Computational Study for Optimizing Microstructures and Properties of Polymer-Matrix Magnetostrictive Composite Materials

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TECHNICAL SUMMARY:This award supports theoretical and computational research and education on composite magnetostrictive materials. The PI will use phase field materials modeling methods to study the properties and microstructure of polymer matrix magnetostrictive composites. The work may have impact on the processing of magnetostrictive composite materials. This computational research focuses on technologically important composites that are composed of giant magnetostrictive Terfenol-D particles embedded in an epoxy resin matrix. The properties of these systems, in a cured epoxy resin, are studied by assuming a free-energy of the magnetostrictive composite system that includes the magnetocrystalline anisotropy energy, the domain-wall energy, the long-range magnetostatic dipolar interactions, the interactions of the magnetic dipoles with an external magnetic field, and the magneto elastic energy. The temporal evolution of the magnetization is determined by solving the Landau-Lifshitz-Gilbert equation. A similar technique is used to determine strategies for field-optimized assembly and control of the Terfenol-D nanoparticles in the uncured epoxy resin. In this case short-range interactions, which account for viscous drag on each particle, are included which ultimately provides a force and torque on each of the nanoparticles. Understanding such materials furthers technologies aimed at the development and application of magnetic sensors, actuators, and transducers. Polymer-bonded Terfenol-D composites significantly increase the electrical resistivity, reduce eddy current loss, improve mechanical toughness and tensile strength, and provide magnetostrictive strains comparable to that of monolithic Terfenol-D alloy, and extend the operational bandwidth. A thrust of this research is a detailed understanding of the connection between materials properties of magnetostrictive composites and microstructure and aims to address how microstructure can be controlled. This computational research complements and is closely related to a large body of experimental findings in both monolithic Terfenol-D and polymer matrix magnetostrictive composites, which together enable effective computer-aided design and fabrication of the composites. NON-TECHNICAL SUMMARYThis award supports theoretical and computational research on the magnetic properties of a class of polymer-matrix composite materials with an aim to understanding the relationship between the structure of the composite and its properties, and how they can be controlled. Polymer-matrix composites are important materials, composed of magnetic particles embedded in an epoxy resin, that offer a variety of advantages over crystalline materials composed of the same magnetic material. They are less susceptible to degradation and mechanical failure but still respond to applied magnetic fields in a way that is comparable to conventional crystalline materials. This research has potential impact on sensor and transducer technologies and will also develop and distribute computational tools for computational materials design and fabrication of advanced magnetostrictive composites. The research is integrated with educational activities that train future computational materials scientists, develops instructional materials, and distributes free source codes to the larger community of scientists in this field. Outreach activities to high school students and teachers are also included in this effort.