掺钪AlN材料特性及HBAR器件性能研究

该文基于掺钪AlN薄膜制备了高次谐波体声波谐振器(HBAR),研究了钪(Sc)掺杂浓度对AlN压电薄膜材料特性及器件性能的影响。研究表明,当掺入Sc的摩尔分数从0增加到25%时,压电应力系数e₃₃增加、刚度 下降,导致Al₁-_xSc_xN压电薄膜的机电耦合系数 从5.6%提升至15.8%,从而使HBAR器件的有效机电耦合系数 提升了3倍。同时,当Sc掺杂摩尔分数达25%时,Al₁-_xSc_xN(x为Sc掺杂摩尔分数)压电薄膜的声速下降13%,声学损耗提高,导致HBAR器件的谐振频率和品质因数降低。     

建筑电气设计中相关问题分析

在民用建筑电气设计中,经常会遇到一些让人感到困惑的问题,特别是在国家及行业设计规范、标准的更新替换时,设计师对于新标准、规范的理解,往往会有不同程度的偏差,导致设计过程中出现一些问题或错误.就执行GB 51348-2019《民用建筑电气设计标准》过程中收集到的几个具体问题进行分析.     

催化剂级配技术在加氢改质装置上的工业应用

基于柴油产品质量升级的需求,中国石化大连石油化工研究院(FRIPP)开发了FHIDW加氢改质技术及配套FF-46加氢精制催化剂、FC-14B加氢改质催化剂和FDW-3临氢降凝催化剂.该技术及催化剂级配体系在格尔木炼油厂0.8 Mt·a-1加氢改质装置上的工业应用情况表明,级配催化剂体系对原料适应性强,装置运转平稳,操作灵活性高,催化剂失活速率慢,产品分布合理且质量优异,在降低柴油产品凝点的同时可以明显改善其密度和十六烷值,解决了改造前装置生产重柴油密度偏低的问题,为炼油厂生产符合国V质量标准的柴油提供了技术保障.     

荷电细水雾对管道瓦斯爆炸超压的影响规律研究

为了研究荷电细水雾对瓦斯爆炸超压的影响规律和机理,采用小尺寸管道模拟瓦斯爆炸,研究不同荷电电压作用下的瓦斯爆炸超压和平均压升速率,以及不同雾通量作用下的瓦斯爆炸超压.结果表明:随着荷电电压的升高,瓦斯爆炸超压和平均压升速率受到明显的抑制;随着雾通量的增加,瓦斯爆炸超压明显降低.在实验条件下,和普通细水雾相比,当雾通量为4L、荷电电压为8kV时,瓦斯爆炸超压峰值降低10.798kPa,降幅达49.78%;平均压升速率峰值降低180.468kPa/s,降幅达49.90%.     

P-doped CoSe2 nanoparticles embedded in 3D honeycomb-like carbon network for long cycle-life Na-ion batteries

We report for the first time a Na-ion battery anode material composed of P-doped CoSe2 nanoparticles(P-CoSe2)with the size of 5-20 nm that are uniformly embed in a 3D porous honeycomb-like carbon network.High rate capability and cycling stability are achieved simultaneously.The honeycomb-like carbon network is rationally designed to support high electrical conductivity,rapid Na-ion diffusion as well as the accommodation of the volume expansion from the active P-CoSe2 nanoparticles.In particular,heteroatom P-doping within CoSe2 introduces stronger P-Co bonds and additional P-Se bonds that signif-icantly improve the structure stability of P-CoSe2 for highly stable sodiation/desodiation over long-term cycling.P-doping also improves the electrical conductivity of the CoSe2 nanoparticles,leading to highly elevated electrochemical kinetics to deliver high specific capacities at high current densities.Benefiting from the unique nanostructure and atomic-level P-doping,the P-CoSe2(2∶1)/C anode delivers an excel-lent cycle stability with a specific capacity of 206.9 mA h g-1 achieved at 2000 mA g-1 after 1000 cycles.In addition,this material can be synthesized using a facile pyrolysis and selenization/phosphorization approach.This study provides new opportunities of heteroatom doping as an effective method to improve the cycling stability of Na-ion anode materials.     

Electrocatalytic activity of LaSr3Fe3O10 and LaSr3Fe3O10-GO towards oxygen reduction reaction in alkaline medium

Oxygen reduction reaction(ORR) plays a critical role in many energy conversion and storage processes.Therein, a comparative study of the electrocatalytic activity for ORR in 0.1 mol/L KOH solution was conducted using layered perovskite-like LaSr_3 Fe_3 O_(10) and LaSr3 Fe_3 O_(10)-graphene oxide(GO) composite as electrodes. Linear sweep voltammetry(LSV) results show that the LaSr3 Fe_3 O_(10)-GO hybrid exhibits higher current density, a more positive onset potential(-0.15 V vs. Hg/HgO) in comparison with LaSr_3 Fe_3 O_(10).The value of the overall transferred electrons for both catalysts implies a dominant two electron process for ORR. Both catalysts under alkalic conditions exhibit a two-step Tafel slope, suggesting a change in the reaction mechanism for ORR. The composite electrode exhibits a higher ORR current density, but inferior durability performances in relative to the LaSr_3 Fe_3 O_(10) electrode.     

基于模糊谱聚类的不确定蛋白质相互作用网络功能模块挖掘

针对谱聚类融合模糊C-means（FCM）聚类的蛋白质相互作用（PPI）网络功能模块挖掘方法准确率不高、执行效率较低和易受假阳性影响的问题，提出一种基于模糊谱聚类的不确定PPI网络功能模块挖掘（FSC-FM）方法。首先，构建一个不确定PPI网络模型，使用边聚集系数给每一条蛋白质交互作用赋予一个存在概率测度，克服假阳性对实验结果的影响；第二，利用基于边聚集系数流行距离（FEC）策略改进谱聚类中的相似度计算，解决谱聚类算法对尺度参数敏感的问题，进而利用谱聚类算法对不确定PPI网络数据进行预处理，降低数据的维数，提高聚类的准确率；第三，设计基于密度的概率中心选取策略（DPCS）解决模糊C-means算法对初始聚类中心和聚类数目敏感的问题，并对预处理后的PPI数据进行FCM聚类，提高聚类的执行效率以及灵敏度；最后，采用改进的边期望稠密度（EED）对挖掘出的蛋白质功能模块进行过滤。在酵母菌DIP数据集上运行各个算法可知，FSC-FM与基于不确定图模型的检测蛋白质复合物（DCU）算法相比，F-measure值提高了27.92%，执行效率提高了27.92%；与在动态蛋白质相互作用网络中识别复合物的方法（CDUN）、演化算法（EA）、医学基因或蛋白质预测算法（MGPPA）相比也有更高的F-measure值和执行效率。实验结果表明，在不确定PPI网络中，FSC-FM适合用于功能模块的挖掘。