Project Details
Description
In order to support world needs, we depend on certain commercial reaction systems that consume a significant fraction of the world's energy resources, such as for the production of ammonia fertilizers from nitrogen gas. This is because one single catalyst material is not optimal for all the elementary reaction steps that are required for a conversion. The current catalyst system is the best compromise, but is inefficient. Improving upon this energy-costly situation through application of new catalyst materials is a daunting challenge, however. Under the National Science Foundation initiative titled Designing Materials to Revolutionize and Engineer our Future, an award is being made to a collaborative team of Profs. Michael Janik (Pennsylvania State University), Suljo Linic (University of Michigan), Will Medlin (University of Colorado) and Eranda Nikolla (Wayne State University) to develop new multicomponent catalyst materials that will allow greater efficiency in energy-demanding reaction schemes. The research team proposes that new cascade catalyst materials be prepared by nanoscale synthesis techniques to link the multiple components that have different functions in an overall reaction. Close linking of these catalytic material components, in principle, can reduce the formation of unwanted and environmentally hazardous byproducts and decrease the required energy input for necessary chemical reactions. While the research team has demonstrated the concepts required to construct the individual catalyst features required for this approach, predictive models are needed to guide the design of how to link these components to result in an improved process. This project will develop the multi-scale models necessary to design complex catalyst assemblies. These models will be validated and refined through experimental testing of catalyst materials defined by computational designs.
An alternative approach to catalytic conversion will be developed using multi-component, multi-active site materials. Communication between active sites will be controlled by the selective transport of energetic intermediates. A computationally-guided design framework will 1) utilize atomistic and electronic structure methods to optimize individual catalytic components, and 2) construct a coupled microkinetic/transport model to guide construction of the multi-component material. Synthesis, fabrication, characterization, and reactivity studies will validate computational models and realize the enhancements offered by the catalysts. Initial catalyst development efforts will concentrate on ammonia synthesis, using one site to generate active proton and electron intermediates that transport to a second site to reduce nitrogen. Transferability of the design approach will be demonstrated by applying it to design cascades for selective oxidation of biomass-derived species in alkaline systems. The computationally guided design of inorganic catalytic cascade systems will both demonstrate the potential of these multi-component materials to provide efficient catalytic processes and provide a design framework for rapid acceleration of their development. The research will be integrated with educational and outreach activities to broaden the impact of the proposed work. Undergraduate researchers drawn from programs that target underrepresented groups will be integrated into research efforts at the four partner institutions, involving these students in multi-disciplinary work with exposure to the collaborative team. Research groups at each institution will participate in science outreach activities targeted at preschool through K-12 groups, such as Central Pennsylvania's 'Exploration Days' and the Michigan Science Center's 'Ask the Expert' series. The collaborative group plan coordinated course offerings among the partner institutions, which will provide opportunities for collaborative teaching, specifically aimed at integrating active learning tools at all the institutions.
Status | Finished |
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Effective start/end date | 9/1/14 → 8/31/19 |
Funding
- National Science Foundation: $476,073.00