CCI Phase I: NSF Center for Adapting Flaws into Features

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The NSF Center for Adapting Flaws into Features (CAFF) is supported by the Centers for Chemical Innovation (CCI) Program of the Division of Chemistry. This Phase I Center is led by Christy Landes of Rice University. Other Rice team members include Stephan Link and Peter Rossky. Additional team members are Jennifer Dionne from Stanford University, Martin Gruebele from the University of Illinois-Urbana Champaign, Ben Levine from Stony Brook University, Sean Roberts from the University of Texas-Austin, and Martin Zanni from the University of Wisconsin. Iron-age metallurgists learned that judicious addition of impurities (nickel, carbon, etc.) could transform a metal with poor materials properties (iron) into strong steel tools. Chemical impurities, ‘flaws’, can be detrimental in some situations and uniquely valuable in others, creating the desirable ‘features’ of a material. In modern times, the development of silicon-based electronics exploited the same concept. CAFF’s overarching goal is to identify chemical flaws that hold promise, understand the structural and electronic properties that make those flaws uniquely influential, and then to demonstrate how the same structures can be amplified to macroscopic scales. CAFF will examine how the type, location, and sparsity of defects on atomic, nano- and microscales influence, in particular, optical materials chemistry. Broader impacts for CAFF include fast-tracking the democratization of undergraduate education and focusing on a constituency of chemists that have fallen between the cracks of public/K-12 outreach on the one hand, and undergraduate/graduate training on the other. Key will be to build a network of Community College partners that includes underrepresented urban and underserved rural communities. A diverse set of faculty and students with unique skill sets will be partners who can help form the future of American science.The NSF Center for Adapting Flaws into Features (CAFF) project aims to transform how to think about, study, and exploit defects, while optimizing new data-informed imaging tools that are broadly accessible. Real-world catalysts, coatings, and batteries are never ideal nor function in ideal conditions. Real-world synthetic chemists never make completely pure samples. Hence, physical chemists must identify ways to exploit, rather than avoid, the messy reality of flaws, such that they can be turned into features. CAFF will pursue understanding of defect-dependent exciton interconversion at organic-organic interfaces. The team will also study heterogeneity-driven chemical dynamics in metal-metal nanoparticles. Another goal is to identify the mechanisms underlying defect-supported energy-transfer in inorganic-organic hybrids. CAFF aims to leverage the combined expertise of the team in predicting, visualizing, and resolving in time localized structure and dynamics, using methods such as electron, tunneling, and hyperspectral microscopy as well as ultrafast laser spectroscopy and theory. Overall research and educational goals may be summarized as: (i) Atomic and nanoscale visualization and understanding of defects inherent to chemistry; (ii) correlating local chemistry to ensemble chemical behavior; (ii) co-development of novel data science approaches and modular instruments to move toward seamless real-time, data loss-less analysis of large data sets. Broader impacts include the development of new data-science integrated tools with potentially broad applications in basic research. Expected broader scientific outcomes include the development of affordable ‘smart’ instruments and modules, both experimental and theoretical, with the ability to adapt in time, space, and spectral resolution. These new tools will allow chemists, biophysicists, engineers, and materials scientists to study how sub-populations of defects, obscured within the ensemble average, critically control macroscale-level outcomes, properties and behavior.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.