Computational-based catalyst design for thermochemical transformations
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Introduction The diminishing availability of fossil fuels and the increasing emissions of carbon dioxide have spurred burgeoning research activity toward alternative and sustainable energy sources. Improved process efficiency for energy savings, untapped energy sources (e.g., utilization of remote and offshore natural gas reserves), renewables (e.g., solar energy, biomass conversion), and carbon dioxide capture followed by sequestration or utilization will all be important contributors to our future energy portfolio.1 Solid materials will be central more than ever in the endeavor of energy production and storage,2 but increased precision in molecular architecture and tailor-made multi-functionality will also be required.3 The substantial economic growth of the developed world has relied heavily on its chemical and petrochemical industry. At the heart of a chemical plant lies the chemical reactor, converting raw materials into valuable chemicals and fuels. A major fraction of chemical reactions are carried out on heterogeneous catalysts. Upstream and/or downstream separations complete the major physical and chemical operations. A separation example entails purification of hydrogen from carbon monoxide to avoid poisoning of the fuel cell catalyst. Low-temperature separation processes using, for example, microporous (pore size < 2 nm) and mesoporous (pore size > 2 nm) membranes and multi-scale,
multi-functional catalytic materials will be key in converting carbon neutral resources, such as biomass and its derivatives (e.g., glucose, fructose), to chemicals and fuels.3 This article delivers a perspective of the computationalbased design of emergent nanocatalysts for thermochemical transformations that can be used for the improved efficiency of existing industrial processes, biomass processing to renewable chemicals and fuels, and the utilization of untapped energy sources. In addition, mechanistic insights into the formation of such nanomaterials are discussed, with an emphasis on colloidal growth of metal nanoparticles. Understanding nucleation and growth can lead to the control of nanoparticles at the atomic level for improved catalyst activity and selectivity.
Catalyst design for thermochemical transformations In this section, we provide an overview of computational advances in the rational design of catalytic materials. We highlight strategies for the discovery of very active bimetallic catalysts and adsorption models that account for nanoparticle characteristics.
Traditional catalyst discovery The selection of catalysts has traditionally been based on trial and error. The introduction of high throughput experimentation
Giannis Mpourmpakis, Institute of Electronic Structure and Laser Foundation for Research and Technology, Greece; [email protected] Dionisios G. Vlachos, University of Delaware, Newark, DE 19716, USA; [email protected] DOI: 10.1557/mrs.2011.36
© 2011 Materials Research Society
MRS BULLETIN • VOLUME 36 • MARCH 2011 • www.mrs.org/bulletin
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COMPUTATIONAL-BASED CATALYST DESIGN FOR THERMOCHEM
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