Award Abstract # 2037026
FMRG: Manufacturing ADvanced Electronics through Printing Using Bio-based and Locally Identifiable Compounds (MADE-PUBLIC)

NSF Org: CMMI
Division of Civil, Mechanical, and Manufacturing Innovation
Recipient: UNIVERSITY OF CHICAGO
Initial Amendment Date: August 31, 2020
Latest Amendment Date: April 15, 2025
Award Number: 2037026
Award Instrument: Continuing Grant
Program Manager: Siddiq Qidwai
sqidwai@nsf.gov
 (703)292-2211
CMMI
 Division of Civil, Mechanical, and Manufacturing Innovation
ENG
 Directorate for Engineering
Start Date: January 1, 2021
End Date: December 31, 2026 (Estimated)
Total Intended Award Amount: $9,150,001.00
Total Awarded Amount to Date: $9,249,981.00
Funds Obligated to Date: FY 2020 = $6,150,001.00
FY 2022 = $750,000.00

FY 2023 = $750,000.00

FY 2024 = $849,980.00

FY 2025 = $750,000.00
History of Investigator:
  • Junhong Chen (Principal Investigator)
    junhongchen@uchicago.edu
  • Stuart Rowan (Co-Principal Investigator)
  • Mark Hersam (Co-Principal Investigator)
  • Santanu Chaudhuri (Co-Principal Investigator)
  • Elizabeth Ainsworth (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Chicago
5801 S ELLIS AVE
CHICAGO
IL  US  60637-5418
(773)702-8669
Sponsor Congressional District: 01
Primary Place of Performance: University of Chicago
Chicago
IL  US  60637-2612
Primary Place of Performance
Congressional District:
01
Unique Entity Identifier (UEI): ZUE9HKT2CLC9
Parent UEI: ZUE9HKT2CLC9
NSF Program(s): OFFICE OF MULTIDISCIPLINARY AC,
SSA-Special Studies & Analysis,
FM-Future Manufacturing
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
01002526DB NSF RESEARCH & RELATED ACTIVIT

01002021DB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT

01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 075Z, 062Z, 8614, 054Z, 094Z, 8037, 8399, 7573, 095Z, 8396, 7237, 079Z, 024E, 7203, 8004, 144E, 7569
Program Element Code(s): 125300, 138500, 142Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041, 47.049

ABSTRACT

This Future EcoManufacturing research grant will enable a future intelligent, scalable, and democratized manufacturing paradigm that allows for distributed printing of low-cost, biodegradable, and recyclable electronic devices using locally identifiable resources, such as bio-based materials derived from plants. These electronic devices are critical components in the rapidly evolving Internet of Things (IoT). The distributed manufacturing can lower overall device costs (by saving transportation costs) and make the supply chain more resilient during disruptions (e.g., during a pandemic). This project will demonstrate as a prototype the distributed printing of a lithium-ion battery (LIB) - powered chemical sensors using plant-derived inks. The printed devices will be used for monitoring growth conditions of hydronic plants that are used to derive the inks. The same platform can be used to print many other sophisticated, biodegradable/recyclable electronic devices using bio-based materials through customization and active learning. Through partnership with community colleges, Manufacturing USA Institutes, and manufacturing incubators, the project aims to educate, train, engage, and excite student audiences and the public on the future sustainable manufacturing through several new, tailored initiatives, such as a cross-institutional certificate program, printable electronics hackathon and DIY initiative, and citizen science competition.

The goal of the project is to enable a manufacturing supply chain from precision agriculture/hydroponics to advanced biodegradable and recyclable electronics. The project will lead to major science advances in three domains: precision growth of plants, manufacturing of tailored bio-based inks, and sustainable production of printable electronics. As a convergent research program, the project will further lead to value-added transferrable and scalable scientific advancements, including novel artificial intelligence/machine learning (AI/ML) algorithms for manufacturing, a framework for designing sustainable and systematically optimized manufacturing processes, and techniques for incorporating heterogeneous data into manufacturing data systems while automatically refining the models. Learned models will correlate plant phenotypes and growth conditions with cellulose and lignin extraction, connect ink formulation with desired ink properties, and associate printing parameters with electronic device performance and quality. The project will lead to an open-source biomaterials-based electronics manufacturing data infrastructure (BEMDI) that fosters innovation through building a community of innovators, educators, and industry partners interested in manufacturing bio-based printable electronics. This Future Manufacturing research is supported by the Divisions of Civil, Mechanical and Manufacturing Innovation (CMMI), Biological Sciences (BIO), Emerging Frontiers and Multidisciplinary Activities (EFMA), Materials Research (DMR), Electrical Communications and Cyber Systems (ECCS), Engineering Education and Centers (EEC), and Mathematical Sciences (DMS).

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 41)
You, Haoyang and Hui, Janan and Zhou, Yilun and Vittore, Kayla and Zhang, Jinrui and Chaney, Lindsay E and Chinta, Sritarun and Zhao, Yunhao and Lim, Gilhwan and Lee, DoKyoung and Ainsworth, Elizabeth A and Dunn, Jennifer B and Dravid, Vinayak P and Hersa "Sustainable Production of BiomassDerived Graphite and Graphene Conductive Inks from Biochar" Small , 2024 https://doi.org/10.1002/smll.202406669 Citation Details
Zhang, Hengrui and Chen, Wei and Iyer, Akshay and Apley, Daniel W. and Chen, Wei "Uncertainty-aware mixed-variable machine learning for materials design" Scientific Reports , v.12 , 2022 https://doi.org/10.1038/s41598-022-23431-2 Citation Details
Zhang, Jinrui and Liang, Chao and Dunn, Jennifer B. "Graphite Flows in the U.S.: Insights into a Key Ingredient of Energy Transition" Environmental Science & Technology , v.57 , 2023 https://doi.org/10.1021/acs.est.2c08655 Citation Details
Wang, Lei and Anderson, John S "Redox Chemistry Mediated Control of Morphology and Properties in Electrically Conductive Coordination Polymers: Opportunities and Challenges" Chemistry of Materials , v.36 , 2024 https://doi.org/10.1021/acs.chemmater.4c00101 Citation Details
Chaney, Lindsay E. and Hyun, Woo Jin and Khalaj, Maryam and Hui, Janan and Hersam, Mark C. "Fully Printed, HighTemperature MicroSupercapacitor Arrays Enabled by a Hexagonal Boron Nitride Ionogel Electrolyte" Advanced Materials , 2023 https://doi.org/10.1002/adma.202305161 Citation Details
Chaney, Lindsay E and van_Beek, Anton and Downing, Julia R and Zhang, Jinrui and Zhang, Hengrui and Hui, Janan and Sorensen, E Alexander and Khalaj, Maryam and Dunn, Jennifer B and Chen, Wei and Hersam, Mark C "Bayesian Optimization of Environmentally Sustainable Graphene Inks Produced by Wet Jet Milling" Small , v.20 , 2024 https://doi.org/10.1002/smll.202309579 Citation Details
Chen, Bolin and Johnson, Zachary T. and Sanborn, Delaney and Hjort, Robert G. and Garland, Nate T. and Soares, Raquel R. and Van Belle, Bryan and Jared, Nathan and Li, Jingzhe and Jing, Dapeng and Smith, Emily A. and Gomes, Carmen L. and Claussen, Jonatha "Tuning the Structure, Conductivity, and Wettability of Laser-Induced Graphene for Multiplexed Open Microfluidic Environmental Biosensing and Energy Storage Devices" ACS Nano , v.16 , 2022 https://doi.org/10.1021/acsnano.1c04197 Citation Details
Chen, Junhong and Pu, Haihui and Hersam, Mark C. and Westerhoff, Paul "Molecular Engineering of 2D Nanomaterial FieldEffect Transistor Sensors: Fundamentals and Translation across the Innovation Spectrum" Advanced Materials , v.34 , 2022 https://doi.org/10.1002/adma.202106975 Citation Details
Diaz-Arauzo, Santiago and Downing, Julia R and Tsai, Daphne and Trost, Jenna and Hui, Janan and Donahue, Kevin and Antonopoulos, Nick and Chaney, Lindsay E and Dunn, Jennifer B and Hersam, Mark C "Ultrahigh-throughput cross-flow filtration of solution-processed 2D materials enabled by porous ceramic membranes" Materials Horizons , v.11 , 2024 https://doi.org/10.1039/D4MH01205D Citation Details
Downing, Julia R. and DiazArauzo, Santiago and Chaney, Lindsay E. and Tsai, Daphne and Hui, Janan and Seo, JungWoo T. and Cohen, Deborah R. and Dango, Michael and Zhang, Jinrui and Williams, Nicholas X. and Qian, Justin H. and Dunn, Jennifer B. and Hers "CentrifugeFree Separation of SolutionExfoliated 2D Nanosheets via CrossFlow Filtration" Advanced Materials , v.35 , 2023 https://doi.org/10.1002/adma.202212042 Citation Details
Fengxue Zhang and Jialin Song and James Bowden and Alexander Ladd and Yisong Yue and Thomas A. Desautels and Yuxin Chen "Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation" , 2023 Citation Details
(Showing: 1 - 10 of 41)

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