This award supports computational and theoretical research and education to develop greatly accelerated and enhanced simulation methods for suspensions of anisotropic colloids.

Significant progress has been made in the fabrication of colloids with anisotropic interactions, that is, particles with aspherical shapes and/or inhomogeneous surface chemistry. One of the goals of such research is to control the structure of self-assembled materials through manipulation of the building blocks. However, it has proven difficult to correlate the nature of individual colloids with the structure of the resulting aggregates. Computer simulations are able to guide and interpret experimental work, but currently deal almost exclusively with idealized, monodisperse systems. From the experimental perspective, it has become clear that an important route towards the design of complex structures arises from the combination of multiple components, rather than from the use of a single highly complicated type of building block. The PI aims to bridge this gap by means of new computational methods that can span a wide range of time and length scales that are inaccessible to current algorithms. A focus of this work will be on developing a new class of highly efficient cluster Monte Carlo algorithms and to extend and apply simulation methods for the hydrodynamics of colloids in suspension.

A second shortcoming of current modeling efforts is the neglect of kinetic effects due to the solvent. "Patchy" interactions can cause particles to remain trapped in nonequilibrium states, and hydrodynamic interactions determine the pathways along which particles encounter each other. The PI plans to extend recent techniques for the inclusion of hydrodynamics to systems containing colloids with anisotropic boundary conditions and interactions.

Jointly, these two developments would provide a comprehensive framework for the modeling of hydrodynamics and thermodynamics of multicomponent systems of anisotropic colloids. This framework will be exploited to gain physical insights and make direct connections to experiments. The PI will continue to work in close collaboration with experimentalists.

The simulation methods developed in this research will have an impact beyond the scope of this program by facilitating the computational study of broad classes of complex fluids, ranging from soft condensed-matter systems to biologically relevant solutions. Cluster algorithms are now routinely incorporated in the simulation course taught by the PI to undergraduates of various backgrounds, bringing new methods to the classroom. The PI has initiated and will continue a strong educational outreach program involving teaching basic science classes to adult students pursuing a high-school diploma and introductory thermodynamics to second-chance students at Harper College, a community college in Palatine, Illinois.

NONTECHNICAL SUMMARY

This award supports computational and theoretical research and education to develop greatly accelerated and enhanced simulation methods for particles of various shapes suspended in fluids. These materials systems, or colloids, can be used to fabricate materials with novel properties starting from building block particles that are some ten thousand or more times smaller than the diameter of a human hair. Because of the way the particles interact in the fluid, they can assemble themselves into a material. Experimentalists seek to engineer the building blocks and the fluid environment to achieve a material with desired properties. Computer simulations hold promise to guide and possibly design materials based on this method. So far, computer simulations have largely focused on spherical particles. The PI aims to develop new simulation techniques that can accommodate particles of different shapes. The shape of the particle is controlled by its geometry and the nature of its interactions with other particles. The simulation methods will also include the fluid in which the particles are suspended. The PI also aims to overcome the need for simulation methods that can properly include processes that occur over a wide range of length and time scales. The work will be carried out in close connection with experimentalists.

This is fundamental research to understand through computation how particles organize themselves in solution. It contributes to the broader effort of exploiting this knowledge to develop new ways to fabricate materials with novel properties and using computation to enable their purposeful design. The realization of this capability would have a significant impact on American competitiveness.

The simulation methods developed in this research will have an impact on the computational study of other complex fluids in other disciplines, notably chemistry and biology. The PI will continue to incorporate algorithms developed in the course of this research into the simulation course that he teaches to undergraduates of various backgrounds. The PI has initiated, and will continue, a strong educational outreach program involving teaching basic science classes to adult students pursuing a high-school diploma and introductory thermodynamics to second-chance students at Harper College, a community college in Palatine, Illinois.

Project Report

This project has focused on the behavior of colloids (particles that have a size similar to the wavelength of visible light). These particles are now widely studied as promising objects to realize "self-assembly," a process in which complex structures spontaneously form when the right components (building blocks) are brought together (often suspended in a liquid environment). Self-assembly is familiar from biology or from basic processes we observe in our surroundings, such a crystallization, but it is not the process through which most of our materials are currently manufactured. To realize self-assembly of any but the simplest structures, we most likely need to use a combination of different types of building blocks (e.g, large and small) and we need building blocks that connect to each other via specific binding sites, known as "patches." To go beyond experimental trial-and-error, it would be ideal to predict structures that form via computer simulations. The present project has provided the tools to do just that: we have developed algorithms that permit simulations of mixtures of anisotropic particles, and unlike existing methods, our approach is highly efficient even if the mixture contains particles of very different dimensions. We have exploited these algorithms to make a number of important discoveries, several of them in close collaboration with experimental research groups: We have demonstrated that completely regular structures can form not merely because they are the thermodynamically most stable structure, but because of the sequence in which smaller clusters form. Once these smaller clusters have connected, the pathways to convert them to even more favorable structures can be insurmountably high. (Science 2011.) We have shown that ordered structures can form even while the building blocks within those structures continue to move (driven by an external magnetic field as well as by the motion of the surrounding building blocks), and that the structures that form are controlled by rules that follow from the mathematical field of synchronization. This insight can be exploited, as we showed, to selectively destroy and reconfigure various self-assembled aggregates of colloids. (Nature 2012.) Interestingly, these investigations had a spin-off well beyond the field of colloids: the systematic investigation of self-assembly of many particles provided us with the tools to investigate and explain the self-organization of bacteria on surfaces – the initial stage of biofilm formation. In collaboration with experimental researchers at the University of California at Los Angeles and the University of Washington at Seattle, we demonstrated how these bacterial trajectories are influenced by the deposition of sugars on the surface. (Nature 2013.) In summary, this project has provided new computational tools for the investigation of self-assembly and self-organization of system consisting of numerous entities, behavior that is often summarized as "collective behavior." We have taken advantage of these tools to clarify aspects of such behavior in a variety of systems, with a particular emphasis on understanding how to create new materials. As a follow-up on this 3-year project we are now incorporating the next level of particle interactions to further unravel the

Agency
National Science Foundation (NSF)
Institute
Division of Materials Research (DMR)
Application #
1006430
Program Officer
Daryl Hess
Project Start
Project End
Budget Start
2010-09-15
Budget End
2014-08-31
Support Year
Fiscal Year
2010
Total Cost
$285,000
Indirect Cost
Name
Northwestern University at Chicago
Department
Type
DUNS #
City
Chicago
State
IL
Country
United States
Zip Code
60611