14 research outputs found

    Machine-learning-driven advanced characterization of battery electrodes

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    Materials characterization is fundamental to our understanding of lithium ion battery electrodes and their performance limitations. Advances in laboratory-based characterization techniques have yielded powerful insights into the structure–function relationship of electrodes, yet there is still far to go. Further improvements rely, in part, on gaining a deeper understanding of complex physical heterogeneities in the materials. However, practical limitations in characterization techniques inhibit our ability to combine data directly. For example, some characterization techniques are destructive, thus preventing additional analyses on the same region. Fortunately, artificial intelligence (AI) has shown great potential for achieving representative, 3D, multi-modal datasets by leveraging data collected from a range of techniques. In this Perspective, we give an overview of recent advances in lab-based characterization techniques for Li-ion electrodes. We then discuss how AI methods can combine and enhance these techniques, leading to substantial acceleration in our understanding of electrodes

    Catalysing sustainable fuel and chemical synthesis

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    Concerns over the economics of proven fossil fuel reserves, in concert with government and public acceptance of the anthropogenic origin of rising CO2 emissions and associated climate change from such combustible carbon, are driving academic and commercial research into new sustainable routes to fuel and chemicals. The quest for such sustainable resources to meet the demands of a rapidly rising global population represents one of this century’s grand challenges. Here, we discuss catalytic solutions to the clean synthesis of biodiesel, the most readily implemented and low cost, alternative source of transportation fuels, and oxygenated organic molecules for the manufacture of fine and speciality chemicals to meet future societal demands

    Cryogenic Laser Ablation Reveals Short-Circuit Mechanism in Lithium Metal Batteries

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    The dramatic 50% improvement in energy density that Li-metal anodes offer in comparison to graphite anodes in conventional lithium (Li)-ion batteries cannot be realized with current cell designs because of cell failure after a few cycles. Often, failure is caused by Li dendrites that grow through the separator, leading to short circuits. Here, we used a new characterization technique, cryogenic femtosecond laser cross sectioning and subsequent scanning electron microscopy, to observe the electroplated Li-metal morphology and the accompanying solid electrolyte interphase (SEI) into and through the intact coin cell battery's separator, gradually opening pathways for soft-short circuits that cause failure. We found that separator penetration by the SEI guided the growth of Li dendrites through the cell. A short-circuit mechanism via SEI growth at high current density within the separator is provided. These results will inform future efforts for separator and electrolyte design for Li-metal anodes

    Gibbs-Thomson Effect in Planar Nanowires: Orientation and Doping Modulated Growth.

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    Epitaxy-enabled bottom-up synthesis of self-assembled planar nanowires via the vapor-liquid-solid mechanism is an emerging and promising approach toward large-scale direct integration of nanowire-based devices without postgrowth alignment. Here, by examining large assemblies of indium tin oxide nanowires on yttria-stabilized zirconia substrate, we demonstrate for the first time that the growth dynamics of planar nanowires follows a modified version of the Gibbs-Thomson mechanism, which has been known for the past decades to govern the correlations between thermodynamic supersaturation, growth speed, and nanowire morphology. Furthermore, the substrate orientation strongly influences the growth characteristics of epitaxial planar nanowires as opposed to impact at only the initial nucleation stage in the growth of vertical nanowires. The rich nanowire morphology can be described by a surface-energy-dependent growth model within the Gibbs-Thomson framework, which is further modulated by the tin doping concentration. Our experiments also reveal that the cutoff nanowire diameter depends on the substrate orientation and decreases with increasing tin doping concentration. These results enable a deeper understanding and control over the growth of planar nanowires, and the insights will help advance the fabrication of self-assembled nanowire devices
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