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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:JOHNS HOPKINS UNIVERSITY, THE
Doing Business As Name:Johns Hopkins University
PD/PI:
  • Michael A Bevan
  • (410) 516-7907
  • mabevan@jhu.edu
Award Date:08/20/2019
Estimated Total Award Amount: $ 300,000
Funds Obligated to Date: $ 100,000
  • FY 2019=$100,000
Start Date:09/01/2019
End Date:08/31/2022
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:Coarse Grained Modeling & Control of Colloidal Assembly
Federal Award ID Number:1928950
DUNS ID:001910777
Parent DUNS ID:001910777
Program:Proc Sys, Reac Eng & Mol Therm
Program Officer:
  • Triantafillos Mountziaris
  • (703) 292-2894
  • tmountzi@nsf.gov

Awardee Location

Street:1101 E 33rd St
City:Baltimore
State:MD
ZIP:21218-2686
County:Baltimore
Country:US
Awardee Cong. District:07

Primary Place of Performance

Organization Name:Johns Hopkins University
Street:
City:
State:MD
ZIP:21218-2686
County:Baltimore
Country:US
Cong. District:07

Abstract at Time of Award

The goal of the proposed project is to develop computational models of ensembles of differently shaped colloidal particles as a means to control their assembly into ordered microstructures with few defects. The proposed research may enable metamaterial applications involving micro-structured colloidal-based materials for manipulation of electromagnetic radiation. Example materials include novel reflectors, gratings, polarizers, waveguides, etc. as part of sensors, solar cells, antennas, optical computers, and cloaking devices, which all require periodic structures of different shaped particles with low defect densities. The focus of the research project will be on modeling and control of ellipsoidal and super-ellipsoidal particles to enable a rich set of microstructures. Novel methods for controlling interactions using directional and time varying inputs will be developed to enable precise control of colloidal particle assembly processes. Understanding the thermodynamics and kinetics in colloidal systems is challenging and applying feedback control adds an additional layer to engineering complex responses in such systems. The goal of the proposed research is to develop minimal physically-meaningful models of stochastic dynamics to design model-based feedback control policies for the assembly of ellipsoidal and super-ellipsoidal particles. The objective is to significantly adapt and extend prior approaches to systematically define coarse grained system coordinates that capture structural features while eliminating system symmetries. The feedback control policies will be tested experimentally with tunable kT-scale interactions to design dynamic reversible assembly of different shaped particles into ordered metamaterials. The fundamental understanding of design rules and control parameters for colloidal assembly will provide new general insights beyond what is known from trial-and-error discovery. The project will train students by integrating broad topics in colloid science, fluid dynamics, materials chemistry, advanced metrology/microfabrication, and control. Broadening participation of underrepresented groups in STEM fields will be pursued through weekly mentoring activities at a local elementary after-school program focused on engineering 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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