The Rackham Predoctoral Fellowships receive approximately 240 nominations each year and are able to award around 85 fellowships. For the 2022-2023 academic year, four mechanical engineering (ME) students have been selected for this fellowship. The Rackham Predoctoral Fellowship supports outstanding doctoral students who have achieved candidacy and are actively working on dissertation research and writing. We seek to support students working on dissertations that are unusually creative, ambitious, and impactful.
Congratulations to the following ME awardees!
My research addresses fundamental challenges in the additive manufacturing (AM) of customizable integrated nanosystems. My work lies at the intersection of process modeling and control for improved device/system functionality. My research focus is to understand and control how process parameters dictate the precision, accuracy, and quality of a nanomanufactured device/system. Toward this objective, I targeted three distinct research areas: (1) fabrication design, which looks at understanding the capabilities and limitations of nanomanufacturing technologies, material interactions, and identifying the proper design based on the knowledge of the device/system and the components required to integrate with the process; (2) understanding of process physics, including the modeling frameworks that enable prediction of the process dynamics across a range of process parameters and environmental conditions; and (3) control design, which leverages the built models to develop control strategies for improving process performance, robustness, and reliability.
I mainly work on modeling, design, and optimization of rechargeable batteries such as lithium-ion and sodium-ion batteries. An essential and challenging task of battery research is to describe the mechanisms by models and optimize the parameters to achieve the best performance. I model the transport of solid-state electrolytes and the degradation of lithium-ion cells. Then I measure the parameters of the models in experiments. Additionally, I develop efficient algorithms to optimize battery parameters to reduce testing costs from long-time cycling. These efforts help to promote battery development to a more logical, predictable, and efficient stage
Finite-amplitude pressure waves occur in compressible flows following large and sudden disturbances, such as the detonation of mining explosives or the rapid transit of a high-velocity aircraft. When these waves interact with material interfaces, they may become attenuated or strengthened, and the mixing they induce has critical implications in many scientific and engineering contexts. For example, shock-induced mixing of astrophysical material naturally follows supernova explosions and may govern the structure of an ensuing nebula. Furthermore, in inertial confinement fusion, mixing leads to a reduction in compression that severely penalizes fusion yields. The focus of this dissertation is to improve our understanding of these complex mixing processes to advance astrophysics, fusion research, and many other applications. This is accomplished with hydrodynamic theory, simulations, and experiments that explore and characterize novel hydrodynamic phenomena and regimes of mixing.