This award was made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." The Divisions of Materials Research and Chemistry jointly support this award for computational research and education. The research is being done in collaborations with groups at NIST, University of Chicago, and the University of Rome.
New nanostructured materials offer properties unattainable by traditional approaches, impacting a broad range of fields from computer technology to health care. The growing field of polymer nanocomposites has demonstrated that the addition of a small fraction of nanoparticles to polymeric materials can lead to dramatic changes in modulus, strength, and other properties, which in turn has led to real-world applications.
This research will address three fundamental issues: What is the underlying mechanism controlling nanoparticle clustering and cluster structure in a polymer matrix? How can knowledge of the clustering properties be used to improve the modeling of nanocomposite materials? How do design choices of the nanoparticles impact the overall materials properties? Computational molecular modeling is ideally suited to probe nanocomposite behavior at the molecular level. Hence the proposed research will utilize distributed Beowulf computing resources to carry out innovative modeling that both exploits existing methods and develops new approaches.
Recently, it has become apparent that nanoparticle clustering in a polymer nanocomposite has, in many cases, a strong similarity to the phenomena of gelation. While traditional phase separation is well understood in the framework of statistical mechanics, the formation of gel phases is comparatively poorly understood. Hence, to understand and eventually control the formation and morphology of nanoparticle clusters, simple model systems are needed in which model parameters can be unambiguously related to the properties of the gel. The insights into the basic mechanisms of gelation will be folded into the design of new models that improve the length and time scales that can be computationally studied for nanocomposite materials. Relating the parameters of the largely homogeneous polymer matrix to general interactions leading to gel formation will enable the development of implicit models for bulk polymer interactions. Such implicit models would dramatically reduce the amount of computational resources that must be dedicated to simulating the molecular detail of polymer chains.
The research will be integrated with educational activities via a new program on computational modeling at Wesleyan University. Connections will also be made with high school students. %%% This award was made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." The Divisions of Materials Research and Chemistry jointly support this award for computational research and education. The research is being done in collaborations with groups at NIST, University of Chicago, and the University of Rome.
New nanostructured materials offer properties unattainable by traditional approaches, impacting a broad range of fields from computer technology to health care. The growing field of polymer nanocomposites has demonstrated that the addition of a small fraction of nanoparticles to polymeric materials can lead to dramatic changes in modulus, strength, and other properties, which in turn has led to real-world applications.
The computational research supported by this award will study the unique properties of polymers with nanoparticles dispersed in them in order to gain an understanding that may lead to the design of novel new materials. The research will be integrated with educational activities via a new program on computational modeling at Wesleyan University. Connections will also be made with high school students. ***
