Quantifying the Coarsening Kinetics of Supported Metal Nanoparticles Using Time-resolved Electron Microscopy, Data Analytics and Simulations

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Non-Technical Abstract:Metallic nanoparticles find important applications in a variety of industries, most notably as catalysts in the chemical industry where they are used for the creation of fuels and related chemical byproducts. This is because their small size exposes many atoms on their surface: these surface atoms are the ones that help to improve their reactivity. However, their ability to function effectively for long periods is related to their ability to maintain this small size, even when being exposed to high temperatures and harsh environments that would normally lead to particle growth. This study will clarify the fundamental processes by which unwanted nanoparticle growth occurs by directly observing these processes using advanced microscopies, measuring the changes that occur in both individual particles and particle ensembles, and using computational modeling to clarify what processes are most responsible for particle growth. The studies will provide fundamental knowledge that can be used to increase the long-term performance of catalytic materials, leading to reduced energy cost and greater industrial yields. The project will include workforce preparation for the student involved via exposure to forefront materials characterization efforts, a deep interaction between experiment and theory, utilization of advanced data analytics approaches and visits to leading laboratories at IBM T.J. Watson Research Center and Brookhaven National Laboratory (BNL). The Summer Undergraduate Laboratory Internship (SULI) program and the Louis Stokes Alliances for Minority Participation (LS-AMP) at BNL will bring in students from the University of Puerto Rico, Rio Piedras to participate in data analytics code development, as well the development of software for microscope image analysis that will be disseminated to the broader community.Technical Abstract:A combination of advanced transmission electron microscopy methods will be used to investigate the role of surface stress and interparticle diffusional interactions in nanoparticle coarsening, to quantify the interplay between evaporation, coarsening and ripening in supported nanoparticles systems, and to investigate the effects of substrate modification and relative levels of nanoparticle oxidation and reduction on these phenomena. The work will exploit high-frame rate image acquisition and semi-automated data analysis routines to produce accurate quantitative data from images. This data will be used in a self-consistent fashion to both provide inputs to and corroborate outcomes from computational simulations. The resulting studies will allow, quantitative understanding of how nanoscale processes affect coarsening and ripening and will suggest strategies to mitigate these process in supported metallic nanostructure systems.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.