Supplementary material for 'Predicting and rationalizing the Soret coefficient of binary Lennard-Jones mixtures in the liquid state' (doi:10.18419/darus-2996)

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Supplementary material for 'Predicting and rationalizing the Soret coefficient of binary Lennard-Jones mixtures in the liquid state'

doi:10.18419/darus-2996

DaRUS

2022-08-03

2

Zimmermann, Nils Edvin Richard; Guevara-Carrion, Gabriela; Vrabec, Jadran; Hansen, Niels, 2022, "Supplementary material for 'Predicting and rationalizing the Soret coefficient of binary Lennard-Jones mixtures in the liquid state'", https://doi.org/10.18419/darus-2996, DaRUS, V2

Supplementary material for 'Predicting and rationalizing the Soret coefficient of binary Lennard-Jones mixtures in the liquid state'

doi:10.18419/darus-2996

Zimmermann, Nils Edvin Richard (Universität Stuttgart)

Guevara-Carrion, Gabriela (Technische Universität Berlin)

Vrabec, Jadran (Technische Universität Berlin)

Hansen, Niels (Universität Stuttgart)

EXC 2075 - 390740016

INST 37/935-1 FUGG

VR 6/11

DaRUS

Zimmermann, Nils Edvin Richard

Zimmermann, Nils Edvin Richard

2022-06-22

https://doi.org/10.18419/darus-2996

Chemistry, Engineering, Physics, Molecular Simulation, Molecular Dynamics Simulation, Non-Equilibrium Statistical Mechanics, Statistical Mechanics, Mathematical Model, Lennard-Jones Potential, Thermophoresis, Green-Kubo Relations, Mixture, Liquid

Theoretical Chemistry, Physical Chemistry, Chemical Physics

<p>Supplementary material for 'Predicting and rationalizing the Soret coefficient of binary Lennard-Jones mixtures in the liquid state' (N. E. R. Zimmermann, G. Guevara-Carrion, J. Vrabec, N. Hansen, Adv. Theory Simul., 2022) containing scripts, packages, and files to re-create and to submit LAMMPS simulations performed for non-equilibrium molecular dynamics (NEMD) simulations and to post-process these simulations to obtain the final results. Furthermore, scripts are provided to calculate Soret coefficients with the Shukla-Firoozabadi model (Ind. Eng. Chem. Res., 1998, 37, 8, 3331) and the Reith-Müller-Plathe model (J. Chem. Phys., 2000, 112, 5, 2436). Finally, all data from the present study are provided, where as much of the raw data of the NEMD simulations are provided as reasonably possible (e.g., trajectory files could not be included due to memory constraints, but temperature profiles and mole fraction profiles are provided in tar archives).</p> <p>Note that each directory of this dataset contains a README.txt to outline the content found in the directory and, possibly, its subdirectories.</p> <p>The general directory structure is as follows:</p> <pre> | |- code | | | |- nemd | | | |- reith | | | '- shukla | '- data | | | |- emd | | | |- nemd | | | |- reith | | | '- shukla | '- movie | '- nemd </pre>

N. E. R. Zimmermann, G. Guevara-Carrion, J. Vrabec, N. Hansen, Predicting and Rationalizing the Soret Coefficient of Binary Lennard-Jones Mixtures in the Liquid State, Advanced Theory and Simulations, 2022.

10.1002/adts.202200311

N. E. R. Zimmermann, G. Guevara-Carrion, J. Vrabec, N. Hansen, Predicting and Rationalizing the Soret Coefficient of Binary Lennard-Jones Mixtures in the Liquid State, Advanced Theory and Simulations, 2022.

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analyze_lj_emd_equil.py

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analyze_lj_nemd.py

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analyze_lj_nemd_campaign.py

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average_soret_data.py

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calculate_soret_data_one_simulation.py

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create_configs.bash

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gen_lj_systems.py

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gen_temp_conc_prof.py

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interpolate_soret_data.py

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prep_emd_equil.py

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prep_nemd.py

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README.txt

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README.md

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storage.py

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lammps.py

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color.py

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files.py

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math.py

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slurm.py

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units.py

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settings_vtk.json

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vtk.py

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predict_ST.py

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calc_shukla.py

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invlbox_gamma.dat

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invlbox_L11_LE1.dat

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extra_temp_molfrac_soret_temp_1_rho_0.8.dat

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tdamp_vs_selfdiff_temp_paramset2_temp0.75_press0.09.dat

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inter_temp_molfrac_soret_temp_0.75_press_0.09.dat

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extra_temp_molfrac_soret_temp_0.85_rho_0.81.dat

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inter_temp_molfrac_soret_temp_0.931_rho_0.81.dat

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reith.dat

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input_data_for_thermo_models_energies.dat

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input_data_for_thermo_models_enthalpies.dat

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shukla_energies.dat

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nemd_english.mp4

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nemd_german.mp4

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