Improving radiation response of solid-state interfaces via control of curvature
To achieve satisfactory performance in advanced nuclear reactors, future nuclear materials must resist numerous forms of radiation-induced degradation, such as swelling, embrittlement, and accelerated corrosion. Materials that are simultaneously resistant to all of these damage mechanisms call for intricate, hierarchical microstructures composed of multiple, interpenetrating phases with finely tuned dimensions, shapes, and connectivity. The ultimate performance of these materials will be determined not only by the properties of their constituents, but also by the interfaces between them. Therefore, substantial effort has been invested into understanding the atomic-level structure of solid-state interfaces and its connection to interface behavior under irradiation. This project aims discover the effects of curvature on the radiation response of solid-state interfaces and explore strategies for elevating the radiation resistance of composite materials via control of interface curvature. The work is supported by the DOE-BES program with Professor Michael Demkowicz as the lead-PI.
Nano-scale characterization of phase-changing materials for neuromorphic computing applications
To emulate neurons and synapses, the electrical conductance of materials must be switched across orders of magnitude in an energy-efficient manner, thereby defining physical analogues of action potentials, i.e., neural spikes. Additionally, these spikes must be precisely correlated across space and time (to enable learning) with tunable retention of internal states (constituting memory). Furthermore, individual devices must be assembled within an interacting network that collectively provides emergent learning, memory, and processing functions. The scope of the problem spans many decades of spatio-temporal dimensions in terms of controlling physical phenomena whilst bridging multiple layers of abstractions. The ambitious vision of our X-grants team is to design new dynamical materials and systems that directly emulate the functionality of neurons and synapses to combine memory, computation, and communication into one fabric. Our effort is to provide nano-scale and atomic-level microstructural information to support this team effort. The work is support by the TAMU X-Grant and in collaboration with Professors Sarbajit Banerjee, Patrick Shamberger, Matt Pharr, and others.
Understanding the interplay of precipitates and dislocations on the reversible martensitic transformation in cyclically actuated NiTiHf shape memory alloys
Shape memory alloys (SMAs) can contract and extend, like an artificial muscle, upon cooling and heating through a process called martensitic transformation. Similar to muscles, shape memory alloys experience fatigue after a number of operation cycles. The fatigue of shape memory alloys is triggered and then exacerbated by the creation and accumulation of ultra-small crystalline defects called dislocations. Recent work has shown that the fatigue life of the SMAs can be dramatically improved by incorporating nano-sized particles. The purpose of this project is to provide a fundamental understanding of how these nano-particles influence the fatigue of these SMAs by using advanced and in situ electron microscopy to watch the interactions of the nanoparticles with the defects in real-time. These insights will accelerate the development of fatigue-resistant and durable super-elastic SMAs that may beneficially impact a wide variety of critical technologies, including aerospace, energy conversion, biomedical, defense, and transportation. This project will also provide multidisciplinary STEM educational and career advancement opportunities for underrepresented students through the Louis Stokes Alliance for Minority Participation program, as well as online STEM course material based on this research. The work is supported by NSF-DMR (Program Manager: Professor Judith Yang) and in collaboration with Dr. Ibrahim Karaman.
