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Observation of Structural Phase Changes Driven by Electrostatic Gating

Oct 13, 2021
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!
U.S. National Science Foundation and NSF DMREF, Materials for Our Future

This material is based upon work supported by the U.S. National Science Foundation Award No. 2015237. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation. This site is maintained collaboratively by principal investigators with NSF DMREF awards, independent of the NSF.