The assembly of colloidal nano- or micro-particles into perfectly ordered periodic structures provides a basis for manufacturing photonic band gap materials and other multi-scale meta-materials with unique electric, magnetic, and optical properties. Although proof-of-concept materials have been made in laboratories to verify their amazing properties, no existing process is yet sufficiently controllable, scalable, and robust for high-throughput manufacturing to enable commercial applications. The fundamental limitation to assembling colloidal components into ordered structures is the complex interplay of thermal motion, interparticle interactions, and external fields that lead to defect-rich and often arrested states. We propose a new approach to the meta-material assembly problem that combines expertise from four separate scientific fields that traditionally have had minimal interaction. Mathematical models of the colloidal systems, represented as free energy landscapes (FELs) in a few key variables that characterize the state of the assembly process, will be constructed using data from advanced microscopic imaging and analysis tools. The FELs will in turn be used as input to rigorous process control algorithms, developed for stochastic processes, that will navigate the landscapes to yield defect-free products. This strategy will be demonstrated and refined on prototype lab-scale reactors, using real-time digital microscopic imaging as the sensor and programmable particle-particle interaction potentials & electric fields as the actuators, to produce meta-materials.

In terms of broader impact, successful development of fundamental tools for large-scale assembly of defect-free colloidal crystals has the potential to produce revolutionary technologies (e.g. optical computing, energy harvesting, sub-diffraction limit imaging, invisibility cloaking) not unlike the creation of single crystal silicon to enable integrated circuits and modern computing. No existing processes today are capable of producing such materials at a commercial scale despite 25 years of trial-and-error efforts. A strategy of rigorous real-time control using quantitatively accurate process models, like that proposed here, is required. The education and outreach activities will incorporate integrate concepts from modeling, control, simulations, and experiments, including rich visual data from colloid experiments (e.g. images, videos) and physics-based simulations (e.g. renderings, animations) to provide intuitive education/training for students at all levels.

Project Start
Project End
Budget Start
2011-09-01
Budget End
2015-08-31
Support Year
Fiscal Year
2011
Total Cost
$406,401
Indirect Cost
Name
University of Massachusetts Amherst
Department
Type
DUNS #
City
Amherst
State
MA
Country
United States
Zip Code
01003