Advancements in semiconductor integrated circuit (IC) “chip” technology over the past 60+ years have enabled exponential growth in chip functionality with exponential reduction in cost per transistor, resulting in the […]
A non-local (gradient) plasticity model for porous metals that accounts for deformation-induced anisotropy is presented. The model is based on the work of Ponte Castañeda and co-workers on porous materials […]
Data compression is enjoying a renaissance fueled by an unprecedented growth in both the amount of data being generated and our reliance on powerful computation. At its heart is an […]
Abstract: Vibrational spectroscopies at mid-infrared frequencies provide excellent probes to characterize functional groups and their immediate chemical environment. However, from a thermodynamic and dynamic point of view, only the ground […]
The end of traditional transistor scaling brings unprecedented new opportunities to semiconductor devices and electronics. We are at the onset of a new technology revolution, which will focus on distributed […]
Since the first discovery of semiconductors, materials synthesis has been the driving force for new devices, new applications, and new markets. In this presentation, Professor Doolittle will provide two examples […]
In this work, we present a low-rank tensor approach for approximating solutions to the nonlinear Vlasov equation. Our method takes advantage of the tensor-friendly nature of the differential operators in […]
Complex, three dimensional (3D) micro/nanostructures in biology provide sophisticated, essential functions in even the most basic forms of life. Compelling opportunities exist for analogous 3D structures in man-made devices, but […]
Email jnespos@seas.upenn.edu for the Zoom link. This talk will start by introducing diverse fluid-mechanics research conducted in the Park research group, including complex fluids, electrokinetics, biofluids, transition-to-turbulence, and turbulent flow. […]
Despite impressive success in domains such as vision and language, machine learning is still far from reliable integration into many challenging real-world scenarios, such as healthcare, where the coverage of […]
