ENERGY-BASED MULTIFUNCTIONAL EFFICIENCY METRIC FOR MULTIFUNCTIONAL COMPOSITE ANODES IN STRUCTURAL BATTERIES
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abstract
A multifunctional efficiency metric is developed using mean-field micromechanics solutions to quantify the multifunctionality of the multifunctional composite anodes. Multifunctional efficiency metrics evaluate the volume and/or mass savings or performance increase when structural and functional materials are replaced by multifunctional materials [1]. The proposed methodology compares the total energy associated with different functionalities, such as elastic strain energy and electric charge energy of the multifunctional materials with the total energy of the single function structural and functional material. To achieve volume and mass savings, the energy of different functionalities is set to be the same between the multifunctional and traditional single- functional materials, and, at the same time, the volume and/or mass of the multifunctional composite needs to be smaller than that of the combination of single- functional materials. The volumes and/or mass savings can be expressed using the properties of multifunctional and traditional single-functional materials. In this work, structural anodes made from silicon nanoparticles, reduced graphene oxide, and aramid nanofibers are used as an example to calculate the mass savings compared to a traditional anode with structural support. The existing multifunctionality metrics are based on the rule of mixtures method, which is adequate for certain geometries and loading conditions, such as in-plane directions for laminate composites. However, if multifunctional composite materials involve multiple phases, material property variation during the charging process, and complex geometries or orientations of the structural and functional phases, a more comprehensive method is required to accurately capture the multifunctional efficiency. The multifunctional efficiency varies significantly during the charging and discharging process. This new metric can provide both upper and lower bounds of multifunctional efficiency. This new multifunctional efficiency metric will help optimize the selection and arrangement of different phases in the multifunctional and quantify the optimization results.
