基于关键路径延时检测的自适应电压缩减技术

为了减小传统的最差情况设计方法引入的电压裕量,提出了一种变化可知的自适应电压缩减(AVS)技术,通过调整电源电压来降低电路功耗.自适应电压缩减技术基于检测关键路径的延时变化,基于此设计了一款预错误原位延时检测电路,可以检测关键路径延时并输出预错误信号,进而控制单元可根据反馈回的预错误信号的个数调整系统电压.本芯片采用SMIC180 nm工艺设计验证,仿真分析表明,采用自适应电压缩减技术后,4个目标验证电路分别节省功耗12.4％,11.3％,10.4％和11.6％.     

中高压变频器冷却方案比较和选型分析

随着电力电子器件的发展,性能优异的中高压变频器在各行各业中得到越来越广泛的应用,能否处理好变频器的散热问题是其长期稳定运行的关键。分析了中高压变频器热量产生来源,并从技术可行性、可靠性、经济性等角度对不同冷却方案的特点进行比较,并结合实际的工程案例,给出合理的变频器冷却方案选型建议,可作为工程电气设计时中高压变频器冷却方案选型参考。     

Application of differential evolution for cascaded multilevel VSI with harmonics elimination PWM switching

Harmonic elimination pulse width modulation (HEPWM) method has been widely applied to multilevel voltage source inverter (MVSI) to remove low frequency harmonics from its output voltage. However, the computation of the HEPWM switching angles for MVSI is very challenging due to several constraints, namely angle sequencing, very tight angular spacing and the numerous possibilities of angles distribution ratio. Realizing the potential of Differential Evolution (DE) to handle complex problems, this work proposes its application to solve the HEPWM problem for cascaded MVSI. Its emphasis is on improving the availability of HEPWM for higher output voltage by extending the maximum range of modulation index (M). It also removes the discontinuities in the switching angles and reduces the number of distribution ratio required to obtain the required solution. Compared to the most advanced (similar) work, i.e., 7-level MVSI with seventeen switching angles, DE covers a wider range of M; the maximum achievable M is 2.80. Furthermore, it exhibits very low second order distortion factor (DF₂): for the worst case, the value of DF₂ is 0.0014%. To verify the viability of the proposed algorithm, simulation is carried out and hardware prototype is constructed. Both results show very good agreement with the theoretical prediction.     

建筑电气工程中低压配电系统的安装与调试

低压配电系统对建筑电气工程是非常重要的，本文对其安装做论述，针对各种建筑物对配电的要求，对系统做合理的调试，最终实现建筑实体安全用电，同时也确保低压配电系统的稳定性。     

电压降法在水平定向钻穿越管道外涂层评价中的应用研究

介绍了电流-电位法、电流密度法在水平定向钻穿越管道外涂层评价中的应用,联合电压降法计算管内电流值,并结合实际案例对穿越管道两端连头之后外涂层性能进行评价。     

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.     

Failure load prediction and optimisation for adhesively bonded joints enabled by deep learning and fruit fly optimisation

Adhesively bonded joints have been extensively employed in the aeronautical and automotive industries to join thin-layer materials for developing lightweight components. To strengthen the structural integrity of joints, it is critical to estimate and improve joint failure loads effectually. To accomplish the aforementioned purpose, this paper presents a novel deep neural network (DNN) model-enabled approach, and a single lap joint (SLJ) design is used to support research development and validation. The approach is innovative in the following aspects: (i) the DNN model is reinforced with a transfer learning (TL) mechanism to realise an adaptive prediction on a new SLJ design, and the requirement to re-create new training samples and re-train the DNN model from scratch for the design can be alleviated; (ii) a fruit fly optimisation (FFO) algorithm featured with the parallel computing capability is incorporated into the approach to efficiently optimise joint parameters based on joint failure load predictions. Case studies were developed to validate the effectiveness of the approach. Experimental results demonstrate that, with this approach, the number of datasets and the computational time required to re-train the DNN model for a new SLJ design were significantly reduced by 92.00% and 99.57% respectively, and the joint failure load was substantially increased by 9.96%.     

Reversible Flat to Rippling Phase Transition in Fe Containing Layered Battery Electrode Materials

Layered sodium transition metal oxides of NaTMO₂ (TM = 3d transition metal) show unique capability to mix different compositions of Fe to the TM layer, a phenomenon that does not exist in LiTMO₂. Here, a novel spontaneous TM layer rippling in the sodium ion battery cathode materials is reported, revealed by in situ X‐ray diffraction, Cs‐corrected scanning transmission electron microscopy, and density functional theory simulation, where the softening and distortion of FeO₆ octahedra collectively drives the flat TM planes into rippled ones with inhomogeneous interlayer distance at high voltage. In such a rippling phase, charge and discharge of Na ions take different evolution pathways, resulting in an unusual hysteresis voltage loop. Importantly, upon discharge beyond a certain Na composition, the rippling TM layer will go back to flat, giving the reversibility of such structural evolution in the following cycles.     

金属氧化物半导体场效应晶体管中总剂量效应导致的阈值电压漂移研究现状

为了研发可用于核与辐射应急响应与准备的机器人,对比了多种具有不同结构和生产工艺的金属氧化物半导体场效应晶体管(MOSFET)由于总剂量效应(TID)导致的阈值电压漂移(ΔV_th)。注意到了栅宽和栅长对器件耐辐射能力的影响在体CMOS器件和纳米线(NW)MOSFET器件之间、高的和低的工艺节点之间的不同,并从辐射诱导的窄通道效应(RINCE)和辐射诱导的短通道效应(RISCE)两方面解释了这种区别的原因。发现近年来前沿的一些研究在考虑辐射效应时,修正了负偏压不稳定性(NBTI)的影响。并讨论了几种新型器件包括锗沟道、氮化镓沟道管和具有特殊几何布局的晶体管。此外,介绍了计算机辅助设计技术(TCAD)在几种新型场效应管的机理研究和建模验证中的应用。     

The Protective Effects of the Autophagic and Lysosomal Machinery in Vascular and Valvular Calcification: A Systematic Review

Background: Autophagy is a highly conserved catabolic homeostatic process, crucial for cell survival. It has been shown that autophagy can modulate different cardiovascular pathologies, including vascular calcification (VCN). Objective: To assess how modulation of autophagy, either through induction or inhibition, affects vascular and valvular calcification and to determine the therapeutic applicability of inducing autophagy. Data sources: A systematic review of English language articles using MEDLINE/PubMed, Web of Science (WoS) and the Cochrane library. The search terms included autophagy, autolysosome, mitophagy, endoplasmic reticulum (ER)-phagy, lysosomal, calcification and calcinosis. Study characteristics: Thirty-seven articles were selected based on pre-defined eligibility criteria. Thirty-three studies (89%) studied vascular smooth muscle cell (VSMC) calcification of which 27 (82%) studies investigated autophagy and six (18%) studies lysosomal function in VCN. Four studies (11%) studied aortic valve calcification (AVCN). Thirty-four studies were published in the time period 2015–2020 (92%). Conclusion: There is compelling evidence that both autophagy and lysosomal function are critical regulators of VCN, which opens new perspectives for treatment strategies. However, there are still challenges to overcome, such as the development of more selective pharmacological agents and standardization of methods to measure autophagic flux.