Scientific articles using the adaptive_sampling package

This page lists publications that have used the adaptive_sampling package. If you have used the package in your work, please consider adding your publication to this list by submitting a pull request on GitHub.

  • Combining Fast Exploration with Accurate Reweighting in the OPES-eABF Hybrid Sampling Method

    • Authors: Andreas Hulm, Robert P. Schiller, Christian Ochsenfeld

    • Journal: J. Chem. Theory Comput. 2025, 21, 13, 6434-6445

    • DOI: 10.1021/acs.jctc.5c00395

    • Abstract: We present a new hybrid sampling method that combines the fast exploration capabilities of the OPES method with the accurate reweighting of the eABF method. The method is implemented in the adaptive_sampling package and demonstrated on several test systems.

  • QM/MM free energy calculations of long-range biological protonation dynamics by adaptive and focused sampling

    • Authors: Maximilian C Pöverlein, Andreas Hulm, Johannes C. B. Dietschreit, Jörg Kussmann, Christian Ochsenfeld, Ville R. I. Kaila

    • Journal: J. Chem. Theory Comput. 2024, 20, 13, 5751-5762

    • DOI: 10.1021/acs.jctc.4c00199

    • Abstract: We present a new method for QM/MM free energy calculations of long-range biological protonation dynamics using adaptive and focused sampling techniques.

  • Exploring Chemical Space Using Ab Initio Hyperreactor Dynamics

    • Authors: Alexandra Stan-Bernhardt, Liubov Glinkina, Andreas Hulm, Christian Ochsenfeld

    • Journal: ACS Central Sci. 2024, 10, 2, 302-314

    • DOI: 10.1021/acscentsci.3c01403

    • Abstract: We present a new method for exploring chemical space using ab initio hyperreactor dynamics, which allows for efficient exploration of complex reaction networks.

  • Improved Sampling of Adaptive Path Collective Variables by Stabilized Extended-System Dynamics

    • Authors: Andreas Hulm, Christian Ochsenfeld

    • Journal: J. Chem. Theory Comput. 2023, 19, 24, 9202–9210

    • DOI: 10.1021/acs.jctc.3c00938

    • Abstract: We present a new method for the sampling of adaptive path collective variables based on stabilized extended-system dynamics, which allows for efficient exploration of complex reaction pathways.

  • Fully Automated Generation of Prebiotically Relevant Reaction Networks from Optimized Nanoreactor Simulations

    • Authors: Alexandra Stan, Beatriz von der Esch, Christian Ochsenfeld

    • Journal: J. Chem. Theory Comput. 2022, 18, 11, 6700-6712

    • DOI: 10.1021/acs.jctc.2c00754

    • Abstract: We present a fully automated method for the generation of prebiotically relevant reaction networks from optimized nanoreactor simulations, which allows for efficient exploration of complex reaction networks.

  • From free-energy profiles to activation free energies

    • Authors: Johannes C. B. Dietschreit, Dennis J. Diestler, Andreas Hulm, Christian Ochsenfeld, Rafael Gómez-Bombarelli

    • Journal: J. Chem. Phys. 2022, 157, 084113

    • DOI: 10.1063/5.0102075

    • Abstract: We present an exact expression for the calculation of the activation free energy from the potential of mean force (PMF).

  • Statistically optimal analysis of the extended-system adaptive biasing force (eABF) method

    • Authors: Andreas Hulm, Johannes C. B. Dietschreit, Christian Ochsenfeld

    • Journal: J. Chem. Phys. 2022, 157, 024110

    • DOI: 10.1063/5.0095554

    • Abstract: We present a new method for the statistically optimal analysis of the eABF method based on the MBAR estimator, which allows for accurate estimation of free energy profiles and reaction rates as well as other ensemble properties. The method is implemented in the adaptive_sampling package and demonstrated on several test systems.