NSF Org:	CMMI Div Of Civil, Mechanical, & Manufact Inn
Recipient:	AUBURN UNIVERSITY
Initial Amendment Date:	August 25, 2023
Latest Amendment Date:	August 25, 2023
Award Number:	2319690
Award Instrument:	Standard Grant
Program Manager:	Alex Leonessa aleoness@nsf.gov  (703)292-2633 CMMI  Div Of Civil, Mechanical, & Manufact Inn ENG  Directorate For Engineering
Start Date:	September 1, 2023
End Date:	August 31, 2026 (Estimated)
Total Intended Award Amount:	$704,482.00
Total Awarded Amount to Date:	$704,482.00
Funds Obligated to Date:	FY 2023 = $704,482.00
History of Investigator:	Shuai Shao (Principal Investigator) sshao@auburn.edu Maria Auad (Co-Principal Investigator) Nima Shamsaei (Co-Principal Investigator) Lauren Beckingham (Co-Principal Investigator) Jingyi Zheng (Co-Principal Investigator)
Recipient Sponsored Research Office:	Auburn University 321-A INGRAM HALL AUBURN AL  US  36849-0001 (334)844-4438
Sponsor Congressional District:	03
Primary Place of Performance:	Auburn University 321-A INGRAM HALL AUBURN AL  US  36849-0001
Primary Place of Performance Congressional District:	03
Unique Entity Identifier (UEI):	DMQNDJDHTDG4
Parent UEI:
NSF Program(s):	Major Research Instrumentation, EPSCoR Co-Funding
Primary Program Source:	01002324DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):	1189, 9102, 9150
Program Element Code(s):	118900, 915000
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.083

ABSTRACT

This Major Research Instrumentation (MRI) award supports the acquisition of an X-ray diffraction contrast tomography instrument at Auburn University. This instrument is expected to enable new research, education, and workforce development activities at Auburn University, in the State of Alabama, and in the Southeast region of the United States. The acquired instrument can uniquely reveal the internal microscopic features of a broad range of materials in a non-invasive manner. This is a capability that has been lacking at Auburn University and the surrounding institutions. This instrument will advance several strategic research areas including fatigue and fracture, materials science/engineering, machine learning and data analytics, earth sciences, chemistry, physics, chemical engineering, and environmental engineering. Through these cross-cutting research efforts, this instrument will benefit the society by enabling greener and more efficient advanced manufacturing, fabricating better fitting and more biocompatible bone implants, understanding the impact of global warming on geological materials, and designing stronger and lighter materials. This project will also actively integrate the generated knowledge from the instrument into several outreach and educational activities. This includes activities designed for K-12 students, underrepresented minorities, and women in STEM, as well as graduate/undergraduate education and research training, and short courses for working professionals. The acquisition of the instrument will therefore result in significant broader impact, promoting public awareness and participation in STEM fields.

This X-ray diffraction contrast tomography instrument utilizes the diffracted portion of the incident X-ray beam, that would be discarded by conventional X-ray computed tomography systems, to non-destructively map the orientations of crystalline materials in three dimensions. This instrument will deliver researchers the unique ability of obtaining both the ante mortem three dimensional micro-/defect-structures and their response to excitations - a task that has been dilemmatic via conventional approaches. Thus, the construction of true structure-property relationships of crystalline materials will be enabled by knowing the micro-/defect-structure of the same specimen both before and after testing. Owing to the ubiquitous nature of polycrystalline materials, the instrument can enable significant, new research and education activities at Auburn University and regional institutions in three interdisciplinary research areas: metal additive manufacturing, minerals and synthetic inorganic compounds, and polymers and composites. As an example, for additively manufactured metallic materials, this project can help reveal how fatigue damage initiates, elucidating the competing roles of volumetric defects and microstructure mediated crack nucleation mechanisms. Notably, machine learning and data analytics will be used to assist extracting geometric features of micro-/defect-structure and correlate with material response to excitations, including thermal, mechanical, and environmental.

This project is jointly funded by the Major Instrumentation Research Program (MRI), the Established Program to Stimulate Competitive Research (EPSCoR), and the division of Civil, Mechanical and Manufacturing Innovation (CMMI).

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.

Please report errors in award information by writing to: awardsearch@nsf.gov.