Apr 24, 2024
1:30pm - 2:00pm
Room 320, Level 3, Summit
Wennie Wang1
University of Texas at Austin1
We present work in the Wang Materials Group (https://wangmaterialgroup.com) in understanding and harnessing defects in materials for energy sustainability applications that leverage and/or are inspired by aspects of machine learning. Our goal is to elucidate and predict the materials properties at the microscopic level using first-principles calculations, drive the exploration of novel materials platforms, and create strategies that directly couple to/guide experiments. Here, we present on two such case studies on next-generation memory and storage applications and electrocatalysts.<br/>Memristors are an emerging memory technology that can help meet the capacity and energy efficiency demands. Non-volatile resistive switching (NVRS) between high- and low-resistive states has been broadly observed in various two-dimensional materials. As atomically thin systems, two-dimensional materials are promising as the active switching layer for two-terminal vertically stacked memristor devices. We examine one particular mechanism of NVRS based on the formation and dissolution of point defect complexes to describe the switching energetics and switching processes. In this talk, we will present our efforts in leveraging automated calculations to screen for defects capable of inducing NVRS in two-dimensional materials and extract materials-based scaling relationships for the switching energy.<br/>In the second case study, we turn to the investigation of structure and catalytic activity relationships in electrocatalysts. Low-temperature electrocatalysis of water is at the forefront of strategies that could help realize a clean hydrogen economy. The (oxy)hydroxides are scientifically significant as electrocatalysts that electrochemically form on many pre-catalyst surfaces in the amorphous state. Interestingly, amorphous electrocatalysts have been reported to consistently outperform crystalline ones. Our goal is to connect the structural disorder in amorphous electrocatalysts to mechanism(s) in enhancing the electrocatalytic activity. We will discuss the considerations to appropriately describe the electronic and atomic structure and strategies in using point defects and genetic algorithms to understand local structural disorder.