Chemical and related process oriented companies are increasingly realizing that the sustainable development of their industries will critically depend upon the development of new innovative processes that use materials and energy more efficiently. As overall separation processes account for 40-60% of both capital and operating costs in chemical industry, their amelioration can significantly reduce costs, energy use, waste generation and increase profits. Over the last decades gas separation by adsorption and permeation technologies have become major unit operations in chemical and petrochemical industries due to their efficiency relative to more mature technologies like cryogenic separation or separation by absorption. Industrial customers are expecting more features and flexibility from vendors, as a result industrial plants are becoming more and more complex both physically and in design. In the past, industrial systems could be designed by trial-and-error and the use of empirical knowledge. Nowadays modelling and simulation are playing a prominent and expanding role in the design process as the understanding of models and phenomena improves along with computational efficiency. The two interrelated directions of research in gas separation by adsorption or permeation technologies are materials research and process design and optimisation [1-4]. The ability to design novel materials needs the development of new simulation tools that can accelerate the discovery process. The challenge in linking different length and time scales in materials science is that there is a lack in theories linking every aspect of materials' characteristics in a unified manner[5]. Much of materials design is based on phenomenological paradigms that provide guidelines for materials selection[6]. The integration of data at different length scales in order to detect patterns of behavior that could lead to new information is an important element towards building a materials design framework. Data mining technology would help to exploit masses of available data and accelerate building of correlations between the 3D chemical solid structures (polymers) and their gas adsorption (permeation) properties[7]. These correlations will be used for generation of design rules for new and better materials to be used in non-cryogenic gas separation technologies. This paper focuses on the need to shorten the research cycle about novel materials for a given gas separation problem by combining several computational approaches and experimental techniques. It does not pretend to be a review or cover all aspects that might be considered traits of the computational materials design. Various examples are used to show how the existing molecular modeling tools are employed in Air Liquide to complement experimental work. After a brief discussion on various computational approaches used to cover different aspects of inorganic materials research the presentation deals with the importance of nanoscopic understanding of phenomena and factors that control themiodynamic and transport properties of confined fluids in adsorbents and membranes.
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