AVS 66th International Symposium & Exhibition
    2D Materials Wednesday Sessions
       Session 2D+EM+MI+MN+NS+QS-WeM

Invited Paper 2D+EM+MI+MN+NS+QS-WeM1
A Safari Through Thousands of Layered Materials Guided by Data Science Techniques

Wednesday, October 23, 2019, 8:00 am, Room A226

Session: Novel 2D Materials
Presenter: Evan Reed, Stanford University
Authors: E.J. Reed, Stanford University
G. Cheon, Stanford University
Correspondent: Click to Email

We have utilized data mining approaches to elucidate over 1000 2D materials and several hundred 3D materials consisting of van der Waals bonded 1D subcomponents, or molecular wires. We find that hundreds of these 2D materials have the potential to exhibit observable piezoelectric effects, representing a new class of piezoelectrics. A further class of layered materials consists of naturally occurring vertical hetero structures, i.e. . bulk crystals that consist of stacks of chemically dissimilar van der Waals bonded layers like a 2-D super lattice. We further combine this data set with physics-based machine learning to discover the chemical composition of an additional 1000 materials that are likely to exhibit layered and two-dimensional phases but have yet to be synthesized. This includes two materials our calculations indicate can exist in distinct structures with different band gaps, expanding the short list of two-dimensional phase change materials. We find our model performs five times better than practitioners in the field at identifying layered materials and is comparable or better than professional solid-state chemists. Finally, we find that semi-supervised learning can offer benefits for materials design where labels for some of the materials are unknown.