AB
Albert P. Bartók
cond-mat.mtrl-sciphysics.chem-phphysics.comp-phcond-mat.stat-mechphysics.atom-phAsymmetryAtomistic modelsCell WallChemical shiftChemical shift anisotropy
On Valency
published · living versionsW_vmvfkhks·v2 · currentpublished
Comparing molecules and solids across structural and alchemical space
with Sandip De, Gábor Csányi, Michele Ceriotti
2 versions
W_8xs88vtr·v1published
W_f7cvwy93·v1published
Preprints & journals
57 papers in the corpus · 2005–2026A strategic roadmap for an atomistic machine-learning ecosystem2609.39090v2 · Jorg Behler, Michele Ceriotti, Cecilia Clementi et al.2026 · 0 citationsarXiv
Data-Driven Equation Discovery for Nonlinear Liquid Film Flows2606.13336v1 · Sebastian T. Dooley, Albert P. Bart'ok, James E. Sprittles et al.2026 · 0 citationsarXiv
How reproducible are first-principles simulations of liquid water?2605.28798v1 · Niamh ONeill, Benjamin X. Shi, William J. Baldwin et al.2026 · 1 citationarXiv
Vibrational infrared and Raman spectra of the methanol molecule with equivariant neural-network property surfaces.42093406 · Sunaga, Ayaki, Bartók, Albert P, Mátyus, Edit2026 · 1 citationPhysical chemistry chemical physics : PCCP. 2026;28(20):12299-12313
MuDirac 1.3.0: A Sustainable Software Tool for Calculating Ground State Nuclear Properties Using Muonic X-Ray Measurements2605.00554v1 · Leandro Liborio, Milan Kumar, Subindev Devadasan et al.2026 · 0 citationsarXiv
Regularity Priors for the Linear Atomic Cluster Expansion2601.15072v2 · James P. Darby, Joe D. Morrow, Albert P. Bart'ok et al.2026 · 0 citationsarXiv
Autonomous thermodynamically informed database generation for machine-learned interatomic potentials and application to magnesium.41567369 · Fletcher, Vincent G, Bartók, Albert P, Pártay, Livia B2026 · 3 citationsnpj computational materials. 2026;12(1):36
Multi-phase dataset for bulk Ti and the Ti-6Al-4V alloy.41350300 · Allen, Connor S, Bartók, Albert P2026 · 4 citationsScientific data. 2025;12(1):1925
Multi-Phase Dataset for Ti and Ti-6Al-4V2501.06116v1 · Connor S. Allen, Albert P. Bart'ok2025 · 0 citationsarXiv
Accurate predictions of chemical shifts with the rSCAN and r2SCAN mGGA exchange-correlation functionals.39291358 · Yates, Jonathan R, Bartók, Albert P2025 · 12 citationsFaraday discussions. 2025;255(0):192-202
Organic NMR crystallography: enabling progress for applications to pharmaceuticals and plant cell walls.39600178 · Rehman, Zainab, Lubay, Jairah, Franks, W Trent et al.2025 · 15 citationsFaraday discussions. 2025;255(0):222-243
Fine-tuning foundation models of materials interatomic potentials with frozen transfer learning.40689407 · Radova, Mariia, Stark, Wojciech G, Allen, Connor S et al.2026 · 62 citationsnpj computational materials. 2025;11(1):237
Kink-Helium Interactions in Tungsten: Increased Dislocation Mobility in the Infinitely Dilute Regime2406.08368v3 · Matthew Nutter, James R. Kermode, Albert P. Bart'ok2024 · 0 citationsarXiv
Experiment-Driven Atomistic Materials Modeling: A Case Study Combining X-Ray Photoelectron Spectroscopy and Machine Learning Potentials to Infer the Structure of Oxygen-Rich Amorphous Carbon.38749497 · Zarrouk, Tigany, Ibragimova, Rina, Bartók, Albert P et al.2024 · 39 citationsJournal of the American Chemical Society. 2024;146(21):14645-14659
Gaussian Approximation Potentials: theory, software implementation and application examples2310.03921v1 · Sascha Klawohn, G'abor Cs'anyi, James P. Darby et al.2023 · 81 citationsarXiv
A collinear-spin machine learned interatomic potential for FeCrNi alloy2309.08689v2 · Lakshmi Shenoy, Christopher D. Woodgate, Julie B. Staunton et al.2023 · 15 citationsPhys. Rev. Materials 8 (2024) 033804
Machine-learned acceleration for molecular dynamics in CASTEP.37497818 · Stenczel, Tamás K, El-Machachi, Zakariya, Liepuoniute, Guoda et al.2023 · 27 citationsThe Journal of chemical physics. 2023;159(4)
Comment on "Manifolds of quasi-constant SOAP and ACSF fingerprints and the resulting failure to machine learn four-body interactions" [J. Chem. Phys. 156, 034302 (2022)].36347686 · Pozdnyakov, Sergey N, Willatt, Michael J, Bartók, Albert P et al.2022 · 9 citationsThe Journal of chemical physics. 2022;157(17):177101
Optimal data generation for machine learned interatomic potentials2207.11828v1 · Connor Allen, Albert P. Bart'ok2022 · 10 citationsarXiv
Massively Parallel Fitting of Gaussian Approximation Potentials2207.03803v3 · Sascha Klawohn, James R. Kermode, Albert P. Bart'ok2022 · 4 citationsarXiv
Uncertainty quantification design principles for machine learning interatomic potentials: lessons learned from hierarchical Bayesian inference2206.08744v2 · Brennon L. Shanks, George Simmons, Albert P. Bart'ok et al.2022 · 5 citationsarXiv
Gaussian Process Regression for Materials and Molecules.34398616 · Deringer, Volker L, Bartók, Albert P, Bernstein, Noam et al.2022 · 1,227 citationsChemical reviews. 2021;121(16):10073-10141
Insight into Liquid Polymorphism from the Complex Phase Behavior of a Simple Model.34270313 · Bartók, Albert P, Hantal, György, Pártay, Livia B2021 · 12 citationsPhysical review letters. 2021;127(1):015701
Machine learning force fields based on local parametrization of dispersion interactions: Application to the phase diagram of C2105.02525v3 · Heikki Muhli, Xi Chen, Albert P. Bart'ok et al.2021 · 61 citationsPhys. Rev. B 104, 054106 (2021)
Incompleteness of Atomic Structure Representations.33124874 · Pozdnyakov, Sergey N, Willatt, Michael J, Bartók, Albert P et al.2020 · 197 citationsPhysical review letters. 2020;125(16):166001
Efficient prediction of nucleus independent chemical shifts for polycyclic aromatic hydrocarbons.32537616 · Kilymis, Dimitrios, Bartók, Albert P, Pickard, Chris J et al.2020 · 17 citationsPhysical chemistry chemical physics : PCCP. 2020;22(24):13746-13755
Combining phonon accuracy with high transferability in Gaussian approximation potential models2005.07046v1 · Janine George, Geoffroy Hautier, Albert P. Bart'ok et al.2020 · 43 citationsJ. Chem. Phys. 153, 044104 (2020)
Publisher's Note: "On the calculation of the bandgap of periodic solids with MGGA functionals using the total energy" [J. Chem. Phys. 151, 161102 (2019)].31837694 · Tran, Fabien, Doumont, Jan, Blaha, Peter et al.2020 · 0 citationsThe Journal of chemical physics. 2019;151(22):229901
Response to "Comment on 'Regularized SCAN functional'" [J. Chem. Phys. 151, 207101 (2019)].31779330 · Bartók, Albert P, Yates, Jonathan R2020 · 14 citationsThe Journal of chemical physics. 2019;151(20):207102
On the calculation of the bandgap of periodic solids with MGGA functionals using the total energy.31675851 · Tran, Fabien, Doumont, Jan, Blaha, Peter et al.2019 · 13 citationsThe Journal of chemical physics. 2019;151(16):161102
Regularized SCAN functional.31042928 · Bartók, Albert P, Yates, Jonathan R2019 · 291 citationsThe Journal of chemical physics. 2019;150(16):161101
Ultrasoft pseudopotentials with kinetic energy density support: implementing the modified Becke-Johnson potential1901.11301v2 · Albert P. Bart'ok, Jonathan R. Yates2019 · 24 citationsPhys. Rev. B 99, 235103 (2019)
Realistic Atomistic Structure of Amorphous Silicon from Machine-Learning-Driven Molecular Dynamics.29754489 · Deringer, Volker L, Bernstein, Noam, Bartók, Albert P et al.2018 · 264 citationsThe journal of physical chemistry letters. 2018;9(11):2879-2885
Machine learning a general purpose interatomic potential for silicon1805.01568v1 · Albert P. Bartok, James Kermode, Noam Bernstein et al.2018 · 472 citationsPhys. Rev. X 8, 041048 (2018)
Machine learning unifies the modeling of materials and molecules.29242828 · Bartók, Albert P, De, Sandip, Poelking, Carl et al.2019 · 762 citationsScience advances. 2017;3(12):e1701816
Tin chemical shift anisotropy in tin dioxide: On ambiguity of CSA asymmetry derived from MAS spectra.29202302 · Aliev, Abil E, Bartók, Albert P, Yates, Jonathan R2018 · 4 citationsSolid state nuclear magnetic resonance. 2018;89:1-10
Polytypism in the ground state structure of the Lennard-Jonesium.28707687 · Pártay, Lívia B, Ortner, Christoph, Bartók, Albert P et al.2018 · 29 citationsPhysical chemistry chemical physics : PCCP. 2017;19(29):19369-19376
Structural Simplicity as a Restraint on the Structure of Amorphous Silicon1609.00668v3 · Matthew J. Cliffe, Albert P. Bart'ok, Rachel N. Kerber et al.2016 · 22 citationsPhys. Rev. B 95, 224108 (2017)
Comparing molecules and solids across structural and alchemical space.27101873 · De, Sandip, Bartók, Albert P, Csányi, Gábor et al.2017 · 774 citationsPhysical chemistry chemical physics : PCCP. 2016;18(20):13754-69
Modeling Molecular Interactions in Water: From Pairwise to Many-Body Potential Energy Functions.27186804 · Cisneros, Gerardo Andrés, Wikfeldt, Kjartan Thor, Ojamäe, Lars et al.2017 · 440 citationsChemical reviews. 2016;116(13):7501-28
Determining pressure-temperature phase diagrams of materials1503.03404v3 · Robert J. N. Baldock, L'ivia B. P'artay, Albert P. Bart'ok et al.2015 · 68 citationsPhys. Rev. B 93, 174108 (2016)on Valency
Gaussian Approximation Potentials: a brief tutorial introduction1502.01366v2 · Albert P. Bart'ok, G'abor Cs'anyi2015 · 26 citationsarXiv
Analyzing the errors of DFT approximations for compressed water systems.25005274 · Alfè, D, Bartók, A P, Csányi, G et al.2015 · 55 citationsThe Journal of chemical physics. 2014;141(1):014104
Nested sampling for materials: the case of hard spheres.25353467 · Pártay, Lívia B, Bartók, Albert P, Csányi, Gábor2015 · 70 citationsPhysical review. E, Statistical, nonlinear, and soft matter physics. 2014;89(2):022302
First-principles energetics of water clusters and ice: a many-body analysis.24387379 · Gillan, M J, Alfè, D, Bartók, A P et al.2014 · 43 citationsThe Journal of chemical physics. 2013;139(24):244504
Communication: energy benchmarking with quantum Monte Carlo for water nano-droplets and bulk liquid water.23781773 · Alfè, D, Bartók, A P, Csányi, G et al.2014 · 42 citationsThe Journal of chemical physics. 2013;138(22):221102
First-principles energetics of water: a many-body analysis1303.0751v1 · M. J. Gillan, D. Alfe, A. P. Bart'ok et al.2013 · 1 citationarXiv
Machine learning for predictive condensed-phase simulation1302.5680v1 · Albert P. Bartok, Michael J. Gillan, Frederick R. Manby et al.2013 · 1 citationarXiv
On representing chemical environments1209.3140v3 · Albert P. Bart'ok, Risi Kondor, G'abor Cs'anyi2012 · 2,564 citationsarXivon Valency
Efficient sampling of atomic configurational spaces.20701382 · Pártay, Lívia B, Bartók, Albert P, Csányi, Gábor2010 · 149 citationsThe journal of physical chemistry. B. 2010;114(32):10502-12
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