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Creators/Authors contains: "Yu, Ting"

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  1. ; ; ; ; ; ; ; ; ; ; et al ( , Advanced Materials)
    Free, publicly-accessible full text available April 1, 2023
  2. ; ; ; ; ; ; ; ; ; ; et al ( , Journal of Materials Chemistry A)
    All-solid-state batteries (ASSBs) are viewed as promising next-generation energy storage devices, due to their enhanced safety by replacing organic liquid electrolytes with non-flammable solid-state electrolytes (SSEs). The high ionic conductivity and low Young's modulus of sulfide SSEs make them suitable candidates for commercial ASSBs. Nevertheless, sulfide SSEs are generally reported to be unstable in ambient air. Moreover, instead of gloveboxes used for laboratory scale studies, large scale production of batteries is usually conducted in dry rooms. Thus, this study aims to elucidate the chemical evolution of a sulfide electrolyte, Li 6 PS 5 Cl (LPSCl), during air exposure and tomore »evaluate its dry room compatibility. When LPSCl is exposed to ambient air, hydrolysis, hydration, and carbonate formation can occur. Moreover, hydrolysis can lead to irreversible sulfur loss and therefore LPSCl cannot be fully recovered in the subsequent heat treatment. During heat treatment, exposed LPSCl undergoes dehydration, decomposition of carbonate species, and reformation of the LPSCl phase. Finally, LPSCl was found to exhibit good stability in a dry room environment and was subject to only minor conductivity loss due to carbonate formation. The dry room exposed LPSCl sample was tested in a LiNi 0.8 Co 0.1 Mn 0.1 O 2 |LiIn half-cell, exhibiting no significant loss of electrochemical performance compared with the pristine LPSCl, proving it to be compatible with dry room manufacturing processes.« less
    Free, publicly-accessible full text available March 30, 2023
  3. ; ; ( , Optics Letters)
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  4. ; ; ; ; ; ; ( , The Journal of Physical Chemistry A)
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  5. ; ; ; ; ; ; ; ; ; ; et al ( , IEEE/CVF Conference on Computer Vision and Pattern Recognition)
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  6. ; ; ; ; ; ; ; ; ; ; et al ( , Science of The Total Environment)
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  7. ; ; ; ; ; ( , International Conference on Computer Communications and Networks)
    Accepted Manuscript Full Text Available
  8. ; ; ; ; ( , 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR))
    This paper studies the problem of predicting the distribution over multiple possible future paths of people as they move through various visual scenes. We make two main contributions. The first contribution is a new dataset, created in a realistic 3D simulator, which is based on real world trajectory data, and then extrapolated by human annotators to achieve different latent goals. This provides the first benchmark for quantitative evaluation of the models to predict multi-future trajectories. The second contribution is a new model to generate multiple plausible future trajectories, which contains novel designs of using multi-scale location encodings and convolutional RNNsmore »over graphs. We refer to our model as Multiverse. We show that our model achieves the best results on our dataset, as well as on the real-world VIRAT/ActEV dataset (which just contains one possible future).« less
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  9. ; ; ; ; ( , IEEE International Conference on Computer Communications and Networks)
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  10. ; ; ( , Experimental Neurology)
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