Check out our posters at the **Spring ’16 Faculty ****Data Science Meetup **hosted by the Ken Kennedy Institute for Information Technology (**April 13, 2016, 3-5pm, **BioScience Research Collaborative Building (BRC) Event/Exhibit Hall):

**Digging into Big Data of 2D nanomaterials… for fun and profit**

Steady progress in computing power has motivated computational materials scientists to try new approaches to modeling materials. Here we explore data-driven and data-centric approaches to *explain* the properties and behavior of *real* advanced materials or accelerate the *discovery of new *ones. Often, this necessitates the sampling of enormous configurational spaces due to chemical and/or structural variety and processing the associated `big-data’ computational output. Selected examples are presented illustrating a state-of-the-art approach that allows for an elegant use of statistical mechanics methods (“cluster expansion”) in combination with first-principles density-functional theory (DFT) calculations, leading to a thorough exploration of the configurational space.

Materials systems include the alloys of two-dimensional transition-metal dichalcogenides M_{1-x}M’_{x}X_{2y}X’_{2(1-y)}, the 2D materials family within the B-N-C phase diagram, the peculiar, no longer hypothetical, 2D polymorphs of elemental boron, as well the end-caps of single walled carbon nanotubes.