are intensive scientifi c efforts focused on the development of new physical adsorbents that might enable more energetically favorable gas separation, relative to traditional distillation or absorption processes. This feat is not easy, as the differences in the molecules of interest, such as CO 2 and N 2 -the main components in a postcombustion fl ue gas, are minimal. [ 2,3 ] As such, these separations require tailor-made adsorbent materials with molecule-specifi c chemical interactions on their internal surface. [ 4,5 ] Metal-organic frameworks (MOFs) are a particularly attractive class of porous adsorbents that are under intense investigation for gas separation due to their unmatched structural versatility. Many stable, 3D frameworks that offer unprecedented internal surface areas and the selective adsorption of a wide range of small guest molecules have been discovered. [ 6 ] The molecular nature of the organic ligand in an MOF provides a convenient modular approach to their synthesis and facile chemical tunability, creating a surge towards the directed design of new materials ( Figure 1 ). [7][8][9] Through judicious selection of the ligand and metal, which control pore size/shape and MOF-adsorbate interactions, MOF uptake properties, Metal-organic frameworks (MOFs) have gained much attention as nextgeneration porous media for various applications, especially gas separation/ storage, and catalysis. New MOFs are regularly reported; however, to develop better materials in a timely manner for specifi c applications, the interactions between guest molecules and the internal surface of the framework must fi rst be understood. A combined experimental and theoretical approach is presented, which proves essential for the elucidation of small-molecule interactions in a model MOF system known as M 2 (dobdc) (dobdc 4− = 2,5-dioxido-1,4-benzenedicarboxylate; M = Mg, Mn, Fe, Co, Ni, Cu, or Zn), a material whose adsorption properties can be readily tuned via chemical substitution. It is additionally shown that the study of extensive families like this one can provide a platform to test the effi cacy and accuracy of developing computational methodologies in slightly varying chemical environments, a task that is necessary for their evolution into viable, robust tools for screening large numbers of materials.