Conventional aqueous batteries usually suffer from serious capacity loss under subzero conditions owing to the freeze of electrolytes. To realize the utilization of aqueous batteries in extremely cold climates, low-temperature aqueous battery systems have to be developed. Herein, an aqueous Pbquinone battery based on p-chloranil/reduced graphene oxide (PCHL-rGO) in H 2 SO 4 electrolyte is developed. Such aqueous Pb/PCHL-rGO batteries display H + insertion chemistry, which endows the batteries with fast reaction kinetics and high rate capability. In addition, the hydrogen bonds between water molecules can be significantly damaged in electrolyte by modulating the interaction between SO 4 2À and water molecules, lowering the freezing point of electrolyte. As a result, the Pb/ PCHL-rGO batteries deliver extraordinary electrochemical performance even at À70 8C. This work will broaden the horizons of aqueous batteries and open up new opportunities to construct low-temperature aqueous batteries.

Four orthogonal polynomials for reconstructing a wavefront over a square aperture based on the modal method are currently available, namely, the 2D Chebyshev polynomials, 2D Legendre polynomials, Zernike square polynomials and Numerical polynomials. They are all orthogonal over the full unit square domain. 2D Chebyshev polynomials are defined by the product of Chebyshev polynomials in x and y variables, as are 2D Legendre polynomials. Zernike square polynomials are derived by the Gram-Schmidt orthogonalization process, where the integration region across the full unit square is circumscribed outside the unit circle. Numerical polynomials are obtained by numerical calculation. The presented study is to compare these four orthogonal polynomials by theoretical analysis and numerical experiments from the aspects of reconstruction accuracy, remaining errors, and robustness. Results show that the Numerical orthogonal polynomial is superior to the other three polynomials because of its high accuracy and robustness even in the case of a wavefront with incomplete data.

To improve the accuracy of midterm power load forecasting, a forecasting model is proposed by combing kernel principal component analysis (KPCA) with back propagation neural network. First, the dimension of the input space is reduced by KPCA, then input the data set to the neural network model, optimized by particle swarm optimization. The monthly average of daily peak loads is forecasted to modify the daily forecast values and output the daily peak load in the end. Using the data provided by European Network on Intelligent Technologies to test the model, the mean absolute percent error of load forecasting model is only 1.39%. The feasibility and validity of the model have been proven.

A novel chemo-photodynamic combined therapeutic self-assembly polymeric platform (MPEG-Hyd-Br2-BODIPY) was constructed based on 2,6-diBr-BODIPY as the photosensitizer core and MPEG as the hydrophilic side chain through hydrazone bond linkage and...

Abstract-Due to the high cell density, low leakage power consumption, and less vulnerability to soft errors, non-volatile memory technologies are among the most promising alternatives for replacing the traditional DRAM and SRAM technologies used in implementing main memory and caches in the modern microprocessor. However, one of the difficulties is the limited write endurance of most non-volatile memory technologies. In this paper, we propose to exploit the narrow-width values to improve the lifetime of non-volatile last level caches. Leading zeros masking scheme is first proposed to reduce the write stress to the upper half of the narrow-width data. To balance the write variations between the upper half and the lower half of the narrow-width data, two swap schemes, the swap on write (SW) and swap on replacement (SRepl), are proposed. To further reduce the write stress to non-volatile caches, we adopt two optimization schemes, the multiple dirty bit (MDB) and read before write (RBW), to improve their lifetime. Our experimental results show that by combining all our proposed schemes, the lifetime of non-volatile caches can be improved by 245% on average.