ABSTRACT
Multifunctional structural batteries are of high and emerging interest in a wide variety of high-strength and lightweight applications. Structural batteries typically use pristine carbon fiber as the negative electrode, functionalized carbon fiber as the positive electrode, and a mechanically robust lithium-ion transporting electrolyte. However, electrochemical cycling of carbon fibre-based positive electrodes is still limited to tests in liquid electrolytes, which does not allow for to introduction of multifunctionality in real terms. To overcome these limitations, structural batteries with a structural battery electrolyte (SBE) are developed. This approach offers massless energy storage. The electrodes are manufactured using economically friendly, abundant, cheap, and non-toxic iron-based materials like olivine LiFePO4. Reduced graphene oxide, renowned for its high surface area and electrical conductivity, is incorporated to enhance the ion transport mechanism. Furthermore, a vacuum-infused solid-liquid electrolyte is cured to bolster the mechanical strength of the carbon fibers and provide a medium for lithium-ion migration. Electrophoretic deposition is selected as a green process to manufacture the structural positive electrodes with homogeneous mass loading. A specific capacity of 112 mAh g-1 can be reached at C/20, allowing the smooth transport of Li-ion in the presence of SBE. The modulus of positive electrodes exceeded 80 GPa. Structural battery-positive half-cells are demonstrated across various mass-loadings, enabling them to be tailored for a diverse array of applications in consumer technology, electric vehicles, and aerospace sectors.
ABSTRACT
The present work describes a methodology to compute equivalent volumes representing the microstructure of 3D-printed continuous fiber-reinforced thermoplastics, based on a statistical characterization of the fiber distribution. In contrast to recent work, the methodology herein presented determines the statistically equivalent fiber distribution directly from cross-section micrographs, instead of generating random fiber arrangements. For this purpose, several regions, with different sizes and from different locations, are cropped from main cross-section micrographs and different spatial descriptor functions are adopted to characterize the microstructures in terms of agglomeration and periodicity of the fibers. Detailed information about the adopted spatial descriptors and the algorithm implemented to identify the fiber distribution, as well as to define the location of cropped regions, are given. From the obtained statistical characterization results, the minimum size of the equivalent volume required to be representative of the fiber distribution, which is found in the cross-section micrographs of 3D-printed composite materials, is presented. To support the findings, as well as to demonstrate the effectiveness of the proposed methodology, the homogenized properties are also computed using representative equivalent volumes obtained in the statistical characterization and the results are compared to those experimentally measured, which are available in the literature.
ABSTRACT
This data in brief article describes a dataset used for an X-ray computer tomography aided engineering process consisting of X-ray computer tomography data and finite element models of non-crimp fabric glass fibre reinforced composites. Additional scanning electron microscope images are provided for the validation of the fibre volume fraction. The specimens consist of 4 layers of unidirectional bundles each supported by off-axis backing bundles with an average orientation on ±80° The finite element models, which were created solely on the image data, simulate the tensile stiffness of the samples. The data can be used as a benchmark dataset to apply different segmentation algorithms on the X-ray computer tomography data. It can be further used to run the models using different finite element solvers.
