95 research outputs found

    Quaternary ammonium cationic polymer as a superior bifunctional binder for lithium – sulfur batteries and effects of counter anion

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    Bifunctional polymer binders featured with both strong binding and superior polysulfide trapping properties are highly desired for the fabrication of sulfur cathodes with suppressed polysulfide shuttling in Li–S batteries. In this paper, we have explored the potential of a quaternary ammonium cationic polymer, polydiallyldimethylammonium (PDADMA-X; X = T, B, P, and Cl) with different counter anions (TFSI–, BF4−, PF6−, and Cl−, respectively) as the bifunctional binder. We have also revealed the dramatic effects of the counter anion on the performance of the cationic polymer binder. PDADMA-X's containing the former three weakly associating anions have been demonstrated to show polysulfide adsorption capability. In particular, PDADMA-T having the largest, least interacting TFSI– anion shows the optimum performance, with strong binding strength and the best polysulfide adsorption capability. Relative to commercial PVDF and PDADMA-X's of other counter anions, it offers sulfur cathodes with lowered polarization, higher discharge capacity, significantly better capacity retention, and improved cycling stability. With its convenient synthesis from commercially available PDADMA-Cl, cationic PDADMA-T having the TFSI– anion is a promising bifunctioal binder for sulfur cathodes in practical Li-sulfur batteries

    Nontrivial Effects of “Trivial” Parameters on the Performance of Lithium–Sulfur Batteries

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    A robust lithium-sulfur (Li–S) battery is constituted by a wide range of optimized fundamental parameters (e.g., amount of electrolyte, electrolyte additive, sulfur loading density, and the size of sulfur particles). In this paper, some other often-neglected “trivial” parameters (including assembly pressure of the coil cells, thickness of spring/lithium foil in coin cells, sheet number of separator, and cut-off voltage) of Li–S batteries have been demonstrated to show pronounced effects on the battery performance. Our results indicate that the coin cell assembly pressure and sheet number of the separator play the important roles in suppressing polysulfide shuttling over battery cycling, which improves significantly the cycling life of Li–S batteries. The thickness of springs/lithium foils also affects the battery performance greatly. When switching the cut-off voltage of 1.5–3.0 V to narrower ones (1.7–2.5 V or 1.8–2.6 V), the cycling life of batteries at 0.2 C can be further enhanced to >300 cycles while with no drastic polysulfide shuttling. Adjusting these trivial parameters can thus synergistically improve the cycling performance of Li–S batteries

    Dual graph regularized latent low-rank representation for subspace clustering

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    Low-rank representation (LRR) has received considerable attention in subspace segmentation due to its effectiveness in exploring low-dimensional subspace structures embedded in data. To preserve the intrinsic geometrical structure of data, a graph regularizer has been introduced into LRR framework for learning the locality and similarity information within data. However, it is often the case that not only the high-dimensional data reside on a non-linear low-dimensional manifold in the ambient space, but also their features lie on a manifold in feature space. In this paper, we propose a dual graph regularized LRR model (DGLRR) by enforcing preservation of geometric information in both the ambient space and the feature space. The proposed method aims for simultaneously considering the geometric structures of the data manifold and the feature manifold. Furthermore, we extend the DGLRR model to include non-negative constraint, leading to a parts-based representation of data. Experiments are conducted on several image data sets to demonstrate that the proposed method outperforms the state-of-the-art approaches in image clustering.Ming Yin, Junbin Gao, Zhouchen Lin, Qinfeng Shi, and Yi Gu

    CUHK electronic theses & dissertations collection

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    Huang, Junbin.Thesis M.Phil. Chinese University of Hong Kong 2015.Includes bibliographical references (leaves 72-76).Abstracts also in Chinese.Title from PDF title page (viewed on 11, November, 2016)
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