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Figure 33. Partial differential equations (PDE)-based techniques can be used to automatically analyze 3D structures of porous materials. These images show how a PDE-based front propagation method is used to map accessible void space inside porous material. Source: M. Haranczyk and J. A. Sethian, Proc. Natl. Acad. Sci. 106, 21472 (2009). Reprinted with permission. Discovery by Inverse Design The concept of inverse design represents an exciting and largely unexplored opportunity to identify optimal materials for carbon capture applications and many other design targets. Given a known property– structure relationship, one could envision algorithms that generate novel materials or molecules that directly satisfy the constraint of producing a desired property. For example, if the desired property requires, say, a nanoporous material with a well-defined pore topology, the inverse design algorithms would generate chemically accessible structures that have exactly the desired property. (See the sidebar “Inverse Design of Capture Molecules.”) Guided Synthesis The preceding two subsections presented two approaches to facilitating the discovery of novel materials. These virtual materials would, however, need to be capable of synthesis before their performance could be verified experimentally. Thus the design of a realistic synthesis pathway for such hypothetical, search-generated, materials will present another considerable challenge for computational techniques. The synthesis of 3D solid-state materials requires a much better understanding of guided nucleation processes (e.g., how structure-directing agents or templates affect the nucleation barriers to create a variety of solid-state forms of matter). Additionally, more study is needed to understand how solution or processing conditions (solvents, aging, and environmental factors) and composition affect the self-assembly processes. Finally, computational elucidation of the principles behind hierarchical assembly is still a significant challenge. It is insufficient simply to know how to create/synthesize a desired molecular structure; competing thermodynamic and kinetic pathways that create undesired or unexpected structures must be inhibited or avoided. IMPACT AND CONCLUSIONS The crosscutting research directions discussed will have a large impact in facilitating and expanding the usefulness of computer simulation techniques (from ab initio to continuum- based approaches) to predict solutions for carbon capture scenarios. The provision of accurate transferable force fields and materials structures forms the bedrock of subsequent studies of specific candidate materials and processes for carbon capture. Better descriptions of these complex host materials and gas–host interactions will be essential for calculating phase equilibria, isotherms, estimates of permeability and selectivity for a specific solute (CO2 or O2, say), and the nature of fluid–fluid and fluid–solid interfaces. Molecular simulation might be used to derive theoretical “upper bounds” for the anticipated separation selectivity for a given class of materials (e.g., ionic liquids, crystalline solids, polymers). Such an upper bound can help experimentalists in setting targets for materials development. For any given separation task, can molecular simulations help us decide a priori which class of materials is likely to be more effective? 110PDF Image | 2020 Carbon Capture
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