Grants and Contributions:

Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019).

The recent technological improvements in microscopy now allows the collection of extensive information ofx000D
samples at the nanoscale. However, in many cases, the amount of data collected surpasses the currentx000D
visualization capacity making their interpretation and analysis impractical. While two and three physicalx000D
dimensions visualization is quite intuitive, the interpretation of datasets with a higher number of dimensionsx000D
such as with chemical tomography, is less intuitive. Nevertheless, the information provided by extrax000D
dimensions is essential when attempting to uncover similarities or correlations essential for materialsx000D
development (e.g. distinguish phases in a material, identify and map impurities).x000D
The research group of Pr. Nadi Braidy have been successful in developing a classification algorithm to simplifyx000D
the interpretation of multi-spectral datasets. However, the efficiency of the algorithm and the code is notx000D
adapted to large datasets (i.e. several giga/terabytes). The goal of this project is to develop and implementx000D
scientific and software improvements to the existing algorithm to improve its computational efficiency. Thex000D
revamped algorithm will be implemented into Object Research System (ORS) Inc. visualization software,x000D
Dragonfly.x000D
In the framework of this Engage, the collaboration between Pr. Braidy and ORS will provide ORS with a toolx000D
to handle multi-modal datasets in its software while providing support in improving its efficiency.