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are a fascinating subfamily of porous crystalline materials. The unique structural flexibility related to pore opening/closing makes them promising candidates for many gas storage and separation
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unobtainable through other means. To date, only a limited number of materials have been successfully demonstrated for use in AM and the structural properties of these materials are not well understood
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separation, energy converting biological processes, and signal transduction. However, despite their obvious importance, atomic structures have been determined for only a few dozen of these proteins because
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guiding materials measurement experiments to acclerate learning the synthesis-process-structure-property relationship. Machine learning methods include, but are not limited to, Bayesian inference
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work is anticipated in the areas of microresonator design, engineering biology/biomanufacturing, dioxygen imaging in 3D cell culture, and structural biology methods development. Knowledge of microwave
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are a key for predicting reaction mechanisms and designing improved electrocatalysts, reactants, and electrolytes. The properties of electrochemical interfaces depend both on the surface structure and the
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301.975.4347 Description Certain functional materials, especially those with perovskite or related structures, exhibit remarkable physical properties, such as large dielectric constants, large piezoelectric
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routinely consist of films only Angstroms in thickness and forming spatially isolated patterns with some lateral dimensions in the low nanometers. Example systems include core-shell structures used in
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photolithography methods. The self-assembly of the block copolymer is directed by a template patterned by conventional lithographic methods. The block copolymer structure within the pattern template can amplify the
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semiconductor nanoparticles, dopant based quantum devices in Si, and complex nanosystems made from these structures. Generation, control, guiding, and manipulation of photons on the nanoscale with these systems