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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:BOARD OF REGENTS OF THE UNIVERSITY OF NEBRASKA
Doing Business As Name:University of Nebraska-Lincoln
PD/PI:
  • Eric Markvicka
  • (402) 472-1617
  • eric.markvicka@unl.edu
Award Date:07/20/2021
Estimated Total Award Amount: $ 354,293
Funds Obligated to Date: $ 354,293
  • FY 2021=$354,293
Start Date:08/01/2021
End Date:07/31/2024
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.041
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:Collaborative Research: Designer Microstructures by Additive Manufacturing of Functional Emulsions
Federal Award ID Number:2054411
DUNS ID:555456995
Parent DUNS ID:068662618
Program:AM-Advanced Manufacturing
Program Officer:
  • Khershed Cooper
  • (703) 292-7017
  • khcooper@nsf.gov

Awardee Location

Street:151 Prem S. Paul Research Center
City:Lincoln
State:NE
ZIP:68503-1435
County:Lincoln
Country:US
Awardee Cong. District:01

Primary Place of Performance

Organization Name:University of Nebraska Lincoln
Street:900 N 16th St., 214 SEC
City:Lincoln
State:NE
ZIP:68588-0511
County:Lincoln
Country:US
Cong. District:01

Abstract at Time of Award

Functional emulsions are an emerging material architecture for creating highly functional elastomer composites that are soft and elastically deformable. However, techniques to control local composition and microstructure of the composite material in emulsions, which ultimately govern material properties and performance of the cured elastomer composite, are lacking. This award supports fundamental research to develop an additive manufacturing technique to control liquid inclusion microstructure in emulsions to achieve unprecedented combinations of thermal, electrical, and mechanical functionalities in elastomer composites. By developing the material and manufacturing knowledge to program inclusion microstructure, new paradigms in composite architecture for next generation functional materials are enabled leading to new applications in electronics and robotics, which benefits the U.S. economy and society. Through a collection of ‘behind the research’ videos generated by team members and a manufacturing workshop for 9-12 grade students, the project provides inspiration and training for future leaders in the emerging fields of additive manufacturing and soft robotics. This project is jointly funded by the Advanced Manufacturing (AM) program and the Established Program to Stimulate Competitive Research (EPSCoR). This project establishes the processing-structure-property relationships of additively manufactured functional emulsions that can be cured into an elastomer composite of complex geometry. This is achieved by creating model emulsion inks, processing methods, and in-situ process monitoring to determine how material composition and printing conditions influence material microstructure. These fundamental processing and material insights are combined with new theoretical models for emulsion extrusion to predict the microstructure of liquid phase inclusions throughout a manufactured part. Liquid metal and glycerol liquid phase inclusions are examined as they present distinctly different fundamental properties, but both offer broad applicability in the field of soft matter engineering. In contrast to rigid carbon black, copper, or silica particle fillers that have fixed shape and size, the on-demand control of liquid inclusion morphology via direct ink write processing provides a new and efficient method to manufacture elastomeric composites. During the manufacturing process, the local material composition and liquid inclusion microstructure are actively tailored to control the electrical, thermal, and mechanical properties of elastomeric composites. By combining printing ink properties and process control with tool design and modeling this work provides new fundamental knowledge to create scalable manufacturing strategies for processing emulsions. This leads to novel model material systems with programmable processing-structure-property relationships to determine physics-based properties of multi-component soft matter. 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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