Speaker
Description
Phase change materials (PCMs), which can be reversibly switched between their high-resistance and low-resistance phases, are promising for non-volatile, high-density data storage and research in non-von Neumann computing architectures. Recent discovery and development of novel PCM superlattices consisting of various layers have demonstrated unprecedented low power and high-density at nanoscale. However, the properties of these layered PCMs are largely under-explored. In this work, the atomic and electronic properties of layered PCMs are explored using high-throughput Density Functional Theory (DFT) calculations. The physical understanding on the structure-property relationships will inform and train a machine learning model for the discovery of novel PCMs for energy-efficient memory devices.
