Symposium SF04—Progress in Materials Genomics, Synthesis and Characterization of Functional Polymers and Polymer Nanocomposites

In the era of data driven material design, processing, structure and properties is inextricably linked with the development and usage of materials data repositories, analytical tools and machine learning methods. This symposium will focus on functional polymeric and polymer nanocomposite materials whose performance is derived from the nanoscale structure and whose data is necessarily complex and high dimensional. Systems of interest include materials that are responsive to thermal, chemical, biological, optical, electro, or magnetic stimulation, as well as those useful in separations, electronics, and medicine. To meet the full promise of these materials, data driven design approaches, and materials data resources are critical. Such design approaches and resources rely on data and modeling of synthesis, structure-property relationships, as well as fundamental characterization of structure and properties. Thus, this symposium will bring together those working in new synthetic methods, the use of optical stimuli to produce materials, control of surface properties through synthesis, production of core-shell and other complex structures, the use of advanced characterization methods together with those working to annotate, store, and reuse this data on these complex soft materials to develop understanding as well as design new materials. The symposium will also host a range of topics including development of data repositories for soft materials and their composites, creation and deployment of associated tools, data driven modeling efforts, and the use of machine learning to bridge length scales. Demonstration cases of materials design loops enabled by MGI (Materials Genome Initiative) methodologies applied to polymers and their composites are encouraged, as are demonstrations using ensemble data and data mining tools to enable fundamental discoveries which illuminate new areas of the processing-structure-property spectrum. Next generation applications of these materials such separation of ions and complex fluids, energy storage and conversion, biomedical imaging agents, and non-linear optical materials are also encouraged.

• Synthesis, characterization, and evaluation of functional nanocomposite materials
• Materials schemas and ontologies and intersection with soft materials
• Structure-property relationships of assembled colloidal systems
• Lessons learned in creating data repositories for soft materials
• Development of common software tools for data descriptors, standardization and translation for soft materials
• Biological applications of multifunctional structures
• Control of the surface chemistry of nanoparticles; its impact on and quantification of dispersion in composites
• Optical stimulation to create functional polymeric materials
• Theory and simulation of mechanical dynamics of organic-inorganic hybrid systems
• The use of machine learning to bridge multi-scale models in polymers and composites
• Characterization of the properties of mesoscale structures, quantum, and non-linear optical materials
• Synthesis, self-assembly, and applications of composite nanoparticles
• Data driven discovery applied to any functional polymer or nanocomposite

• Cyrille Boyer (The University of New South Wales, Australia)
• Juan de Pablo (The University of Chicago, USA)
• Amalie Frischknecht (Sandia National Laboratories, USA)
• Cherie Kagen (University of Pennsylvania, USA)
• Xiao-Min Lin (Argonne National Laboratory, USA)
• Sergiy Minko (University of Georgia, USA)
• Junko Morikawa (Tokyo Institute of Technology, Japan)
• Rampi Ramprasad (Georgia Institute of Technology, USA)
• Javier Read de Alaniz (University of California, Santa Barbara, USA)
• Elena Shevchenko (Argonne National Laboratory, USA)
• Mercedes Taylor (University of Maryland, USA)
• Ryo Yoshida (The University of Tokyo, Japan)