4 research outputs found

    Bridging Nano and Micro-scale X-ray Tomography for Battery Research by Leveraging Artificial Intelligence

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    X-ray Computed Tomography (X-ray CT) is a well-known non-destructive imaging technique where contrast originates from the materials' absorption coefficients. Novel battery characterization studies on increasingly challenging samples have been enabled by the rapid development of both synchrotron and laboratory-scale imaging systems as well as innovative analysis techniques. Furthermore, the recent development of laboratory nano-scale CT (NanoCT) systems has pushed the limits of battery material imaging towards voxel sizes previously achievable only using synchrotron facilities. Such systems are now able to reach spatial resolutions down to 50 nm. Given the non-destructive nature of CT, in-situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area, and volume expansion during battery operation or cycling. Combined with powerful Artificial Intelligence (AI)/Machine Learning (ML) analysis techniques, extracted 3D tomograms and battery-specific morphological parameters enable the development of predictive physics-based models that can provide valuable insights for battery engineering. These models can predict the impact of the electrode microstructure on cell performances or analyze the influence of material heterogeneities on electrochemical responses. In this work, we review the increasing role of X-ray CT experimentation in the battery field, discuss the incorporation of AI/ML in analysis, and provide a perspective on how the combination of multi-scale CT imaging techniques can expand the development of predictive multiscale battery behavioral models.Comment: 33 pages, 5 figure

    High Performance Printed AgO-Zn Rechargeable Battery for Flexible Electronics

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    The rise of flexible electronics calls for cost-effective and scalable batteries with good mechanical and electrochemical performance. In this work, we developed printable, polymer-based AgO-Zn batteries that feature flexibility, rechargeability, high areal capacity, and low impedance. Using elastomeric substrate and binders, the current collectors, electrodes, and separators can be easily screen-printed layer-by-layer and vacuum-sealed in a stacked configuration. The batteries are customizable in sizes and capacities, with the highest obtained areal capacity of 54 mAh/cm2 for primary applications. Advanced micro-CT and EIS were used to characterize the battery, whose mechanical stability was tested with repeated twisting and bending. The batteries were used to power a flexible E-ink display system that requires a high-current drain and exhibited superior performance than commercial coin-cell batteries. The developed battery presents a practical solution for powering a wide range of electronics and holds major implications for the future development of practical and high-performance flexible batteries
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