With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Landes at Rice University is working to understand and optimize processes that occur within porous materials. The goal of the project is to develop a new type of microscope with unprecedented space and time resolution. The Landes group's new microscope allows the study of how rare events impact the efficiency of porous materials that are important for catalysis, separations science, corrosion, and biology. It has been established that it is possible to manipulate light as it interacts with molecules and proteins. For example, Professor Landes has already shown that by shaping light's phase, events faster than the camera frame rate can be imaged. By incorporating new mathematical and physical tools, the current project will result in a new instrument to image and track fast dynamics in porous materials with optimized 3-D space and time resolution. The interdisciplinary nature of this research effort provides participating students with a unique experience at the interface of spectroscopy and materials science, as well as image processing and modern information theory, and continues the strong history of cross-disciplinary activities in science and technology at Rice University. This grant supports Professor Landes to provide training opportunities to high school teachers to incorporate cutting edge science into their course materials, as well as her new effort to create a summer scientific programming course.
Recently, a new microscopy technique called super temporal-resolved microscopy (STREM) was developed. Proof-of-concept measurements showed that STREM can improve the time resolution of traditional wide-field cameras by at least twenty times. This development, if combined with recent advances in 3-D imaging methods and signal processing, represents an opportunity to resolve the multiscale, nonlinear dynamics that drive a range of interfacial materials properties. Thus, the current project's objective is to develop and optimize 4-D STREM, a chemical imaging method for quantifying the nonlinear dynamics and structures in porous materials. It is hypothesized that better 3-D sub-diffraction spatial information, coupled with improved time resolution and signal processing algorithms, reveals heterogeneous mass transport, chemical, and biological mechanisms occurring at porous interfaces. The project will involve innovations in both hardware and software to improve the temporal and 2-D spatial resolution. Additionally, a new algorithm is to be developed to track in 3-D. Finally, the new microscope is to be used to acquire and curate a machine learning library capable of differentiating among common analyte, sample, and instrument conditions. A new instrument optimized for characterizing the multiscalar physics and chemistry that underlie separations in porous media, by improving both spatial and temporal resolution is obtained in this project. Further, the project will result in new algorithms to extract information from large 3-D data sets. In terms of applications, a more detailed description of mass transport in pores and channels is a step towards predictive separations, which are currently optimized empirically, amounting to billions of dollars each year for industry, government, and academic purposes.
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.
