Catalysis research often generates vast amounts of data from experimental and computational studies. This data can be multi-dimensional and highly complex, involving variables such as temperature, pressure, reactant concentrations, and catalyst properties. HDF5 provides a robust solution for storing such intricate datasets efficiently and reliably. It supports the creation of portable, self-describing files that can be shared across different platforms and research teams.
