and redox potentials of atoms and molecules: machine learning aided first principles calculations.39776663 · Jinnouchi, Ryosuke, Karsai, Ferenc, Kresse, Georg2025 · 15 citationsChemical science. 2025;16(5):2335-2343
Density-based long-range electrostatic descriptors for machine learning force fields.39620413 · Faller, Carolin, Kaltak, Merzuk, Kresse, Georg2024 · 21 citationsThe Journal of chemical physics. 2024;161(21)
Automated Workflow for Accurate High-Throughput GW Calculations2410.15948v1 · Lorenzo Varrassi, Florian Ellinger, Espen Flage-Larsen et al.2024 · 0 citationsarXiv
Density isobar of water and melting temperature of ice: Assessing common density functionals.39360681 · Montero de Hijes, Pablo, Dellago, Christoph, Jinnouchi, Ryosuke et al.2024 · 40 citationsThe Journal of chemical physics. 2024;161(13)
Core-hole induced misalignment between Van-Hove singularities and K-edge fine structure in carbon nanotubes2409.17619v1 · Martin Unzog, Alexey Tal, Pedro Melo et al.2024 · 2 citationsarXiv
Stoichiometric reconstruction of the Al2O3(0001) surface.39265005 · Hütner, Johanna I, Conti, Andrea, Kugler, David et al.2024 · 71 citationsScience (New York, N.Y.). 2024;385(6714):1241-1244
Derivative learning of tensorial quantities-Predicting finite temperature infrared spectra from first principles.39171710 · Schmiedmayer, Bernhard, Kresse, Georg2024 · 21 citationsThe Journal of chemical physics. 2024;161(8)
Toward Large-Scale AFQMC Calculations: Large Time Step Auxiliary-Field Quantum Monte Carlo.38750634 · Sukurma, Zoran, Schlipf, Martin, Humer, Moritz et al.2024 · 5 citationsJournal of chemical theory and computation. 2024;20(10):4205-4217
Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations.38594273 · Liu, Mingfeng, Wang, Jiantao, Hu, Junwei et al.2025 · 38 citationsNature communications. 2024;15(1):3079
Comparing machine learning potentials for water: Kernel-based regression and Behler-Parrinello neural networks.38506284 · Montero de Hijes, Pablo, Dellago, Christoph, Jinnouchi, Ryosuke et al.2024 · 48 citationsThe Journal of chemical physics. 2024;160(11)
Towards Large-Scale AFQMC Calculations: Large Time Step Auxiliary-Field Quantum Monte Carlo2403.02542v1 · Zoran Sukurma, Martin Schlipf, Moritz Humer et al.2024 · 0 citationsarXiv
Machine Learning Density Functionals from the Random-Phase Approximation.37800677 · Riemelmoser, Stefan, Verdi, Carla, Kaltak, Merzuk et al.2023 · 24 citationsJournal of chemical theory and computation. 2023;19(20):7287-7299
Correction: New insights into the 1D carbon chain through the RPA.37740336 · Ramberger, Benjamin, Kresse, Georg2023 · 0 citationsPhysical chemistry chemical physics : PCCP. 2023;25(38):26396
Machine Learning-Aided First-Principles Calculations of Redox Potentials2309.13217v2 · Ryosuke Jinnouchi, Ferenc Karsai, Georg Kresse2023 · 36 citationsarXiv
Phaseless auxiliary field quantum Monte Carlo with projector-augmented wave method for solids.37493127 · Taheridehkordi, Amir, Schlipf, Martin, Sukurma, Zoran et al.2023 · 10 citationsThe Journal of chemical physics. 2023;159(4)
Benchmark Phaseless Auxiliary-Field Quantum Monte Carlo Method for Small Molecules.37470356 · Sukurma, Zoran, Schlipf, Martin, Humer, Moritz et al.2023 · 17 citationsJournal of chemical theory and computation. 2023;19(15):4921-4934
How to verify the precision of density-functional-theory implementations via reproducible and universal workflows2305.17274v1 · Emanuele Bosoni, Louis Beal, Marnik Bercx et al.2023 · 90 citationsNat. Rev. Phys. 6, 45-58 (2024)
Proton Transport in Perfluorinated Ionomer Simulated by Machine-Learned Interatomic Potential.37018477 · Jinnouchi, Ryosuke, Minami, Saori, Karsai, Ferenc et al.2023 · 25 citationsThe journal of physical chemistry letters. 2023;14(14):3581-3588
Combining Machine Learning and Many-Body Calculations: Coverage-Dependent Adsorption of CO on Rh(111).36867825 · Liu, Peitao, Wang, Jiantao, Avargues, Noah et al.2023 · 46 citationsPhysical review letters. 2023;130(7):078001
Approaching the basis-set limit of the dRPA correlation energy with explicitly correlated and projector augmented-wave methods.36414465 · Humer, Moritz, Harding, Michael E, Schlipf, Martin et al.2022 · 8 citationsThe Journal of chemical physics. 2022;157(19):194113
Quantum paraelectricity and structural phase transitions in strontium titanate beyond density-functional theory2211.09616v2 · Carla Verdi, Luigi Ranalli, Cesare Franchini et al.2022 · 56 citationsarXiv
Temperature-dependent anharmonic phonons in quantum paraelectric KTaO by first principles and machine-learned force fields2209.12036v1 · Luigi Ranalli, Carla Verdi, Lorenzo Monacelli et al.2022 · 34 citationsarXiv
Core-hole excitations using the projector augmented-wave method and the Bethe-Salpeter equation2206.11544v1 · Martin Unzog, Alexey Tal, Georg Kresse2022 · 0 citationsarXiv
Zero-point Renormalization of the Band Gap of Semiconductors and Insulators Using the PAW Method2205.04265v2 · Manuel Engel, Henrique Miranda, Laurent Chaput et al.2022 · 43 citationsarXiv
Thermal transport and phase transitions of zirconia by on-the-fly machine-learned interatomic potentials2109.15002v1 · Carla Verdi, Ferenc Karsai, Peitao Liu et al.2021 · 156 citationsnpj Comput. Mater. 7, 156 (2021)
Phase Transitions of Zirconia: Machine-Learned Force Fields Beyond Density Functional Theory2109.06282v1 · Peitao Liu, Carla Verdi, Ferenc Karsai et al.2021 · 62 citationsarXiv
Optical and excitonic properties of transition metal oxide perovskites by the Bethe-Salpeter equation2106.14632v1 · Lorenzo Varrassi, Peitao Liu, Zeynep Ergonenc Yavas et al.2021 · 24 citationsarXiv
Electronic State Unfolding for Plane Waves: Energy Bands, Fermi Surfaces, and Spectral Functions.34276866 · Dirnberger, David, Kresse, Georg, Franchini, Cesare et al.2021 · 27 citationsThe journal of physical chemistry. C, Nanomaterials and interfaces. 2021;125(23):12921-12928
New insights into the 1D carbon chain through the RPA.33629671 · Ramberger, Benjamin, Kresse, Georg2023 · 9 citationsPhysical chemistry chemical physics : PCCP. 2021;23(9):5254-5260
First-principles hydration free energies of oxygenated species at water-platinum interfaces.33685177 · Jinnouchi, Ryosuke, Karsai, Ferenc, Verdi, Carla et al.2021 · 24 citationsThe Journal of chemical physics. 2021;154(9):094107
- phase transition of zirconium predicted by on-the-fly machine-learned force field2012.04489v2 · Peitao Liu, Carla Verdi, Ferenc Karsai et al.2020 · 51 citationsPhys. Rev. Materials 5, 053804 (2021)
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