Prof. Alp Sehirlioglu received supplemental funding for his NSF CAREER award to add a new task focused on applied data sciences. The new task follows a proposal to investigate the chemical phenomena underlying heterostructures through introduction of dimensional stacking to a dimensional reduction technique, specifically nonnegative matrix factorization (NMF), applied to time-of-flight Secondary Ion Mass Spectroscopy (ToF-SIMS) data. The new task supports a summer project for an undergraduate student and a new collaboration with Prof. Laura Bruckman.  Matthew Hoffman has been selected as the undergraduate student.

As a part of his NSF research project Prof. Sehirlioglu and his graduate student Elahe Farghadany has been investigating processing-strucutre-property relationships in (Nd,Li)TiO3 (NLTO) thin films. These materials exhibit self-assembled structures in bulk when cooled in equilibrium conditions. This research focuses on the effects of templating, interfacial strain and non-equilibrium processing (i.e., pulsed laser deposition) on self-assembly characteristics and related defect structures of single crystal films of NLTO with varying Li-content. The new task, by applying data science concepts to ToF-SIMS data, provides an atomic level resolution to composition as a function of the depth of the film, and enables extraction of information that is not normally reported.