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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:MISSISSIPPI STATE UNIVERSITY
Doing Business As Name:Mississippi State University
PD/PI:
  • Hyeona Lim
  • (662) 325-7142
  • hlim@math.msstate.edu
Co-PD(s)/co-PI(s):
  • Rudolf T Clay
Award Date:02/11/2020
Estimated Total Award Amount: $ 310,000
Funds Obligated to Date: $ 310,000
  • FY 2020=$310,000
Start Date:04/01/2020
End Date:03/31/2023
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.049
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:REU Site: Computational Methods with applications in Materials Science
Federal Award ID Number:1950208
DUNS ID:075461814
Parent DUNS ID:075461814
Program:XC-Crosscutting Activities Pro
Program Officer:
  • Lynnette Madsen
  • (703) 292-4936
  • lmadsen@nsf.gov

Awardee Location

Street:PO Box 6156
City:MISSISSIPPI STATE
State:MS
ZIP:39762-9662
County:Mississippi State
Country:US
Awardee Cong. District:03

Primary Place of Performance

Organization Name:Mississippi State University
Street:P.O. Box 6156
City:Mississippi State
State:MS
ZIP:39762-9662
County:Mississippi State
Country:US
Cong. District:03

Abstract at Time of Award

This project is jointly funded by the Division of Materials Research and the Established Program to Stimulate Competitive Research (EPSCoR). NON-TECHNICAL DESCRIPTION: Computational methods and data analysis are now widely used to predict the properties of materials and to understand data from materials experiments and simulations. While these computational techniques are commonly taught in graduate programs in science, math, and engineering, few undergraduate students have an opportunity to learn about them or participate in this rapidly expanding research field. This Research Experiences for Undergraduates (REU) Site addresses this shortcoming and provides a unique opportunity for undergraduate students to participate in meaningful research with a group of researchers from the Center for Computational Sciences (CCS), an interdisciplinary computational research center at Mississippi State University (MSU). A significant portion of participants for this REU program are recruited from historically black colleges and universities and primarily undergraduate institutions from across the United States. An annual one-day workshop for high school teachers offers the teachers guidance on research that they can perform with their own students. Graduates of this REU site are well prepared for graduate study in science, engineering, or mathematics. TECHNICAL DETAILS: The student participants recruited for this REU spend 10 weeks over the summer in multidisciplinary research with eight faculty mentors in Mathematics, Statistics, Physics, and Chemistry from CCS. The students are first trained in the basic science and computational techniques necessary for their research projects. Additional training activities improve the participants’ computational skills as well as written and oral presentation skills. The eight research projects are: (1) electron-electron correlation physics; (2) numerical Methods for Phase Field Models; (3) interfacial properties in high-performance composite materials; (4) materials research for rare earth-free permanent magnets; (5) image denoising and segmentation methods for material analysis; (6) Bayesian parameter estimation and model comparison; (7) photophysical properties of novel polycyclic aromatic hydrocarbons and their complexes; and (8) high-dimensional material data analysis. REU participants are given access to supercomputing resources at the MSU High Performance Computing Collaboratory. The students participate in weekly group meetings, seminars and training sessions on scientific and computational topics, and a Graduate Record Exam workshop. At the end of the summer they present the final results of their project to the REU group and at the MSU Summer Undergraduate Research Symposium. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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