Evolution of Local Structural Ordering and Chemical Distribution upon Delithiation of a Rock Salt–Structured Li1.3Ta0.3Mn0.4O2 Cathode

Lithium‐rich disordered rock‐salt oxides have attracted great interest owing to their promising performance as Li‐ion battery cathodes. While experimental and theoretical efforts are critical in advancing this class of materials, a fundamental understanding of key property changes upon Li extraction is largely missing. In the present study, single‐crystal synthesis of a new disordered rock‐salt cathode material, Li_1.3Ta_0.3Mn_0.4O₂ (LTMO), and its use as a model compound to investigate Li concentration–driven evolution of local cationic ordering, charge compensation, and chemical distribution are reported. Through the combined use of 2D and 3D X‐ray nanotomography, it is shown that Li removal accompanied by oxygen oxidation is correlated with the development of morphological defects such as particle cracking. Chemical heterogeneity, quantified by subparticle level distribution of Mn valence state, is minimal during Mn redox, which drastically increases upon the formation of cracks during oxygen redox. Density functional theory and bond valence sum mismatch calculations reveal the presence of local short‐range ordering in the pristine oxide, which gradually disappears along with the extraction of Li. The study suggests that with cycling the transformation into true cation–disordered state can be expected, which likely impacts the voltage profile and obtainable energy density of the oxide cathodes.     

应用膨胀算法提取目标的直接定位算法

为了解决被动雷达系统中的多发射源定位问题，提出了一种基于多重信号分类(MUSIC)算法和图像膨胀(IE)算法的直接定位方法。该方法结合了谱分析中的MUSIC思想，通过对接收量测协方差矩阵进行特征分析求解目标的位置。首先，在目标个数未知的前提下，利用Akaike信息准则(AIC)来确定模型阶数；然后，推导了基于MUSIC的定位代价函数；之后，利用图像膨胀算法处理得到的代价函数平面；最后，膨胀处理后的输出为目标个数及目标位置的估计值。提出的算法有效地解决了目标检测及提取的问题，能够确定多个目标的位置坐标，为后续的定位性能分析提供可能性，也保证了算法的完整性。进一步地分析了多个临近目标情况下影响目标提取性能的主要因素。     

Enhanced linear magneto-resistance near the Dirac point in topological insulator Bi2(Te1−xSex)3 nanowires

Nano Research - We report the composition and back-gate voltage tuned transport properties of ternary compound Bi2(Te1−xSex)3 nanowires synthesized by chemical vapor deposition (CVD). It is...     

Nonhydrolyzable Heptose Bis- and Monophosphate Analogues Modulate Pro-inflammatory TIFA-NF-κB Signaling

d -Glycero-d -manno-heptose-1β,7-bisphosphate (HBP) and d -glycero-d -manno-heptose-1β-phosphate (H1P) are bacterial metabolites that were recently shown to stimulate inflammatory responses in host cells through the activation of the TIFA-dependent NF-κB pathway. To better understand structure-based activity in relation to this process, a family of nonhydrolyzable phosphonate analogues of HBP and H1P was synthesized. The inflammation modulation by which these molecules induce the TIFA-NF-κB signal axis was evaluated in vivo at a low-nanomolar concentration (6 nM) and compared to that of the natural metabolites. Our data showed that three phosphonate analogues had similar stimulatory activity to HBP, whereas two phosphonates antagonized HBP-induced TIFA-NF-κB signaling. These results open new horizons for the design of pro-inflammatory and innate immune modulators that could be used as vaccine adjuvant.     

Backtesting portfolio value-at-risk with estimated portfolio weights

This article theoretically and empirically analyzes backtesting portfolio value-at-risk (VaR) with estimation risk in an intrinsically multi-variate framework. It particularly takes into account the estimation of portfolio weights in forecasting portfolio VaR and its impact on backtesting. It shows that the estimation risk from estimating portfolio weights and that from estimating the multi-variate dynamic model make the existing methods in a univariate framework inapplicable. It proposes a general theory to quantify estimation risk applicable to the present problem and suggests practitioners a simple but effective way to implement valid inference to overcome the effect of estimation risk in backtesting portfolio VaR. In particular, we apply our theory to the efficient mean-variance-skewness portfolio for a multi-variate generalized autoregressive conditional heteroscedasticity model with multi-variate general hyperbolic distributed innovations. Some Monte Carlo simulations and an empirical application demonstrate the merits of our method.     

Se doped nickel-molybdenum bimetal sulfide with enhanced electrochemical activity for hydrogen evolution reaction

In this work, we synthesized Se doped MoS₂@Ni₃S₂ with nanosheets coated nanorods structure supported on Ni foam (MoNiSeS). Firstly, MoS₂@Ni₃S₂ (MoNiS) nanorods was synthesized by hydrothermal method. After selenization treatment, MoSe₂ successfully formed on the edge of MoS₂ nanosheets and particle Ni₃S₂ transformed into NiSe, in which MoSe₂ and NiSe acted as new phase in MoNiSeS. The obtained MoNiSeS only needs a low overpotential of 68 mV to reach the current density of 10 mA cm^?2, and has a low Tafel plots of 72.77 mV dec^?1 and good electrochemical durability, whose electrochemical activity is much better than that of MoNiS and NiSeS, implying the introduction of Mo and Se is beneficial to improve the electrocatalytic performance of NiS for HER. In addition, the proper amount of Mo source, which has an effect on the morphology of product, has also been investigated. For MoNiSeS, the typical nanosheets coated nanarods expose more active sites and the synergic effects is good to the improvement of the catalytic activity. Meanwhile, WNiSeS has also been prepared using the same method and the corresponding results show that the electrochemical activity of WNiSeS is much better than that of NiSeS, proving the universality of this strategy.     

Effect of Temperature and Strain Rate on the Hot Deformation Behaviour of Ferritic Stainless Steel

Metals and Materials International - The flow behaviour and microstructure characteristics of a ferritic stainless steel were investigated using plain strain compression test on a Gleeble 3500...     

Study on the relationship between the particle size distribution and the effectiveness of the K‐powder fire extinguishing agent

The relationship between the particle size distribution and the extinguishing effectiveness of the new K‐powder fire extinguishing agent has been studied experimentally, to explore the reason of the great extinguishing efficiency exhibited by the new K‐powder fire extinguishing agent on Class B fire (liquid fuel fire). The results of the experiment showed that the extinguishing effectiveness increased along with the decrease of the particle size distribution. In addition, a sharp discontinuity appeared around the limiting size, about 40 μm. The powder with the particle size below 40 μm exhibited highly effective extinguishing with the minimum effective extinguishing concentration C_xr = 23 g·m^?3, while the powder with the particle size above 40 μm exhibited little fire extinguishing efficiency. Compared with other fire extinguishing agents produced by different substances, the new K‐powder fire extinguishing has the bigger limiting size. That means, in the same particle size distribution, the new K‐powder fire extinguishing agent contains more highly effective powder than others contain, and is more effective.