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Tue, 04/11/2023 - 09:56am | By: Van Arnold

Dr. Xiaodan Gu, professor in the School of Polymer Science and Engineering at The University of Southern Mississippi (USM), has been awarded a $250,886 National Science Foundation grant titled, RII Track-4: Obtaining Data Science Expertise to Enable Rapid Data-Driven Material Discovery.

The one-year grant is part of a new round of research fellowships announced by NSF under its Office of Integrative Activities (OIA) Track 4 program, with the aim of improving research competitiveness in EPSCoR (Established Program to Stimulate Competitive Research) states.

Gus project will utilize cutting-edge data science techniques to accelerate the discovery and design of new polymeric materials with improved properties for various applications. The research will focus on leveraging large datasets, computational modeling, and machine learning algorithms to predict and optimize material properties, leading to the development of novel materials with enhanced performance and functionality.

This NSF OIA Track 4 award represents a significant opportunity for me to acquire expertise in this rapidly developing field of material science research, said Gu. By harnessing the power of data-driven approaches, we can accelerate the process of material discovery, reduce experimental trial-and-error, and uncover new materials with properties that were previously unattainable. It's like Moore's Law for materials. The faster the pace of discovery, the better the material's properties can be.

To acquire this new skillset, Gu will collaborate with Dr. Alexander Hexemer, a renowned data scientist in the X-ray scattering community, at the Center for Advanced Mathematics for Energy Research Applications (CAMERA) at the Lawrence Berkeley National Laboratory. Together, they will develop innovative algorithms and models that can analyze vast amounts of data, including material properties, chemical compositions, and processing conditions, to identify patterns and correlations that can guide the design of new materials.

The potential impact of this research is far-reaching, said Dr. Derek Patton, Director of the School of Polymer Science and Engineering. Data-driven material design has the potential to revolutionize industries such as aerospace, electronics, energy, and healthcare by enabling the development of advanced materials with tailored properties that can drive technological innovations.

The EPSCoR RII Track-4: EPSCoR Research Fellows program aligns with NSF EPSCoR's strategic goal of establishing sustainable pathways for Science, Technology, Engineering, and Mathematics (STEM) professional development, advancing workforce development in STEM, and promoting engagement in STEM at national and global levels.

The fellowship provides awards to build research capacity in institutions and transform the career trajectories of investigators by fostering collaborations with investigators from premier private, governmental, or academic research centers. The fellowship also provides opportunities for extended or periodic collaborative visits to a selected host site, with the aim of creating lasting impacts that enhance the fellows' research trajectories beyond the award period.

Gu's research under the NSF OIA Track 4 award on data-driven material design has the potential to contribute significantly to the field of material science and advance the development of new materials with enhanced properties. The fellowship will also provide valuable opportunities for collaboration and skill acquisition, ultimately benefiting the broader scientific community and driving innovations in various industries.

For more information about this award. One can find it on the NSFs website.

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USM Professor Earns NSF EPSCoR Fellowship to Develop New ... - The University of Southern Mississippi