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Award Detail

Doing Business As Name:University of Illinois at Urbana-Champaign
  • Qian Chen
  • (217) 300-1137
Award Date:11/30/2017
Estimated Total Award Amount: $ 533,604
Funds Obligated to Date: $ 108,361
  • FY 2018=$108,361
Start Date:03/01/2018
End Date:02/28/2023
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.049
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:CAREER: Imaging and Understanding the Kinetic Pathways in Shape-Anisotropic Nanoparticle Self-Assembly
Federal Award ID Number:1752517
DUNS ID:041544081
Parent DUNS ID:041544081
Program Officer:
  • Birgit Schwenzer
  • (703) 292-4771

Awardee Location

Street:SUITE A
Awardee Cong. District:13

Primary Place of Performance

Organization Name:University of Illinois at Urbana-Champaign
Street:506 S. Wright St.
Cong. District:13

Abstract at Time of Award

Non-Technical Abstract: An emerging theme in materials science is to understand and design artificial materials exhibiting the features of living organisms: adaptive and evolving functional behaviors. Examples include patterned ultra-small antennas that modulate local electromagnetic field strengths upon different sun positions, or automotive "skins" that optimize the aerodynamics of vehicles in varying environments. With support from the Solid State and Materials Chemistry program, the Principal Investigator's NSF CAREER grant is focused on deciphering the rules upon which nanometer-sized building blocks self-organize and reorganize into such adaptive materials. These building blocks are chosen due to the unique potential for miniaturization and the collective properties determined by the structures they organize into. The key enabling innovations of this project are two-fold. First, a novel imaging tool will be used to trace and videotape the building block motions on the fly at up to atomic resolution. Second, the obtained motions will be analyzed to interpret the crosstalk among these building blocks. The obtained fundamental understanding can also be applied to other systems composed of tiny elementary objects such as biological molecules which are critical for human health, or to create new materials that can achieve cheap and clean renewable energy. The project provides training to both undergraduate and graduate students. A "tri-M lab" including Modular lab demos, a Mobile game app, and Movies is utilized as a platform for broad dissemination to the general public. Technical Abstract: The Principal Investigator's long-term goal is to transmute inanimate materials into animate ones, capable of reconfiguring their structure and property on demand. The key challenge in designing reconfigurable materials from nanoscale building blocks lies in understanding the kinetic pathways of their self-assembly. These pathways define how building blocks interact and assemble into targeted structures, i.e. the building block nanoscale interaction-targeted structure relationship. However, the kinetic pathways are associated with how building blocks continuously diffuse and tumble in a solvent, which is both spatiotemporally varying and nanoscopic in nature. Thus, fully understanding these pathways requires real-space, in-situ characterization with high spatiotemporal resolution, which is not offered by existing ex-situ and ensemble methods. The research objective of this CAREER proposal is thus to address this challenge and to quantify the interactions and kinetic pathways governing self-assembly and structural reconfiguration in model systems of anisotropic gold nanoparticles (NPs). The proposed approach is to combine the emergent liquid-phase transmission electron microscopy (TEM) with automated movie analysis methods developed in the PI's group to quantify the dynamics of NP self-assembly. Specifically, this research will (i) capture the self-assembly trajectories of representative anisotropic NPs using low-dose liquid-phase TEM with nanometer and millisecond resolution, (ii) extract from these trajectories hitherto physical parameters, such as NP-NP interaction potentials and self-assembly kinetic pathways, based on high-throughput statistical analysis of these trajectories, and (iii) quantify how diverse stimuli, such as temperature and solvent polarity, affect phase transition dynamics in systems of NPs with reconfigurable polymer coronas, moving towards systems that adapt their structure and functions entirely from the bottom-up. This approach will help establish a quantitative building block-nanoscale interaction-targeted structure relationship for predictive materials design. 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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