Data to support article: "Toluene hydrogenation on Pt nanoparticles: Site-ensemble requirements and inverse temperature effects on rates"

Code and data repository for submitted manuscript on the mechanism toluene hydrogenation on Pt surfaces titled: "Toluene hydrogenation on Pt nanoparticles: Site-ensemble requirements and inverse temperature effects on rates", published in the Journal of Catalysis (doi link: https://doi.org/10.1016/j.jcat.2025.116574). The "DFT-outputs" directory has all outputs from geometry optimization and frequency calculations. Calculations for gas and surface species are reported in the "/gas" and "/surface" directories, respectively. Outputs are contained within sub-directories named according to Tables S5 and S6 in the manuscript. The outputs reported from geometry optimizations include the CONTCAR, OUTCAR, and OSZICAR VASP output files. The outputs reported from frequency calculations include those same VASP output files along with the structure in .xyz format (out.xyz) and a list of vibrational frequencies (Freqs.txt). The "Thermochemistry-analysis" directory contains Jupyter notebooks used to process the DFT outputs and calculate thermochemical properties (enthalpy, entropy, and free energy). "Thermo_calc_Final.ipynb" and "Thermo_calc_gas_Final.ipynb" calculate properties for surface and gas species, respectively. They read "surf_thermo_2025.csv" and "gas_thermo_2025.csv", respectively, to find the path to the DFT outputs. They output a .csv file containing the calculated thermodynamic properties at a specified condition. The "Regression-analysis" directory contains the MATLAB codes used to regress MCHE hydrogenation rate data (psi) to the mechanistic model developed in the manuscript. "data_psi_HT_full-deact-corr.csv" contains the experimental data. "model_1.m" contains the kinetic model as a MATLAB function. "fit_model.m" runs least-squares regression, calling on model_1.m. Funding and support:This material is based upon work supported by the National Science Foundation (NSF) Graduate Research Fellowship Program under Grant No. DGE 1106400. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the NSF. Financial support was provided from the Chevron Energy Technology Company and a Chevron/UC-Berkeley Graduate Research Fellowship. Computational resources were provided by the National Energy Research Scientific Computing Center (a DOE Office of Science user facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231), by the Extreme Science and Engineering Discovery Environment (XSEDE) supported by the NSF, and by the National Supercomputing Centre (NSCC) Singapore. Notes:Repository title was updated 14 Dec. 2025 to match the final title of the corresponding research article accepted at the Journal of Catalysis.