Transferable force fields and transport properties

PN 3-8

Project description

Classical transferable force fields allow predicting physical properties and microscopic processes of pure substances and mixtures. The development of force fields, especially the parametrization of the ‘non-bonded’ interactions, requires multidimensional optimization with computationally expensive (and noisy) objective function evaluations through Monte Carlo (MC) and molecular dynamics (MD) simulations. This is demanding because force-field parameters are highly correlated. We use physically-based surrogate models to drastically accelerate the optimization procedure and specifically propose new reduced order models for transport properties based on entropy scaling. Transport properties, such as viscosity, thermal conductivity, and self-diffusion coefficients, can then be considered in the optimization of force fields simultaneously with static properties, which was not possible before. Machine-learned models for transport properties will be developed with an increasing data-base of simulated force field parameters and substances.

Project information

Project title Transferable force fields and transport properties
Project leaders Niels Hansen, Joachim Groß
Project partners Jürgen Pleiss
Christian Holm
Project duration February 2020 - June 2023
Project number PN 3-8

Publications PN 3-8 and PN 3-8 (II)

  1. 2025

    1. M. B. M. Spera, S. Darouich, J. Pleiss, and N. Hansen, “Influence of water content on thermophysical properties of aqueous glyceline solutions predicted by molecular dynamics simulations,” Fluid Phase Equilibria, vol. 592, p. 114324, 2025, doi: https://doi.org/10.1016/j.fluid.2024.114324.
    2. M. Fleck, R. Katsuta, T. Esper, N. Hansen, and J. Gross, “Gaussian Process-Supported Optimization of the Transferable Anisotropic Mie Potential Force Field for Primary Alkylamines misc,” Industrial & Engineering Chemistry Research, vol. 64, Art. no. 11, Mar. 2025, doi: 10.1021/acs.iecr.4c04170.

  2. 2024

    1. M. Fleck, S. Darouich, N. Hansen, and J. Gross, “TAMie Force Field for Alkanethiols: Multifidelity Gaussian Processes for Dealing with Scarce Experimental Data,” The Journal of Physical Chemistry B, vol. 128, Art. no. 39, Sep. 2024, doi: 10.1021/acs.jpcb.4c04456.
    2. M. Fleck, S. Darouich, N. Hansen, and J. Gross, “Transferable Anisotropic Mie Potential Force Field for Alkanediols,” The Journal of Physical Chemistry B, vol. 128, Art. no. 19, May 2024, doi: 10.1021/acs.jpcb.4c00962.
    3. M. Pechlaner, W. F. van Gunsteren, L. J. Smith, B. Stankiewicz, L. N. Wirz, and N. Hansen, “Molecular Structure Refinement Based on Residual Dipolar Couplings: A Comparison of the Molecular Rotational-Sampling Method with the Alignment-Tensor Approach,” Journal of Chemical Information and Modeling, vol. 64, Art. no. 12, Jun. 2024, doi: 10.1021/acs.jcim.4c00416.
    4. A. Schneider, T. B. Lystbæk, D. Markthaler, N. Hansen, and B. Hauer, “Biocatalytic stereocontrolled head-to-tail cyclizations of unbiased terpenes as a tool in chemoenzymatic synthesis,” Nature Communications, vol. 15, Art. no. 1, Jun. 2024, doi: 10.1038/s41467-024-48993-9.
    5. B. Bursik, R. Stierle, A. Schlaich, P. Rehner, and J. Gross, “Viscosities of inhomogeneous systems from generalized entropy scaling,” Physics of Fluids, vol. 36, Art. no. 4, Apr. 2024, doi: 10.1063/5.0189902.
    6. M. Pechlaner, W. F. van Gunsteren, L. J. Smith, and N. Hansen, “Molecular structure refinement based on residual dipolar couplings using magnetic-field rotational sampling,” The Journal of Chemical Physics, vol. 161, Art. no. 4, Jul. 2024, doi: 10.1063/5.0203153.
    7. M. Fleck, W. A. Kopp, N. Viswanathan, N. Hansen, J. Gross, and K. Leonhard, “Efficient Generation of Torsional Energy Profiles by Multifidelity Gaussian Processes for Hindered Rotor Corrections,” Journal of Chemical Theory and Computation, vol. 20, Art. no. 17, Aug. 2024, doi: 10.1021/acs.jctc.4c00475.
    8. L. Grunenberg et al., “Probing Self-Diffusion of Guest Molecules in a Covalent Organic Framework: Simulation and Experiment,” ACS Nano, vol. 18, Art. no. 25, Jun. 2024, doi: 10.1021/acsnano.3c12167.
    9. M. Fleck, J. Gross, and N. Hansen, “Multifidelity Gaussian Processes for Predicting Shear Viscosity over Wide Ranges of Liquid State Points Based on Molecular Dynamics Simulations,” Industrial & Engineering Chemistry Research, vol. 63, Art. no. 8, 2024, doi: 10.1021/acs.iecr.3c03931.
    10. R. Stierle, G. Bauer, N. Thiele, B. Bursik, P. Rehner, and J. Gross, “Classical density functional theory in three dimensions with GPU-accelerated automatic differentiation: Computational performance analysis using the example of adsorption in covalent-organic frameworks,” Chemical Engineering Science, vol. 298, p. 120380, Oct. 2024, doi: 10.1016/j.ces.2024.120380.
    11. F. Mayer et al., “Computer-aided molecular refrigerant design for adsorption chillers based on classical density functional theory and PC-SAFT,” Computers & Chemical Engineering, vol. 184, p. 108629, May 2024, doi: 10.1016/j.compchemeng.2024.108629.

  3. 2023

    1. L. Neumaier, D. Roskosch, J. Schilling, G. Bauer, J. Gross, and A. Bardow, “Refrigerant Selection for Heat Pumps: The Compressor Makes the Difference,” Energy Technology, Feb. 2023, doi: 10.1002/ente.202201403.
    2. P. Rehner, A. Bardow, and J. Gross, “Modeling Mixtures with PCP-SAFT: Insights from Large-Scale Parametrization and Group-Contribution Method for Binary Interaction Parameters,” International Journal of Thermophysics, vol. 44, Art. no. 12, 2023.
    3. A. Reimer, T. v. Westen, and J. Groß, “Physically based equation of state for Mie ν-6 fluids,” The journal of chemical physics, vol. 158, Art. no. 16, 2023, doi: 10.1063/5.0141856.
    4. T. Braun, R. Stierle, M. Fischer, and J. Gross, “Investigating Learning and Improving Teaching in Engineering Thermodynamics Guided by Constructive Alignment and Competency Modeling: Part II. Assessment and Exam Design,” Chemical Engineering Education, vol. 57, Art. no. 3, 2023, doi: 10.18260/2-1-370.660-133030.
    5. I. Nitzke, R. Stierle, S. Stephan, M. Pfitzner, J. Gross, and J. Vrabec, “Phase equilibria and interface properties of hydrocarbon propellant-oxygen mixtures in the transcritical regime,” Physics of Fluids, vol. 35, Art. no. 3, 2023, doi: 10.1063/5.0138973.
    6. M. Hammer, G. Bauer, R. Stierle, J. Groß, and Ø. Wilhelmsen, “Classical density functional theory for interfacial properties of hydrogen, helium, deuterium, neon, and their mixtures,” The Journal of Chemical Physics, vol. 158, Art. no. 10, 2023, doi: 10.1063/5.0137226.
    7. R. Stierle, M. Fischer, T. Braun, and J. Gross, “Investigating Learning and Improving Teaching in Engineering Thermodynamics Guided by Constructive Alignment and Competency Modeling: Part I. Improving Our Learning Environment - How We Support Student Learning,” Chemical Engineering Education, vol. 57, Art. no. 2, 2023, doi: 10.18260/2-1-370.660-126287.
    8. C. Steinhausen et al., “Characterisation of the transient mixing behaviour of evaporating near-critical droplets,” Frontiers in Physics, vol. 11, 2023, doi: 10.3389/fphy.2023.1192416.

  4. 2022

    1. M. Pechlaner, W. F. van Gunsteren, N. Hansen, and L. J. Smith, “Molecular dynamics simulation or structure refinement of proteins: are solvent molecules required? A case study using hen lysozyme,” European Biophysics Journal, vol. 51, Art. no. 3, Apr. 2022, doi: 10.1007/s00249-022-01593-1.
    2. W. F. van Gunsteren, M. Pechlaner, L. J. Smith, B. Stankiewicz, and N. Hansen, “A Method to Derive Structural Information on Molecules from Residual Dipolar Coupling NMR Data,” The Journal of Physical Chemistry B, vol. 126, Art. no. 21, May 2022, doi: 10.1021/acs.jpcb.2c02410.
    3. J. Eller, T. Sauerborn, B. Becker, I. Buntic, J. Gross, and R. Helmig, “Modeling Subsurface Hydrogen Storage With Transport Properties From Entropy Scaling Using the PC‐SAFT Equation of State,” Water Resources Research, vol. 58, Art. no. 4, 2022, doi: 10.1029/2021wr030885.
    4. N. E. R. Zimmermann, G. Guevara-Carrion, J. Vrabec, and N. Hansen, “Predicting and Rationalizing the Soret Coefficient of Binary Lennard-Jones Mixtures in the Liquid State,” Advanced Theory and Simulations, vol. 5, Art. no. 11, Jul. 2022, doi: 10.1002/adts.202200311.
    5. L. Neumaier, J. Schilling, A. Bardow, and J. Gross, “Dielectric constant of mixed solvents based on perturbation theory,” Fluid Phase Equilibria, vol. 555, p. 113346, Apr. 2022, doi: 10.1016/j.fluid.2021.113346.
    6. T. van Westen, M. Hammer, B. Hafskjold, A. Aasen, J. Gross, and Ø. Wilhelmsen, “Perturbation theories for fluids with short-ranged attractive forces: A case study of the Lennard-Jones spline fluid,” The Journal of Chemical Physics, vol. 156, Art. no. 10, Mar. 2022, doi: 10.1063/5.0082690.
    7. D. Markthaler, H. Kraus, and N. Hansen, “Binding free energies for the SAMPL8 CB8 “Drugs of Abuse” challenge from umbrella sampling combined with Hamiltonian replica exchange,” Journal of Computer-Aided Molecular Design, vol. 36, pp. 1–9, 2022, doi: 10.1007/s10822-021-00439-w.
    8. D. Markthaler, M. Fleck, B. Stankiewicz, and N. Hansen, “Exploring the Effect of Enhanced Sampling on Protein Stability Prediction,” Journal of Chemical Theory and Computation, vol. 18, Art. no. 4, Mar. 2022, doi: 10.1021/acs.jctc.1c01012.
    9. P. Rehner, T. van Westen, and J. Gross, “Equation of state and Helmholtz energy functional for fused heterosegmented hard chains,” Physical Review E, Mar. 2022, doi: 10.1103/PhysRevE.105.034110.
    10. C. Kessler et al., “Influence of layer slipping on adsorption of light gases in covalent organic frameworks: A combined experimental and computational study,” Microporous and Mesoporous Materials, vol. 336, p. 111796, May 2022, doi: 10.1016/j.micromeso.2022.111796.

  5. 2021

    1. J. Schilling, M. Hopp, J. Gross, and A. Bardow, “Tailor-made solvents by integrated design of molecules and CO<sub>2</sub> absorption processes,” Computer Aided Chemical Engineering, vol. 50, pp. 197–202, 2021.
    2. L. J. Smith, W. F. van Gunsteren, B. Stankiewicz, and N. Hansen, “On the use of 3J-coupling NMR data to derive structural information on proteins,” Journal of Biomolecular NMR, vol. 75, Art. no. 1, Jan. 2021, doi: 10.1007/s10858-020-00355-5.
    3. J. Schilling, M. Entrup, M. Hopp, J. Gross, and A. Bardow, “Towards optimal mixtures of working fluids:Integrated design of processes and mixtures for Organic Rankine Cycles,” Renewable and Sustainable Energy Reviews, vol. 135, 2021.
    4. J. Eller and J. Gross, “Free-Energy-Averaged Potentials for Adsorption in Heterogeneous Slit Pores Using PC-SAFT Classical Density Functional Theory,” Langmuir, vol. 37, Art. no. 12, Mar. 2021, doi: 10.1021/acs.langmuir.0c03287.
    5. R. Stierle and J. Gross, “Hydrodynamic density functional theory for mixtures from a variational principle and its application to droplet coalescence,” The Journal of Chemical Physics, Oct. 2021, doi: 10.1063/5.0060088.
    6. D. Markthaler and N. Hansen, “Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B,” Data in Brief, vol. 39, p. 107618, Dec. 2021, doi: 10.1016/j.dib.2021.107618.
    7. T. van Westen and J. Gross, “Accurate first-order perturbation theory for fluids: uf-theory,” The Journal of Chemical Physics, Jan. 2021, doi: 10.1063/5.0031545.
    8. T. van Westen and J. Gross, “Accurate thermodynamics of simple fluids and chain fluids based on first-order perturbation theory and second virial coefficients: uv-theory,” The Journal of Chemical Physics, Dec. 2021, doi: 10.1063/5.0073572.
    9. C. Keßler, J. Eller, J. Groß, and N. Hansen, “Adsorption of light gases in covalent organic frameworks : comparison of classical density functional theory and grand canonical Monte Carlo simulations,” Microporous and mesoporous materials, vol. 324, Art. no. September, 2021, doi: 10.1016/j.micromeso.2021.111263.
    10. L. J. Smith, W. F. Gunsteren, and N. Hansen, “On the Use of Side-Chain NMR Relaxation Data to Derive Structural and Dynamical Information on Proteins: A Case Study Using Hen Lysozyme,” ChemBioChem, vol. 22, Art. no. 6, Dec. 2021, doi: 10.1002/cbic.202000674.
    11. P. Rehner, B. Bursik, and J. Gross, “Surfactant Modeling Using Classical Density Functional Theory and a Group Contribution PC-SAFT Approach,” Industrial & Engineering Chemistry Research, vol. 60, Art. no. 19, Apr. 2021, doi: 10.1021/acs.iecr.1c00169.
    12. J. Eller, T. Matzerath, T. van Westen, and J. Gross, “Predicting solvation free energies in non-polar solvents using classical density functional theory based on the PC-SAFT equation of state,” The Journal of Chemical Physics, Jun. 2021, doi: 10.1063/5.0051201.

  6. 2020

    1. G. Lamanna et al., “Laboratory Experiments of High-Pressure Fluid Drops,” in High-Pressure Flows for Propulsion Applications, American Institute of Aeronautics and Astronautics, Inc., 2020, pp. 49–109. doi: 10.2514/5.9781624105814.0049.0110.
    2. N. Hansen et al., “A Suite of Advanced Tutorials for the GROMOS Biomolecular Simulation Software Article v1.0,” Living Journal of Computational Molecular Science, vol. 2, Art. no. 1, 2020, doi: 10.33011/livecoms.2.1.18552.
    3. M. Fischer, G. Bauer, and J. Gross, “Force Fields with Fixed Bond Lengths and with Flexible Bond Lengths: Comparing Static and Dynamic Fluid Properties,” Journal of Chemical & Engineering Data, vol. 65, Art. no. 4, Feb. 2020, doi: 10.1021/acs.jced.9b01031.
    4. R. Stierle, C. Waibel, J. Gross, C. Steinhausen, B. Weigand, and G. Lamanna, “On the Selection of Boundary Conditions for Droplet Evaporation and Condensation at high Pressure and Temperature Conditions from interfacial Transport Resistivities,” International Journal of Heat and Mass Transfer, vol. 151, p. 119450, Apr. 2020, doi: 10.1016/j.ijheatmasstransfer.2020.119450.
    5. R. Stierle and J. Gross, “A fast inverse Hankel Transform of first Order for computing vector-valued weight Functions appearing in Fundamental Measure Theory in cylindrical Coordinates,” Fluid Phase Equilibria, vol. 511, p. 112500, May 2020, doi: 10.1016/j.fluid.2020.112500.
    6. J. Gebhardt, M. Kiesel, S. Riniker, and N. Hansen, “Combining Molecular Dynamics and Machine Learning to Predict Self-Solvation Free Energies and Limiting Activity Coefficients,” Journal of Chemical Information and Modeling, vol. 60, Art. no. 11, Aug. 2020, doi: 10.1021/acs.jcim.0c00479.
    7. M. Theiss and J. Gross, “Nonprimitive Model Electrolyte Solutions: Comprehensive Data from Monte Carlo Simulations,” Journal of Chemical & Engineering Data, vol. 65, Art. no. 2, Jan. 2020, doi: 10.1021/acs.jced.9b00855.

Data and software publications PN 3-8 and PN 3-8 (II)

  1. C. Keßler et al., “Supplementary material for ‘Influence of Layer Slipping on Adsorption of Light Gases in Covalent Organic Frameworks: A Combined Experimental and Computational Study.’” 2022. doi: 10.18419/darus-2308.
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