For this reason, practitioners often use local feature sets (e.g., RACs) along with global ones; most commonly with scalars describing the pore geometry (e.g., pore volumes, surface areas, accessible volumes). However, there are additional vector-valued or count-based descriptors that can be used to describe the pore geometry and might be more expressive than scalar descriptors but are seldom used in machine learning studies for reticular materials.