Vibrational Excitation in Plasma Catalysis: How Important are Dynamical Effects?

This record contains the results for the MD trajectories and its analysis described in the article "Vibrational Excitation in Plasma Catalysis: How Important are Dynamical Effects?" (EES Catalysis, 2025, DOI: 10.1039/D5EY00132C).It contains input configurations and of all trajectories as well as summaries of their results, as well as the plot scripts and data of all figures in the article and supporting information. Description per file: README.md - This file.requirements.txt - Python dependencies for (plot) scripts.makefile - Makefile to produce/remove figure and plotdata. Folder 'input' N2_state_thermal.dat - File containing the initial conditions for the quasi-classical trajectories. Only the diatom coordinates u, v, alpha, beta, gamma, phi are equal to actual inputs.Ru0001_3x3x7_575K.xyz - XYZ file of 100 Ru(0001) geometries for a 3 by 3 surface cell with 7 layers, sampled from NVT ensemble at 575 Kelvin. HDNNP - Folder containing input file for RuNNer/N2P2 neural network potential. Folder 'data' Contains the data from the quasi-classical trajectories. Folder 'data/adiabatic' Contains data for adiabatic trajectories: NVE ensemble without electronic friction. Folders 'data/adiabatic/nu=[0-10]' 0_sticking_probabililty.dat - Computed mean sticking probabilities and 95% confidence interval per incidence energy.E=XXXX-10000(0).dat - Results from 10000(0) trajectories at incidence energy E=XXXX eV. Folder 'data/ldfa' Contains data for adiabatic trajectories: NVE ensemble with electronic friction. Folders 'data/ldfa/nu=[0-10]' E=XXXX-10000(0).dat - Results from 10000(0) trajectories at incidence energy E=XXXX eV. Folder 'scripts' mkm.py - Expanded microkinetic model for ammonia synthesis from Mehta et al. [1]. Added DFT barriers, vibrational efficacy, sticking probability based reaction rates for Ru(0001). Imports 'sticking.py'.sticking.py - Helper function for converting sticking probabilities from trajectories to sticking curves. Imports 'energy_distributions.py'.energy_distributions.py - Helper functions for sampling incidence energies from Maxwell-Boltzmann distributions.compute_sticking_probabilities.py - Script processing the trajectories outputs and computing reaction probabilities with confidence bounds. Outputs 'data/adiabatic/nu=[0-10]/0_sticking_probabililty.dat'. Folder 'figure_1' plot_ammonia_turnover_frequencies.py - Python plot script. Calculation takes very long. By default reads precalculated JSON if present. Imports 'scripts/mkm.py'.ammonia_turnover_frequencies.json - Ammonia turnover frequencies from a microkinetic model for a ground state, thermal and plasma vibrational distribution at different levels of theory: 'Scaling relations + Fridman-Macheret', 'DFT + Fridman-Macheret', 'DFT + vibrational efficacy' and 'molecular dynamics based'.ammonia_turnover_frequencies.pdf - Figure as PDF. Folder 'figure_2' plot_reaction_probabilities.py - Python plot script. Imports 'scripts/sticking.py'.reaction_probabilities.dat - Thermally averaged reaction probabilities of N2 on Ru(0001) per vibrational state at different levels of theory: 'Scaling relations + Fridman-Macheret', 'DFT + Fridman-Macheret', 'DFT + vibrational efficacy' and 'molecular dynamics based'.reaction_probabilities.pdf - Figure as PDF. Folder 'figure_3' plot_vibrational_efficacy.py - Python plot script. Imports 'scripts/sticking.py' and 'scripts/energy_distributions.py'.qct_fridman-macharet_alpha.dat - Computed Fridman-Macheret alpha factor from thermally average reaction probability over vibrational state curve.thermal_vibrational_efficacy.dat - Thermally averaged vibrational efficacy per vibrational state.vibrational_efficacy_indidence_energy_nu=[0-10].dat - Vibrational efficacies over incidence energy per vibrational state nu. vibrational_efficacy.pdf - Figure as PDF. Folder 'figure_4' plot_configurational_dependence.py - Python plot script.dissociated_initial_conditions.dat - Initial coordinates of diatom (polar angle, azimuthal angle, centre of mass position) for trajectories resulting in dissociation of the molecule.configuration_distributions.pdf - Figure as PDF. Folder 'figure_S1' plot_dissociation_probabilities_uncertainty.py - Python plot script. Plots data from 'data/adiabatic/nu=[0-10]/0_sticking_probabililty.dat' files.dissociation_probabilities_uncertainty.pdf - Figure as PDF. Folder 'figure_S2' plot_qct_reaction_probability_methods.py - Python plot script. Import 'scripts/sticking.py'.qct_reaction_probability_methods.dat - Thermally averaged sticking probabilities and 95% confidence interval per vibrational state for expectation value method, interpolation method and fitting method.qct_reaction_probabilities_methods.pdf - Figure as PDF. Folder 'figure_S3' plot_md_sticking_comparison.py - Python plot script. Import 'scripts/sticking.py'.kedalo_fig4.txt - Data extracted form figure 4 in work by Kedalo et al. [2].md_sticking_comparison.pdf - Figure as PDF. Folder 'figure_S4' plot_skew_distributions.py - Python plot script. Imports 'scripts/energy_distributions.py'.skew_distribution.dat - Probability density functions of the Maxwell-Boltzmann distribution for the incidence velocity of N2 and the skewed version employed by Kedalo et al. [2].skew_velocity_distribution.pdf - Figure as PDF. Folder 'figure_S5' plot_energy_contributions.py - Python plot script. Import 'scripts/sticking.py'.plasma_energy_contributions.dat - Relative contribution per vibrational state and incidence energy to the total reaction probability for a Treanor vibrational distribution.thermal_energy_contributions.dat - Relative contribution per vibrational state and incidence energy to the total reaction probability for a Boltzmann vibrational distribution.energy_contributions.pdf - Figure as PDF. Folder 'figure_S6' plot_mean_vibrational_efficacy.py - Python plot script.energy_shifts.dat - Vibrational energy differences, Equivalent incidence energy shifts and uncertainties per vibrational state.mean_vibrational_efficacy.pdf - Figure as PDF. Folder 'figure_S7' plot_configurational_efficacy.py - Python plot script. Imports 'figure_04/plot_configurational_dependence.py'.configuration_efficacy.dat - Efficiency coefficients from minimum energy path deviations in Phi, Theta, XY and all diatom coordinates over incidence energy.configuration_efficacy.pdf - Figure as PDF. Folder 'figure_S8' plot_recrossing_distribution.py - Python plot script.recrossing_distributions.dat - Crossing count probability split between trapping, dissociation and scattering trajectories.recrossing_count.pdf - Figure as PDF. Folder 'figure_S9' plot_recrossing_efficacy.py - Python plot script. Imports 'figure_S04/plot_recrossing_distribution.py'.recrossing_efficacy.dat - Transmission coefficient versus incidence energy as computed from crossovers.recrossing_efficacy.pdf - Figure as PDF. Folder 'table_S1' print_optimal_parameters.py - Script to output the values in Table S1 in Supplementary Information. Folder 'style' EES_catalysis.mplstyle - Matplotlib stylesheets with dimensions for EES catalysis single column figure.double.mplstyle - modifying Matplotlib stylesheets with dimensions for EES catalysis double column figure. References [1] Mehta, P., Barboun, P., Herrera, F.A. et al. Overcoming ammonia synthesis scaling relations with plasma-enabled catalysis. Nat Catal 1, 269–275 (2018). https://doi.org/10.1038/s41929-018-0045-1[2] Yegor M. Kedalo, Andrey A. Knizhnik, and Boris V. Potapkin. The Journal of Physical Chemistry C 2023 127 (24), 11536-11541. DOI: 10.1021/acs.jpcc.3c01967