Low threshold voltage,highly stable electroforming-free threshold switching characteristics in VOx films-based device

Threshold switching (TS) devices have evolved as one of the most promising elements in memory circuit due to their important significance in suppressing crosstalk current in the crisscross array structure. However, the issue of high threshold voltage (V_th) and low stability still restricts their potential applications. Herein, the vanadium oxide (VO_x) films deposited by the pulsed laser deposition (PLD) method are adopted as the switching layer to construct the TS devices. The TS devices with Pt/VO_x/Pt/PI structure exhibit non-polar, electroforming-free, and volatile TS characteristics with an ultralow V_th (+0.48 V/−0.48 V). Besides that, the TS devices also demonstrates high stability, without obviously performance degradations after 350 cycles of endurance measurements. Additionally, the transition mechanism is mainly attributed to the synergistic effect of metal-insulator transition of VO₂ and oxygen vacancies. Furthermore, the nonvolatile bipolar resistance switching behaviors can be obtained by changing oxygen pressure during the deposition process for switching films. This work demonstrates that vanadium oxide film is a good candidate as switching layer for applications in the TS devices and opens an avenue for future electronics.     

Nitrate Additives Coordinated with Crown Ether Stabilize Lithium Metal Anodes in Carbonate Electrolyte

Lithium metal anodes (LMAs) are promising for next-generation batteries but have poor compatibility with the widely used carbonate-based electrolytes, which is a major reason for their severe dendrite growth and low Coulombic efficiency (CE). A nitrate additive to the electrolyte is an effective solution, but its low solubility in carbonates is a problem that can be solved using a crown ether, as reported. A rubidium nitrate additive coordinated with 18-crown-6 crown ether stabilizes the LMA in a carbonate electrolyte. The coordination promotes the dissolution of NO₃⁻ ions and helps form a dense solid electrolyte interface that is Li₃N-rich which guides uniform Li deposition. In addition, the Rb (18-crown-6)⁺ complexes are adsorbed on the dendrite tips, shielding them from Li deposition on the dendrite tips. A high CE of 97.1% is achieved with a capacity of 1 mAh cm⁻² in a half cell, much higher than when using the additive-free electrolyte (92.2%). Such an additive is very compatible with a nickel-rich ternary cathode at a high voltage, and the assembled full battery with a cathode material loading up to 10 mg cm⁻² shows an average CE of 99.8% over 200 cycles, indicating a potential for practical use.     

“高电压技术”课程线上线下混合式教学

本文采用超星学习通线上教学平台，以 “高电压技术”课程为对象，实施了规模为120余人的线上线下混合式教学。基于线上教学和传统教学的优势互补，设计了“高电压技术”多个教学环节。归纳分析了混合式教学在各个教学环节取得的效果和问题，并根据学生反馈提出了持续性的改进措施。     

变压吸附制氮(PSA)设备在炼油生产中的应用

针对某炼油装置氮气供需矛盾突出的问题,提出采用变压吸附(PSA)制氮设备,利用空压站净化风生产氮气方案,(1)降低空压站多余风量放空,减少浪费;(2)正常生产情况下,利用PSA设备生产氮气,对供氮管网压力调节。针对上述方案,结合空压站供风现状进行分析,得出结论:利用PSA制氮设备满足炼油装置高峰用氮是可行的,并提出了具体措施和运行过程中应注意的问题。     

超临界机组发生FAC的因素及相互关系分析

为了减轻因流动加速腐蚀(FAC)引起的锅炉结垢加速、汽水系统管道厚度减小甚至爆裂现象，对超临界机组发生流动加速腐蚀的机理及其主要影响因素进行了研究，并讨论了管壁内表面粗糙度、蒸汽含汽率、pH值、溶氧量对FAC的影响，以及温度与pH值、温度与流速、pH值与溶解氧量、溶解氧量与氢电导率等影响因素之间的相互作用关系，最后结合实际电厂的运行数据验证了分析结果。研究表明：减小工质流速、管壁粗糙度和氢电导率，增大给水的pH值和溶解氧含量可以使FAC的腐蚀速率减小，超临界加氧处理时pH值应在8.9～9.2之间，溶解氧量范围为45～100μg/L,氢电导率的期望值在0.1μS/cm以下。由于各影响因素之间的作用十分复杂，本文只给出了大致范围和趋势，并未给出准确数据。     

火电机组一次调频性能实时监测系统

为了实时监测和评价火电机组一次调频性能，开发了火电机组一次调频性能实测监测系统。该系统具有一次调频参数异动感知、一次调频性能量化预测及自适应校正等关键功能。某机组的实际应用表明，该系统能够实现火电机组一次调频关键参数的实时监测和调频性能的准确预测。     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

Influence of applied voltage and conductive material in DIET promotion for methane generation

The utilization of biological-, electrode- and conductive material-mediated direct interspecies electron transfer (DIET) between exoelectrogenic bacteria and methanogenic archaea for enhancing methane productivity is widely reported in the literature. However, two cardinal questions are still controversial, i.e., which applied voltage value would be more recommended to enhance methane generation? and how the DIET over IIET has the upper hand in enhancing methane productivity? Herein, the influence of different applied voltages to promote biological-, conductive- and electrode-mediated DIET was investigated in MEC-AD reactors with conductive material. Polarized bioelectrodes induced electrode-mediated DIET (eDIET) and biological DIET (bDIET), in addition to cDIET (conductive material-mediated DIET), improved the methane yield to 315.40 mL/g COD_r with an applied voltage of 0.9 V. Whereas further increase of applied voltage 1.2 V, lessened methane production efficiency due to high-voltage inhibition and adverse effect on DIET promotion. The anaerobic digestion coupled microbial electrolysis cells with optimal electric potential selectively promotes the DIET through polarized electrodes were confirmed through microbial analysis. As the contribution of DIET increased to 80%, the methane yield increased, and the substrate residue decreased, resulting in a significant improvement in methane production.     

High voltage and self-healing zwitterionic double-network hydrogels as electrolyte for zinc-ion hybrid supercapacitor/battery

The hydrogel electrolyte is an important part of safety and development potential in zinc-based energy storage equipment due to its inherent low mechanical strength and voltage decomposition. However, hydrogel electrolytes possess a reduced working life for zinc dendrites growth and a narrow voltage window. In this study, a hydrogel electrolyte prepares by the zwitterionic monomer [2-(methacryloyloxy)ethyl]dimethyl-(3-sulfopropyl) (MS) and sodium alginate (SA) alleviate these problems. The zwitterionic double-network hydrogel has good mechanical strength, inhibits the growth of zinc dendrites, enhances practicability, greatly increases the voltage window (0–2.4 V), and has self-healing properties to its rich functional groups. The assembled zinc-ion hybrid supercapacitors (ZHSs) have a high-power density of 172.33 W kg^?1 and an energy density of 88.56 Wh·kg^?1 at 0.5 A g^?1. The assembled zinc-ion battery also has good electrochemical performance. Flexible ZHSs and batteries provide power to the timer stably under different bending angles. The zwitterionic double-network hydrogel can be applied to both zinc-based supercapacitors and batteries.     

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%。