Polymer Nanocomposites using Discrete Nanoparticles and Bicontinuous Scaffolds: New Strategies for Connective Morphologies and Property Control

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NON-TECHNICAL SUMMARY:Polymer nanocomposites are mixtures of flexible long-chain molecules (polymers) and hard functional particles. Although found in everyday materials from tires to paints, polymer nanocomposites also have future potential as advanced functional materials in applications from energy storage to water purification. This research will provide a fundamental understanding of chemistry, physics and engineering principles that can be brought together to investigate a new type of composite containing a mixture of charged polymers and particles coated with similar or different charged polymers to achieve properties not possible with traditional composites. In short, the overall goal is to promote the progress of science leading to new and improved advanced materials. One fundamental issue is controlling molecular interactions that determine how particles are distributed in a composite material. One challenge with this “mixing” approach is a tendency for particles to aggregate. To overcome this limitation, a second fundamental issue in this study is the fabrication of highly loaded composites where the polymer is incorporated into a scaffold, analogous to water swelling a sponge. To accelerate the discovery of new materials, a smart experimental approach will be used where data will be characterized and fed back immediately to formulate a new composite. This process is continued until the optimum formulation is found. Students performing this research will gain valuable skills in data science, enhancing career opportunities, and learn to utilize valuable resources (materials, equipment) sustainably. Graduate and undergraduate students also participate in annual public events including Nanotechnology Day at Penn, Philly Materials Day, and the Philadelphia Science Festival. A particularly unique program is “First Exposure to Research in STEM,” which provides a structure for introducing first-generation, low-income students to their first research project. TECHNICAL SUMMARY:Polymer nanocomposite (PNC) structure determines their properties. However, the full potential of PNCs is hindered by lack of control over structure-property relationships, partly due to the prevalence of non-equilibrium structures. Here, PNCs containing discrete nanoparticles (NP) in a polymer matrix or those fabricated from bicontinuous, nanoporous scaffolds are designed, processed and characterized to understand their fundamental thermodynamic, interfacial, and dynamic principles. The objectives of this work are to (1) elucidate how brush charge density affects NP dispersion in polyelectrolyte (PE) matrices of varying charge and polarity and explore kinetic pathways towards percolated structures, (2) investigate infiltration kinetics of polar polymers into scaffolds, and (3) develop autonomous experimentation (AE) to accelerate discovery of PNCs with distinct structures. Aim 1 investigates PE-NPs in polymer matrices of increasing polarity. Aim 1a studies PE-NP/matrix miscibility to provide insight into brush-matrix electrostatic interactions. Aim 1b studies phase separation to guide the identification of kinetic pathways that produce percolation of charged brushes. Aims 2a and 2b investigate bicontinuous metal and polymer scaffolds, respectively, infiltrated with polar matrix polymers. Infiltration kinetics and properties are studied as a function of pore confinement and scaffold type. The significance of these studies involves the discovery of pathways for fabricating (bi)continuous structures for enhanced energy storage or water purification applications. In Aim 3, AE-optical microscopy will be used to map the phase diagram of PNCs, whereas AE-GISAXS, in collaboration with scientists from Brookhaven National Laboratory, will identify materials and processing conditions that produce percolated PNC structures with advantageous mechanical properties and conductivity. In summary, fundamental studies of PNCs) combined with data-science-driven characterization will act synergistically to advance knowledge for materials discovery in this project..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.