This dataset contains all data generated during the study titled "Fischer-Tropsch Catalysis of Fe13 Nanoclusters on SiO2 Surfaces in Outer Space: A Quantum Mechanical Study." It includes computational results, input files, and methodological details used in the research. The dataset aims to ensure transparency, facilitate reproducibility, and provide access to the computational methods employed. By making this data available, researchers can verify the findings and apply the methodologies to similar studies in astrochemistry and catalysis.

METHODOLOGICAL INFORMATION

1. Description of methods used for collection-generation of data: All de data has been generated with the program CP2K, the level of theory used to perform the calculations was DFT functionals (PBEsol and B3LYP) and a double and triple z-basis sets. Also, RRKM calculations have been performed with a homemade program freely available in zenodo. All the references are included below by order of appearance.

Kühne, T. D., Iannuzzi, M., Del Ben, M., Rybkin, V. V., et al. CP2K: An electronic structure and molecular dynamics software package -Quickstep: Efficient and accurate electronic structure calculations. J. Chem. Phys. 2020, 152, 194103. Perdew, J. P., Ruzsinszky, A., Csonka, G. I., Vydrov, O. A., et al. Restoring the density-gradient expansion for exchange in solids and surfaces. Phys. Rev. Lett. 2008, 100, 136406. Grimme, S., Antony, J., Ehrlich, S., Krieg, H. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J. Chem. Phys. 2010, 132, 154104. Vandevondele, J., Krack, M., Mohamed, F., Parrinello, M., et al. Quickstep: Fast and accurate density functional calculations using a mixed Gaussian and plane waves approach. Comput. Phys. Commun. 2005, 167, 103–128. Goedecker, S., Teter, M. Separable dual-space Gaussian pseudopotentials. Phys. Rev. B - Condens. Matter Mater. Phys. 1996, 54, 1703–1710. Lippert, G., Hutter, J., Parrinello, M. A hybrid Gaussian and plane wave density functional scheme. Mol. Phys. 1997, 92, 477–488. Becke, A. D. A new mixing of Hartree-Fock and local density-functional theories. J. Chem. Phys. 1993, 98, 1372–1377. Lee, C., Yang, W., Parr, R. G. Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density. Phys. Rev. B 1988, 37, 785–789. Guidon, M., Hutter, J., VandeVondele, J. Robust periodic Hartree-Fock exchange for large-scale simulations using Gaussian basis sets. J. Chem. Theory Comput. 2009, 5, 3010–3021. Guidon, M., Hutter, J., Vandevondele, J. Auxiliary density matrix methods for Hartree-Fock exchange calculations. J. Chem. Theory Comput. 2010, 6, 2348–2364. Neese, F. Software update: The ORCA program system—Version 5.0. Wiley Interdiscip. Rev. Comput. Mol. Sci. 2022, 12, e1606. Riplinger, C., Sandhoefer, B., Hansen, A., Neese, F. Natural triple excitations in local coupled cluster calculations with pair natural orbitals. J. Chem. Phys. 2013, 139, 134101. Guo, Y., Riplinger, C., Becker, U., Liakos, D. G., et al. Communication: An improved linear scaling perturbative triples correction for the domain based local pair-natural orbital based singles and doubles coupled cluster method [DLPNO-CCSD(T)]. J. Chem. Phys. 2018, 148, 11101. Dunning, T. H. Gaussian basis sets for use in correlated molecular calculations. I. The atoms boron through neon and hydrogen. J. Chem. Phys. 1989, 90, 1007–1023. Perdew, J. P., Burke, K., Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 1996, 77, 3865–3868. Jaramillo, J., Scuseria, G. E., Ernzerhof, M. Local hybrid functionals. J. Chem. Phys. 2003, 118, 1068–1073. Becke, A. D. Perspective: Fifty years of density-functional theory in chemical physics. J. Chem. Phys. 2014, 140, 18–301. Chai, J. Da, Head-Gordon, M. Systematic optimization of long-range corrected hybrid density functionals. J. Chem. Phys. 2008, 128, 84106. Zarkevich, N. A., Johnson, D. D. Nudged-elastic band method with two climbing images: Finding transition states in complex energy landscapes. J. Chem. Phys. 2015, 142, 24106. Marcus, R. A. Unimolecular dissociations and free radical recombination reactions. J. Chem. Phys. 1952, 20, 359–364. Eckart, C. The penetration of a potential barrier by electrons. Phys. Rev. 1930, 35, 1303–1309. Molpeceres, G., Zaverkin, V., Furuya, K., Aikawa, Y., Kästner, J. Reaction dynamics on amorphous solid water surfaces using interatomic machine-learned potentials: Microscopic energy partition revealed from the P + H → PH reaction. Astron. Astrophys. 2023, 673, A51. Enrique-Romero, J., Rimola, A. QuantumGrain RRKM code. at https://doi.org/10.5281/ZENODO.10518616 2024.

1. Methods for processing the data: The submitted data has been not modified from the collected data, it is presented as obtained from the calculations outputs.

2. Instrument- or software- specific information needed to interpret the data: Not specific software is required to interpret the data.

3. Instruments, calibration and standards information: No instruments has been used, the programs can run in any HPC facility.

4. Environmental or experimental conditions: Computational methods: DFT. Software used: CP2K and Orca Level of theory and basis sets: Functional PBEsol and B3LYP, basis sets DZVP and TZVP. Simulation conditions: Periodic Bondary Conditions.

5. Quality-assurance procedures performed on the data: We performed the following tests: Convergence tests: Ensuring calculations are well-converged with respect to energy, forces, and basis set size. Benchmarking: Comparing results with computational data at very tight levels (CCSDT) Validation checks: Cross-checking with literature values. Reproducibility tests: Running key calculations multiple times to confirm consistency. Data integrity checks: Ensuring input/output files are complete, correctly formatted, and free from corruption.