Interactions of Li2O volatilized from ternary lithium-ion battery cathode materials with mullite saggar materials during calcination

In recent years, the rapid development of Li(Ni_xCo_yMn_1-x-y)O₂ (LNCM) materials for application in ternary lithium-ion batteries has led to an increased demand for refractory kiln saggars in industries. However, saggars used for firing ternary Li-ion battery cathode materials are often subjected to severe corrosion and spalling. To investigate the damage mechanism of the saggar materials, non-contact corrosion experiments were designed to study the effects of the precursor additions, calcination temperature, and number of calcinations during the interaction between mullite saggar and LNCM materials. The phase composition and microstructure of the mullite saggar specimens before and after corrosion were characterized using X-ray diffraction and scanning electron microscopy, respectively, to obtain a comprehensive understanding of the causes of the deterioration of mullite saggar materials during corrosion.     

Optimization of hydrogen enrichment via palladium membrane in vacuum environments using Taguchi method and normalized regression analysis

In this study, the separation of hydrogen from gas mixtures using a palladium membrane coupled with a vacuum environment on the permeate side was studied experimentally. The gas mixtures composed of H₂, N₂, and CO₂ were used as the feed. Hydrogen permeation fluxes were measured with membrane operating temperature in the range of 320–380 °C, pressures on the retentate side in the range of 2–5 atm, and vacuum pressures on the permeate side in the range of 15–51 kPa. The Taguchi method was used to design the operating conditions for the experiments based on an orthogonal array. Using the measured H₂ permeation fluxes from the Taguchi approach, the stepwise regression analysis was also employed for establishing the prediction models of H₂ permeation flux, followed by the analysis of variance (ANOVA) to identify the significance and suitability of operating conditions. Based on both the Taguchi approach and ANOVA, the H₂ permeation flux was mostly affected by the gas mixture composition, followed by the retentate side pressure, the vacuum degree, and the membrane temperature. The predicted optimal operating conditions were the gas mixture with 75% H₂ and 25% N₂, the membrane temperature of 320 °C, the retentate side pressure of 5 atm, and the vacuum degree of 51 kPa. Under these conditions, the H₂ permeation flux was 0.185 mol s^?1 m^?2. A second-order normalized regression model with a relative error of less than 7% was obtained based on the measured H₂ permeation flux.     

Effect of micro-cracks on the in-plane electronic conductivity of proton exchange membrane fuel cell catalyst layers based on lattice Boltzmann method

Micro-cracks commonly occur on the catalyst layers (CLs) during the manufacturing of catalyst coated membranes (CCMs). However, the crack shape parameters effect on CLs in-plane (IP) electronic conductivity λ_s is not clear. In this work, the relationship between crack parameters and the λ_s is obtained based on the two-dimensional (2D) multiple-relaxation time (MRT) lattice Boltzmann method (LBM). The LBM numerical model is validated by the normalized λ_s experiment applied on three different home-made cracked CLs, and the parameter study focus on crack width, length, quantity and phase angle are carried out. The results show that the decrease of λ_s has different sensitivity |k| to the parameters above. The crack width has little effect on λ_s decrease, and the |k_w| is 0.038. However, crack arm length and quantity show more significant impact, which |k_l| and |k_N| are 0.753 and 0.725, respectively. The CLs with different crack propagation directions show significant anisotropy on λ_s, and a 53.53% decrease in λ_s is observed between 0° and 90° crack phase angle change. To manufacture a high electronic conductivity CL, crack initiation and migration mitigation are highly encouraged.     

基于多通道的ICU脑血管疾病死亡风险预测模型

死亡风险预测指根据病人临床体征监测数据来预测未来一段时间的死亡风险。对于ICU病患，通过死亡风险预测可以有针对性地对病人做出临床诊断，以及合理安排有限的医疗资源。基于临床使用的MEWS和Glasgow昏迷评分量表，针对ICU病人临床监测的17项生理参数，提出一种基于多通道的ICU脑血管疾病死亡风险预测模型。引入多通道概念应用于BiLSTM模型，用于突出每个生理参数对死亡风险预测的作用。采用Attention机制用于提高模型预测精度。实验数据来自MIMIC [Ⅲ]数据库，从中提取3?080位脑血管疾病患者的16?260条记录用于此次研究，除了六组超参数实验之外，将所提模型与LSTM、Multichannel-BiLSTM、逻辑回归（logistic regression）和支持向量机（support vector machine, SVM）四种模型进行了对比分析，准确率Accuracy、灵敏度Sensitive、特异性Specificity、AUC-ROC和AUC-PRC作为评价指标，实验结果表明，所提模型性能优于其他模型，AUC值达到94.3%。     

IRS辅助的SWIPT系统中基于能效优先的波束成形设计与优化

以智能反射面(intelligent reflecting surface,IRS)辅助的无线携能通信(simultaneous wireless information and power transfer,SWIPT)系统为背景,研究了该系统中基于能效优先的多天线发送端有源波束成形与IRS无源波束成形联合设计与优化方法。以最大化接收端的最小能效为优化目标,构造在发送端功率、接收端能量阈值、IRS相移等多约束下的非线性优化问题,用交替方向乘子法(alternating direction method of multipliers,ADMM)求解。采用Dinkelbach算法转化目标函数,通过奇异值分解(singular value decomposition,SVD)和半定松弛(semi-definite relaxation,SDR)得到发送端有源波束成形向量。采用SDR得到IRS相移矩阵与反射波束成形向量。结果表明,该系统显著降低了系统能量收集(energy harvesting,EH)接收端的能量阈值。当系统总电路功耗为?15 dBm时,所提方案的用户能效为300 KB/J。当IRS反射阵源数与发送天线数均为最大值时,系统可达最大能效。     

A dotted nanowire arrayed by 5 nm sized palladium and nickel composite nanopaticles showing significant electrocatalytic activity towards ethanol oxidation reaction (EOR)

To the best of our knowledge, this is the first time to report the preparation of a dotted nanowire arrayed by 5 nm sized palladium and nickel composite nanoparticles (denoted as Pd_xNi_y NPs) via a hydrothermal method using NU and PdO·H₂O as the starting materials. The samples prepared at the mass ratio of NU to PdO·H₂O 1:1, 1:2 and 2:1 were, respectively, nominated as catalyst c₁, c₂ and c₃. The chemical compositions of all synthesized catalysts were mainly studied by using X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS), revealing that metallic Ni was one main component of all prepared catalysts. Surprisingly, the main diffraction peaks appearing in the XRD patterns of all prepared catalysts were assigned to the metallic Ni rather than the metallic Pd. Very interestingly, as indicated by the TEM images, a large number of dotted nanowires arrayed by numerous equidistant 5 nm sized nanoparticles were distinctly exhibited in catalyst c₁. More importantly, when being used as electrocatalysts for EOR, all prepared catalysts exhibited an evident electrocatalytic activity towards EOR. In the cyclic voltammetry (CV) test, the peak current density of the forward peak of EOR on catalyst c₁ measured at 50 mV s^?1 was as high as 56.1 mA cm^?2, being almost 9 times higher than that of EOR on catalyst c₃ (6.3 mA cm^?2). Particularly, the polarized current density of EOR on catalyst c₁ at 3600 s, as indicated by the chronoamperometry (CA) experiment, was still maintained to be around 1.47 mA cm^?2, a value higher than the latest reported data of 1.3 mA cm^?2 (measured on the pure Pd/C electrode). Presenting a novel method to prepare dotted nanowires arranged by 5 nm sized nanoparticles and showing the significant eletrocatalytic activities of the newly prepared dotted nanowires towards EOR were the major contributions of this preliminary work.     

Structure-sensitive semantic matching for aggregate question answering over knowledge base

Aggregate question answering essentially returns answers for given questions by obtaining query graphs with unique dependencies between values and corresponding objects. Word order dependency, as the key to uniquely identify dependency of the query graph, reflects the dependencies between the words in the question. However, due to the semantic gap caused by the expression difference between questions encoded with word vectors and query graphs represented with logical formal elements, it is not trivial to match the correct query graph for the question. Most existing approaches design more expressive query graphs for complex questions and rank them just by directly calculating their similarities, ignoring the semantic gap between them. In this paper, we propose a novel Structure-sensitive Semantic Matching(SSM) approach that learns aligned representations of dependencies in questions and query graphs to eliminate their gap. First, we propose a cross-structure matching module to bridge the gap between two modalities(i.e., textual question and query graph). Then, we propose an entropy-based gated AQG filter to remove the structural noise caused by the uncertainty of dependencies. Finally, we present a two-channel query graph representation that fuses the semantics of abstract structure and grounding content of the query graph explicitly. Experimental results show that SSM could learn aligned representations of questions and query graphs to eliminate the gaps between their dependencies, and improves up to 12% (F1 score) on aggregation questions of two benchmark datasets.     

High performance asymmetric supercapacitor based on 3D microsphere-like 1T-MoS2 with high 1T phase content

1T phase molybdenum disulfide (1T-MoS₂) has aroused extensive concern in energy storage devices such as supercapacitors due to its large interlayer spacing, high conductivity and good hydrophilicity. However, it is struggle to synthesize 1T-MoS₂ with stable 1T phase with high content. Herein, Ammonium ion intercalation molybdenum disulfide (A-MoS₂) with high 1T content and stable 3D microsphere structure was successfully synthesized using a facile hydrothermal method. We explained the feasibility of ammonium ion (NH₄⁺) intercalation through density functional theory (DFT) calculations and proved the successful intercalation of NH₄⁺ by XRD and XPS. Through XPS fitting, the 1T phase content is calculated as high as 83.1%. The as-prepared A-MoS₂ presents a stable 3D microsphere structure with the interlayer spacing expanded to 0.93 nm, which provides a wide ion diffusion channel that allows ions to pass through quickly. Moreover, the high 1T content increases the hydrophilicity of MoS₂, thereby improving the wettability of the electrode, which contributes to the interaction between the electrolyte and electrode. In 1 M Na₂SO₄, A-MoS₂ electrode material displays high specific capacitance of 228 F g^?1 at 5 mV s^?1 and retains 127 F g^?1 at 80 mV s^?1, which proves the good rate capability. Furthermore, the assembled α-MnO₂//A-MoS₂ asymmetric supercapacitor (ASC) displayed a wide operating voltage of 2.1 V. The assembled ASC displays a high energy density of 35.8 Wh?kg^?1 at a power density of 525.0 W kg^?1, which indicates excellent energy storage performance.     

Synthesis of Hollow Three-Dimensional Channels LiNi_(0.5)Mn_(1.5)O_4 Microsphere by PEO Soft Template Assisted with Solvothermal Method

A appropriate size with three-dimension(3 D) channels for lithium diffusion plays an important role in constructing highperforming LiNi_(0.5)Mn_(1.5)O_4(LNMO) cathode materials, as it can not only reduce the transport path of lithium ions and electrons, but also reduce the side effects and withstand the structural strain in the process of repetitive Li~+ intercalation/deintercalation. In this work, an e fficient method for designing the hollow LNMO microsphere with 3 D channels structure by using polyethylene oxide(PEO) as soft template agent assisted solvothermal method is proposed. Experimental results indicate that PEO can make the reagents mingle evenly and nucleate slowly in the solvothermal process, thus obtaining a homogeneous distribution of carbonate precursors. In the final LNMO products, the hollow 3 D channels structure obtained by the decomposition of PEO and carbonate precursor in the calcination can provide abundant electroactive zones and electron/ion transport paths during the charge/discharge process, which benefits to improve the cycling performance and rate capability. The LNMO prepared by adding 1 g PEO possesses the most outstanding electrochemical performance, which presented an excellent discharge capacity of 143.1 mAh g~(-1) at 0.1 C and with a capacity retention of 92.2% after 100 cycles at 1 C. The superior performance attributed to the 3 D channels structure of hollow microspheres, which provide uninterrupted conductive systems and therefore achieve the stable transfer for electron/ion.