Copper Activation Enabling Reversible Aqueous Cu-ZnS Battery Chemistry.

The aqueous metal-sulfide batteries (AMSBs) have attracted research interest due to their high capacity, environmentally friendly qualities, and the accessibility of raw materials. However, the design strategies for metal-sulfide cathode have rarely been reported. Here, the copper-activated sphalerite in which Zn2+ is substituted by Cu2+ through ion exchange has been introduced for the first time as cathode for aqueous Cu/ZnS batteries. After sphalerite transformed to CuS, a two-step conversion of CuS→Cu7 S4 →Cu2 S storage mechanism has been proposed. At 0.7 A g-1 current density, the capacity can reach 532.4 mAh g-1 after 100 cycles. When cycled once at a current density of 35 mA g-1 , the initial reversible capacity can reach 461 mAh g-1 under 1 A g-1 . Furthermore, the assembled Zn//ZnS hybrid ion cell delivers an energy of up to 460 Wh kg-1 , which is better than for many AMSBs.

Negentropy Spectrum Decomposition and Its Application in Compound Fault Diagnosis of Rolling Bearing.

The rolling bearings often suffer from compound fault in practice. Compared with single fault, compound fault contains multiple fault features that are coupled together and make it difficult to detect and extract all fault features by traditional methods such as Hilbert envelope demodulation, wavelet transform and empirical node decomposition (EMD). In order to realize the compound fault diagnosis of rolling bearings and improve the diagnostic accuracy, we developed negentropy spectrum decomposition (NSD), which is based on fast empirical wavelet transform (FEWT) and spectral negentropy, with cyclic extraction as the extraction method. The infogram is constructed by FEWT combined with spectral negentropy to select the best band center and bandwidth for band-pass filtering. The filtered signal is used as a new measured signal, and the fast empirical wavelet transform combined with spectral negentropy is used to filter the new measured signal again. This operation is repeated to achieve cyclic extraction, until the signal no longer contains obvious fault features. After obtaining the envelope of all extracted components, compound fault diagnosis of rolling bearings can be realized. The analysis of the simulation signal and the experimental signal shows that the method can realize the compound fault diagnosis of rolling bearings, which verifies the feasibility and effectiveness of the method. The method proposed in this paper can detect and extract all the fault features of compound fault completely, and it is more reliable for the diagnosis of compound fault. Therefore, the method has practical significance in rolling bearing compound fault diagnosis.

A novel time-frequency slice extraction method for target recognition and local enhancement of non-stationary signal features.

Blind deconvolution can remove the effects of complex paths and extraneous disturbances, thus recovering simple features of the original fault source, and is used extensively in the field of fault diagnosis. However, it can only identify and extract the statistical mean of the fault impact features in a single domain and is unable to simultaneously highlight the local features of the signal in the time-frequency domain. Therefore, the extraction effect of weak fault signals is generally not ideal. In this paper, a new time-frequency slice extraction method is proposed. The method first computes a high temporal resolution spectrum of the signal by short-time Fourier transform to obtain multiple frequency slices with distinct temporal waveforms. Subsequently, the constructed harmonic spectral feature index is used to quantify and target the intensity of feature information in each frequency slice and enhance their fault characteristics using maximum correlation kurtosis deconvolution. Enhancing the local features of selected frequency slice clusters can reduce noise interference and obtain signal components with more obvious fault signatures. Finally, the validity of the method was confirmed by a simulated signal and fault diagnosis of the rolling bearing outer and inner rings was accomplished sequentially. Compared with other common deconvolution methods, the proposed method obtains more accurate and effective results in identifying fault messages.

Fe3O4-PVDF Composite Network for Dendrite-Free Lithium Metal Batteries.

Dendrite growth has been the main trouble preventing the practical application of Li metal anodes. Herein, we present how an Fe3O4-PVDF composite network prepared by using electrospinning has been designed to protect lithium metal anodes effectively. In the symmetrical cells test, the cell with the Fe3O4-PVDF composite network maintains good cycle performance after 600 h (500 cycles) at a current density of 1 mA cm-2 and a plating/stripping capacity of 1 mAh cm-2. The bulky Li dendrite is suppressed and a uniform Li deposition remains after long cycling. The characteristics of this engineered separator are further demonstrated in Li-S full cells with a good cycle performance (capacity of 419 mAh g-1 after 300 cycles at 0.5 C). This work provides a new idea for the protection of lithium metal anodes.