含银纳米粒子中不对称硫醚链相关性的探讨

纳米银簇外层包裹有机链形成的纳米粒子可以用于组装成纳米电子器件。纳米粒子冠中链间电子传输的可能性与链及苯环间的相关性有关。本文以87个银原子核外层吸附了22根不对称硫醚链的含银纳米粒子为研究对象,利用分子动力学模拟得到一定温度下的轨迹数据。由此出发.以次序参数为依据,对不同条件下的链及苯环间相关性进行了探讨。通过对采用不同临界次序参数下链及苯环间相关性的分析,确定了较为合理的相关性判据。同时,本文还考察了升高温度对链及苯环间的相关性的影响。     

随机分布的纳米链聚集结构:建模与光吸收特性研究

纳米粒子聚集结构可以高效捕获光子,因此,其具有优异的光吸收性能。提出并分析了一种硅基随机分布的纳米链聚集结构模型,采用高斯、柯西和均匀分布函数表征纳米链的聚集形式,实现了对其微观形貌的真实重建。建立并研究了结构参数(厚度和填充系数),等效物理参数(密度、热导率和热容)和可见光吸收率之间的关系。上述结构参数和等效物理参数均存在使可见光吸收率最大化的极值,该极值由材料属性和聚集结构决定。最后,通过降低蒸发沉积工艺中金属蒸汽动能的方法,在硅基底上制备了铝纳米聚集结构样品,实验研究了样品的光谱反射率特性。模型计算得到的光谱吸收率曲线和实验测得的曲线Spearman相关性系数高于0.82,证明了模型的准确性。模型计算得到的可见光吸收率与实验测量结果的相对误差低于0.3%,进一步验证了模型的准确性。     

生物柴油分子系统凝固过程的分子动力学模拟

具有良好的低温流动性是生物柴油的重要特性之一,而这一性质与系统的凝点相关联.本文以硬脂酸甲酯、油酸甲酯等7种常见生物柴油组成分子为研究对象,通过建模构建了7种单组份生物柴油分子的模拟液态模型.利用分子动力学方法对7种液态模型系统的凝固过程进行了研究.采用PCFF力场,在一定的模拟条件下,对系统进行逐次降温分子动力学模拟.根据分子动力学轨迹,计算了不同温度下系统的热容、碳原子自扩散系数以及分子链的头尾距.模拟计算得到的液态热容合理.利用“热容法”和“扩散系数法”对不同系统的凝点进行判断,发现凝点区间基本一致,且与实际凝点基本相吻合.而采用2种区间交集的方法得到的凝点区间则与实际凝点十分相近.以油酸甲酯为例,模拟观察到,随着温度降低,分子链总体呈伸展趋势,符合热力学基本原理.在油酸甲酯的凝点前后,链长及链的微观结构存在明显差异.模拟结果表明,本实验方法对研究生物柴油分子系统确实有效.     

一种新型仿壁虎爬行机器人的粘附阵列设计

分析了壁虎与表面间的微尺度粘附接触作用模型,在此基础上设计了一种具有主动控制能力的仿壁虎微纳米粘附阵列．给出了粘附阵列各设计参数,并介绍了微纳米阵列的加工工艺方法．     

常减压装置减压塔的链控制系统研究

为了提高减压塔的质量控制水平,研究了链系统方法在减压塔上的应用.通过对减压塔工艺流程的分析,以减压塔顶温度和真空度为受控变量,分析了影响塔顶温度和真空度的主要因素,建立了由4个单元模型、2条控制链和3支链间关联的链系统模型.设计了减压塔工艺中塔顶温度和真空度的链预估算法和链控制系统,通过对过程未来动向的预估和系统链之间的控制联系确定出最优的控制律.仿真结果表明,设计的链系统模型稳定性和抗干扰能力强,容错性好,控制效果良好.     

基于改进PSO-LSTM的APU排气温度预测研究北大核心

为了提高辅助动力装置排气温度的预测精度,采用基于粒子群算法优化长短期记忆网络的方法。通过分析不同参数间相关性,选出影响排气温度的主要参数作为预测模型的输入,构造惯性权重和学习因子的动态调节函数来解决粒子群算法存在的早熟收敛问题,得到一种改进粒子群算法。结果表明,改进PSO-LSTM模型比传统的RNN模型、LSTM模型、基本PSO-LSTM模型、标准PSO-LSTM模型具有更高的预测精度。上述研究结果可为短期APU性能变化趋势预测提供一定的参考。     

基于共享矢量链的多任务概念漂移分类方法

增强型时间自适应支持向量机在针对单一概念漂移问题时展现出了良好效果,但是无法协同求解多个概念漂移问题.然而,在很多应用场景中,有时会包含数个具有内在相关性的非静态数据集,它们各自的分类模型应充分考虑这种关联.为了反映出各概念漂移分类模型之间的相关部分,提出共享矢量链的概念,并开发面向多任务概念漂移问题的共享矢量链支持向量机(SVC-SVM).在模拟数据集及气体传感器阵列漂移数据集上的实验结果显示,协同求解多个具有相关性的概念漂移问题能够有效提升各自的泛化能力.     

基于粒距和动态区间的粒子群权值调整策略

由于标准粒子群优化(PSO)算法把惯性权值作为全局参数,因此很难适应复杂的非线性优化过程。针对这一问题,提出了一种基于粒距和动态区间的权值调整策略（PSSIW）,根据粒子的粒距大小在动态区间内选取不同的权值,并通过区间的动态变化来控制算法的收敛速度。设计了四种不同的动态区间,并采用三个常用的标准测试函数测试不同区间对算法性能的影响。通过与标准粒子群算法比较发现,该策略提高了算法摆脱局部极值的能力,是一种新型全局收敛粒子群算法。     

基于改进粒子群算法的宽带测向阵列结构优化

通过对测向模糊性进行分析,提出了针对宽带信号无模糊测向的阵列结构设计方法。该方法基于改进粒子群优化算法,以测向无模糊及各阵元最小间距为条件,对各阵元位置进行优化设计,得到合适的阵列结构以提高阵列的测向性能。仿真实验证明,改进粒子群算法提高了搜索效率,通过本方法设计的测向阵列在测向带宽内能够得到较高的测向性能,而且最小阵元间距不受均匀线阵中阵元间距不大于半波长的约束。     

管道燃气快烤装置燃烧过程数值仿真及结构参数影响分析

快烤试验装置作为快烤试验的重要组成部分,其产生的火焰温度对试验结果有很大的影响。为设计管道燃气快烤装置,利用Fluent软件、采用SST k-ω湍流模型和非预混燃烧模型,开展管道燃气装置燃烧过程仿真和关键结构参数对火焰温度及其均匀性的影响规律研究。选择三个关键参数即管道间距h1、火孔孔径Φ、火孔孔距h2,设计了三因素三水平正交试验进行仿真。研究结果表明:在管道直径确定的条件下,管道间距是影响管道燃烧器火焰温度均匀性的最主要因素,其次是火孔间距,火孔孔径是影响火焰温度均匀性的最次要因素;管道燃烧器上方不同高度处火焰温度均匀性对应的最佳结构参数并不相同。     

纳米技术在生物传感器及检测中的应用

纳米生物技术是纳米技术与生物技术交叉渗透形成的新技术,是纳米技术的重要组成部分,也是将来生物医学领域中的一个重要发展方向.纳米颗粒是生物医学中研究最多、应用最广的纳米材料,有着许多独特的性质.本文叙述了近年来国际上以纳米颗粒为基础的纳米技术在生物传感器及生物检测中的研究成果和进展,介绍了纳米颗粒的制备方法,以及它们在纳米生物传感器和纳米生物芯片中的应用,结合纳米病原微生物检测也介绍了我们进行的有关免疫传感器检测细菌的研究成果.最后,对该领域的应用前景进行了展望.     

Reliability testing of nano-particle system packaging

Metal nanoparticle applications in nanoelectronics are based on single nanodots or 1-D nanodot chains (both for single electron transistors), or 2-D discontinuous metal thin film (DMTF) arrays (e.g. for sensors), or 3-D polymer or ceramic “cermets,” (for high resistivity resistors and high-k dielectrics). DMTF fabrication relies upon weak substrate adhesion for discrete island formation, which promotes long-term instability and reliability problems. Past work on DMTF nanodot stability is applicable to future nanoelectronics and nanopackaging.     

Microfluidic patterning of nanoparticle monolayers

A microfluidic technique was developed to pattern nanoparticle monolayer controllably in a tentative polydimethylsiloxane (PDMS) microchannel. It was found that nanoparticle monolayer could be achieved in a two-step fluidic process: nanoparticle sedimentation and DI water rinsing. When nanoparticle suspension flows through a tentative PDMS microchannel, the particles will settle down due to the gravity effect and the Brownian motion and be captured onto the amino-functionalized substrate via electrostatic attraction. Aggregation on the substrate followed by a necessary DI water rinsing transforms hill-like nanoparticle aggregates into monolayer. Removing the tentative PDMS microchannel, pattern of nanoparticle monolayer following the channel shape was obtained. Experimental results indicated that the final monolayered nanoparticle coverage decreases when the flowing velocity in the sedimentation and/or the rinsing steps increases. Based on the continuity essence of fluid flow, different flowing velocities could be realized in one microchannel by varying the channel size. Therefore, monolayer patterns with controllable coverage could be achieved by carefully designing the microchannel width. The present approach is believed to be a promising nanoparticle monolayer patterning technique.     

纳米金与二茂铁在葡萄糖传感器中的相互作用

针对纳米金颗粒修饰的葡萄糖生物传感器对葡萄糖的响应电流随着工作电压的下降快速下降的问题,进一步利用电子媒介体二茂铁对其进行修饰,并选用丝网印刷电极研究了纳米金颗粒和二茂铁之间的相互作用。实验结果表明:二茂铁有效地降低了纳米金颗粒修饰的葡萄糖生物传感器响应电流的下降值,纳米金颗粒降低了电子媒介体二茂铁的氧化还原反应电位,并且,纳米金颗粒与电子媒介体二茂铁在葡萄糖生物传感器中表现协同增效效应。     

Mesoporous nanoparticle TiO2 thin films for conductometric gas sensing on microhotplate platforms

Mesoporous TiO₂ nanoparticle thin films were prepared on MEMS microhotplate (μHP) platforms and evaluated as high-sensitivity conductometric gas sensor materials. The nanoparticle films were deposited onto selected microhotplates in a multi-element array via microcapillary pipette and were sintered using the microhotplate. The films were characterized by optical and scanning electron microscopies and by conductometric measurements. The thin films were evaluated as conductometric gas sensors based on the critical performance elements of sensitivity, stability, speed and selectivity. The nanoparticle films were compared with compact TiO₂ films deposited via chemical vapor deposition (CVD) and the nanoparticle films were found to demonstrate higher sensitivity to target analytes. The nanoparticle films were also stable with regard to both baseline conductance and signal response over 60 h of continuous operation at high temperatures (up to 475 °C). Sensor response times were evaluated and the TiO₂ nanoparticle films showed fast responses to the presence of analyte (≈5 s) and a response-time dependence on the analyte concentration. Control of the sensor operating temperature, an inherent benefit of the microhotplate platform, was employed to demonstrate the selectivity of the nanoparticle films.     

Study about the nanoparticle agglomeration in a magnetic nanofluid by the Langevin dynamics simulation model using an effective Verlet-type algorithm

This paper presents a modelling study about the nanoparticle agglomeration in magnetic nanofluids. The colloidal magnetic nanoparticles size distribution is subjected to simultaneous translation and rotation movements under the action of conservative and dissipative forces, with their respective moments. In order to obtain the numerical solution of the coupled equations of motion, we use a Langevin dynamics stochastic method based on an effective Verlet-type algorithm. The presented model is based on an easy-to-implement integrator. We apply a number of analytical techniques to assess the performance of the method. The model has been tested on a magnetite nanoparticle-based nanofluid. Finally, the paper presents a number of structures obtained in various physical conditions, discussing the retrieved results of modelling and simulation. In weak external magnetic field, the nanoparticles form arrangements like linear chains or dense globes and rings, with magnetic moments rotating in both directions (both clockwise and counterclockwise). These arrangements, in vortex and toroidal states, are reported in actual scientific literature and open new perspectives for understanding the behaviour of nanofluids, with applications in engineering and medicine. Chains are predominant in high external magnetic, with local magnetic moments mainly orientated mainly along the direction of the applied field.     

Molecular dynamics simulation of nanoparticle diffusion in dense fluids

This article deals with a molecular dynamics simulation of the diffusion of nanoparticles in dense gases and liquids using the Rudyak–Krasnolutskii nanoparticle–molecule potential. Interaction of molecules of the carrier fluid is described by the Lennard-Jones potential. The behavior of the nanoparticle velocity autocorrelation function is studied. It is shown by molecular dynamics simulation that the diffusion coefficient of small nanoparticles depends greatly on the nanoparticle material. Relations are obtained between the diffusion coefficient of nanoparticles and the nanoparticle radius and the temperature of the medium. These relations differ from the corresponding Einstein relation for Brownian particles.     

Gold nanoparticle synthesis in microfluidic systems and immobilisation in microreactors designed for the catalysis of fine organic reactions

Our work is focused on two applications of fine tunable microfluidic systems, first to optimize heterogeneous size nanoparticle synthesis and second to build catalytic microreactors for advanced organic reactions. The first part of our work consists in the use of an original microfluidic setup for gold nanoparticle synthesis, which allows a high control of the reaction parameters as the reactants flow, the concentration, the temperature, and the reaction time. We show that using such microfluidic systems permit a better control of the reaction parameters for producing homodispersed 1–2 nm gold nanoparticle. The second part of our work deals with the incorporation of gold nanoparticles into silica capillaries to build catalytic microreactors dedicated to fine chemical reactions. Our strategy consists in the immobilization of gold nanopadiegolirticles onto the inner surface (2D dispersion) or into the inner volume (3D dispersion) of functionalized silica microcapillaries. Characterizations show that by different functionalization procedures, those gold nanoparticles are well anchored inside the microcapillary.