Publications

Montero de Hijes P, Neubeck L, Kresse G, Dellago C. Dynamical properties of ab initio water from machine-learning potentials. Journal of Chemical Physics. 2026 Aug 21;165(7):074502. doi: 10.48550/arXiv.2606.18163, 10.1063/5.0348453

Giannetti G, Pils J, Gräter F, Monego D, Dellago C. Introducing non-enzymatic crosslinks into atomistic simulations of collagen fibrils. Bioinformatics. 2026 Jul;42(7):btag409. doi: 10.1093/bioinformatics/btag409

Yang X, Reiner MM, Bachmair B, González L, Dietschreit JCB, Dellago C. Natps: Nonadiabatic Transition Path Sampling Using the Time-Reversible Mapping Approach to Surface Hopping. The Journal of Physical Chemistry Letters. 2026 May 28;17(21):6014-6023. Epub 2026 May 13. doi: 10.1021/acs.jpclett.6c00910

Montero de Hijes P, Falkner S, Dellago C. Non-Markovian dynamics in ice nucleation. Journal of Chemical Physics. 2026 Mar 7;164(9):094501. doi: 10.48550/arXiv.2512.01479, 10.1063/5.0314412

Montero de Hijes P, Shi K, Vega C, Dellago C. Comparing the Mechanical and Thermodynamic Definitions of Pressure in Ice Nucleation. Journal of Physical Chemistry Letters. 2026 Feb 26;17(8):2367-2373. doi: 10.48550/arXiv.2511.20129, 10.1021/acs.jpclett.5c03700

Jedlovszky P, Dellago C, Sega M. Hydrogen bond topology reveals layering of LDL-like and HDL-like water at its liquid/vapor interface. Journal of Chemical Physics. 2025 Jul 21;163(2):024511. doi: 10.48550/arXiv.2505.12953, 10.1063/5.0272802

Falkner S, Coretti A, Peters B, Bolhuis PG, Dellago C. Revisiting shooting point Monte Carlo methods for transition path sampling. Journal of Chemical Physics. 2025 Jul 21;163(3):034105. doi: 10.48550/arXiv.2408.03054, 10.1063/5.0261744

Eingang E, Dellago C, Sega M. Nuclear quantum effects at the liquid/vapor interface from neural-network based path integral molecular dynamics simulations. Journal of Chemical Physics. 2025 Jun 28;162(24):244709. doi: 10.1063/5.0268072

Coretti A, Falkner S, Geissler PL, Dellago C. Learning mappings between equilibrium states of liquid systems using normalizing flows. Journal of Chemical Physics. 2025 May 7;162(18):184102. doi: 10.48550/arXiv.2208.10420, 10.1063/5.0253034

Speckmann C, Angeletti A, Kývala L, Lamprecht D, Herterich F, Mangler C et al. Electron-Beam-Induced Adatom-Vacancy-Complexes in Mono- and Bilayer Phosphorene. Advanced Materials Interfaces. 2025 May 5;12(9):2400784. Epub 2024 Dec 13. doi: 10.48550/arXiv.2409.11102, 10.1002/admi.202400784

Kocer E, Singraber A, Finkler JA, Misof P, Ko TW, Dellago C et al. Iterative charge equilibration for fourth-generation high-dimensional neural network potentials. Journal of Chemical Physics. 2025 Mar 21;162(12):124106. doi: 10.48550/arXiv.2502.07907, 10.1063/5.0252566

Gorfer A, Abart R, Dellago C. Mechanism and kinetics of sodium diffusion in Na-feldspar from neural network based atomistic simulations. Acta Materialia. 2025 Mar 1;286:120657. doi: 10.1016/j.actamat.2024.120657

Kývala L, Montero de Hijes P, Dellago C. Unsupervised identification of crystal defects from atomistic potential descriptors. npj Computational Materials. 2025 Feb 27;11(1):50. doi: 10.48550/arXiv.2405.01320, 10.1038/s41524-025-01544-2

Romano S, Montero de Hijes P, Meier M, Kresse G, Franchini C, Dellago C. Structure and Dynamics of the Magnetite(001)/Water Interface from Molecular Dynamics Simulations Based on a Neural Network Potential. Journal of Chemical Theory and Computation. 2025 Feb 25;21(4):1951-1960. doi: 10.48550/arXiv.2408.11538, 10.1021/acs.jctc.4c01507

Montero de Hijes P, Dellago C, Jinnouchi R, Kresse G. Density isobar of water and melting temperature of ice: Assessing common density functionals. Journal of Chemical Physics. 2024 Oct 7;161(13):131102 . doi: 10.1063/5.0227514

Gorfer A, Abart R, Dellago C. Structure and thermodynamics of defects in Na-feldspar from a neural network potential. Physical Review Materials. 2024 Jul;8(7):073602. doi: 10.48550/arXiv.2402.14640, 10.1103/PhysRevMaterials.8.073602

Omranpour A, Montero De Hijes P, Behler J, Dellago C. Perspective: Atomistic simulations of water and aqueous systems with machine learning potentials. Journal of Chemical Physics. 2024 May 7;160(17):170901. doi: 10.48550/arXiv.2401.17875, 10.1063/5.0201241

Falkner S, Coretti A, Dellago C. Enhanced Sampling of Configuration and Path Space in a Generalized Ensemble by Shooting Point Exchange. Physical Review Letters. 2024 Mar 22;132(12):128001. doi: 10.48550/arXiv.2302.08757, 10.1103/PhysRevLett.132.128001

Montero de Hijes P, Dellago C, Jinnouchi R, Schmiedmayer B, Kresse G. Comparing machine learning potentials for water: Kernel-based regression and Behler-Parrinello neural networks. Journal of Chemical Physics. 2024 Mar 21;160(11):114107. doi: 10.1063/5.0197105

Coretti A, Falkner S, Weinreich J, Dellago C, von Lilienfeld-Toal OA. Boltzmann Generators and the New Frontier of Computational Sampling in Many-Body Systems. KIM Review. 2024;2:3. doi: 10.25950/bfa99422