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 SUMMARY
This 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.
Polymer-matrix composites with functional fillers such as magnetostrictive, piezoelectric and ferroelastic inclusions are important alternatives to the monolithic materials and significantly broaden their application regimes. Composites offer unique combinations of physical and mechanical properties that are not simultaneously attainable with the conventional materials. The properties of the composites not only depend on the properties of respective constituent materials, but also critically depend on the microstructures of the filler inclusions embedded in the matrix. The central issues of composite design and optimization are to establish quantitative microstructure-property relationships and find effective fabrication routes to control the microstructures and optimize the properties. Experimental approach alone is costly, time-consuming, and even difficult for these tasks. This project has developed materials modeling and computer simulation tools to perform systematic computational study of polymer-matrix magnetostrictive composites and related materials, which complements experimental investigations to advance fundamental understanding and rational design of such composite materials. Intellectual Merit: Diffuse Interface Field Approach is adopted to develop a set of computational tools that are able to study important issues covering the whole spectrum of composite design, microstructure control, property optimization, and domain mechanisms. The models are employed to simulate packing behavior and field-directed self-assembly of particle fillers in uncured polymer melts for microstructural control during composite fabrication, and simulate domain-level processes in functionally active fillers for mechanism identification during material service. The results advance our quantitative understanding of processing-microstructure-property relationships and the underlying mechanisms. It is found that filler phase connectivity plays an important role in determining the effective composite properties. Directional alignment of filler particles into pseudo-chains corresponds to optimal microstructures, which can be achieved by field-directed particle self-assembly. The composite properties can be further improved by introducing surface coating to mitigate local field concentration in the filler-matrix interfacial regions. The particle microstructures can be further controlled by capillary forces by using two-liquid-phase polymer melts such as diblock copolymers via phase separation. These computational works complement a large body of existing experimental works, which together help improve design and fabrication of polymer-matrix functional composites. Broader Impact: Polymer-matrix composites are an increasingly important class of materials. This research project develops effective computational tools for computer-aided design and fabrication of advanced composites. The project trained graduate students in computational materials science and engineering. One student supported by this project received the Outstanding Graduate Student Scholar Award, earned Ph.D. degree and continues academic career as postdoc in National Energy Technology Laboratory. The simulation results are used to develop instructional materials to enhance teaching and learning in undergraduate and graduate classrooms, and to develop a new graduate course "Computational Materials Science and Engineering." The research outcomes of this project were presented to high school students and teachers at various summer camp programs, including C-Tech2, Engineering Scholars, ASM Materials Camp-Teachers, School Visits and Demonstrations, and Summer Youth Program.
