The proposed work aims at developing the tools required for the intelligent choosing and tuning of nano-porous materials with respect to a specific application. For this purpose, a combined computational theoretical and experimental study is envisaged in order to digitally reconstruct the porous matrix of selected advanced materials, mainly for applications involving sorption of carbon dioxide and methane by employing advanced Statistical Mechanics based computer simulation methods, both, in atomistic (Monte Carlo, ab initio and equilibrium and non-equilibrium Molecular Dynamics) and mesoscopic level (Kinetic Monte Carlo and Lattice Gas Cellular Automata). The reasoning behind this strategy is that the structure of materials spans a wide range of length scales, making thus sorption and transport phenomena depend upon length and time scale. As a consequence, the proposed computational methodology consists of many levels in order to address properly these phenomena. Moreover, a complementary approach to computer simulations is provided through direct comparison of two highly sophisticated methods for measuring motion of guest molecules inside porous materials, namely, quasi-elastic neutron scattering (QENS) and pulsed field gradient nuclear magnetic resonance (PFG NMR), carried out by the groups of Lyon and Leipzig respectively. This type of combined studies can be perfectly utilized through the proposed work towards a fascinating insight of the relation of the material interior to the sorption and transport mechanisms of sorbates such as carbon dioxide and methane, both involved in the so-called greenhouse effect.