CAREER: Mechanisms of Resistive Switching in Monolayer Materials Based on Interface and Defect Chemistry from First Principles

NONTECHNICAL SUMMARY This CAREER award supports theoretical and computational research and associated education on neuromorphic materials. Conventional architectures in computing separate processing from memory, which involves an energy-intensive process of shuttling data across physical wires. A variety of device technologies beyond conventional silicon-based devices and 10- to 100-fold improvements in capacity and energy efficiency are required to meet the growing energy demand of computing. One promising strategy, inspired by the energy efficiency of the human brain, is to place memory and processing in the same location. This necessitates finding novel materials platforms that demonstrate nonlinear behavior in their electronic properties in analogy to how neurons behave. That is, materials are needed in which electrical resistance is dependent on the history of electrical current that passed through it. Transition metal dichalcogenides are a class of nearly atomically thin materials that exhibit such resistive switching through the formation and dissolution of defects. Such monolayer materials represent the ultimate material scaling limit for high-density device integration. Proof-of-concept devices have been demonstrated, but progress is held back by large, sometimes contradictory variations in their resistive switching behavior. This arises from a limited understanding of the underlying mechanism(s) in resistive switching. The PI seeks to address this knowledge gap through atomistic simulations of the resistive switching energetics, the chemistry of defects and interfaces, and charge transport properties. By developing a materials-based model for resistive switching, this research enables rational design of energy-efficient resistive switching based on atomically-thin materials. The educational component aims to strengthen workforce development at college and pre-college levels in digital and computational literacy relevant to semiconductor technologies. The PI trains graduate students in a highly interdisciplinary research environment, produces versatile researchers with in-demand skills, and integrates these efforts into teaching and educational outreach. Activities include training undergraduate researchers, collaborating with high-school and community college instructors at the local and national levels in curriculum development, and developing a local infrastructure for tracking impact. TECHNICAL SUMMARY This CAREER award supports theoretical and computational research and associated education on neuromorphic materials. This award supports the computer-driven prediction and elucidation of resistive switching energetics and mechanisms in vertically stacked heterostructures based on transition metal dichalcogenide monolayer materials. A significant hurdle arises from the large variability in observed resistive switching characteristics, compounded by a vast number of monolayer material choices and a broad repertoire of potential defects in low-dimensional systems. There is thus a critical need to develop physical models of resistive switching to accelerate the realization of monolayer materials in high-capacity and energy-efficient memristors. This research seeks to understand connections among defect and interfacial chemistry, electronic structure, and resistive switching characteristics. By leveraging first-principles electronic structure calculations, the PI aims to: i) determine materials trends in the switching energy based on complex defect formation, ii) establish design rules for how interfacial interactions impact the resistive switching energy and resistive switching ratio, and iii) develop models that approach device-level understanding of resistive switching mechanisms by including explicit electric fields and open-quantum-system transport calculations. These efforts establish a physical basis for switching energy in atomically thin materials, help identify materials candidates with low switching energies, provide design guidelines for defect and interfacial interactions in low-dimensional heterostructures, and help accelerate the realization of low-dimensional materials in memory and storage technologies. 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.