Observation of Structural Phase Changes Driven by Electrostatic Gating
Our efforts in data mining and machine learning have resulted in a number of new databases and predictions. These include: a database of over 1,000 2D materials that exist naturally as layered materials in the bulk (a), exploration of possible 2D materials that could be used in phase change applications, prediction of new superionic solid state Li-containing battery materials, and the creation of a website that allows researchers to easily search and predict the conductivity of solid-state electrolyte materials.
We have hosted several excellent high school students, many of who will be first-generation college students. (b) High school students Manuel Haro, Alex Anaya, and Michael Chau at the Stanford RISE poster session presenting their research!
Related Project: Data Driven Discovery of Synthesis Pathways and Distinguishing Electronic Phenomena of 1D Van der Waals Bonded Solids