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Fine-tuning the molecular energy levels by incorporating thiophene units onto the π-backbone of core-expanded naphthalene diimides

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Chinese Chemical Letters 2016年第7期27卷 1022-1026页

作者： Dong Lu Xiao-Chun Yang Bing Leng Xiao-Di Yang Cong-Wu ge Xue-Shun Jia Xi-Ke Gao Department of Chemistry College of Science Shanghai University Key Laboratory of Synthetic and self-Assembly Chemistry for Organic Functional Molecules Shanghai Institute of Organic Chemistry Chinese Academy of Sciences Laboratory of Advanced Materials Fudan University

A series of core-expanded naphthalene diimides（nDI-DTYM） and thiophene-based derivatives（1a-c）were designed and synthesized to investigate the relationship between molecular structures and the highest occupied molecular orbital（HOMO） energy levels but has little impact on the lowest unoccupied molecular orbital（LUMO） energy *** results demonstrated that increasing the number of thiophene units can gradually elevate the HOMO energy levels but had little impact on the LUMO energy *** n-channel organic field-effect transistors（OFETs） based on 1b and 1c have demonstrated that these almost unchanged LUMO energy levels are proper to transport electrons.

关键词： naphthalene diimide Thiophene Molecular energy level Organic transistor Organic semiconductor

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高压直流缓冲器的建模分析及应用

电网技术 2016年第6期40卷 1766-1771页

作者：屈鲁李格中国科学院等离子体物理研究所安徽省合肥市230031

高压直流缓冲器是一种类变压器的直流短路电流抑制装置,结合高压直流断路器可有效地抑制、切断直流输电系统中的短路电流。首先基于高压直流缓冲器的等效电路,采用非线性电阻和非线性电感并联的方法建立其等效模型;接着对高压直流缓冲... 详细信息

高压直流缓冲器是一种类变压器的直流短路电流抑制装置,结合高压直流断路器可有效地抑制、切断直流输电系统中的短路电流。首先基于高压直流缓冲器的等效电路,采用非线性电阻和非线性电感并联的方法建立其等效模型;接着对高压直流缓冲器的工作性能进行了实验验证和仿真验证,结果表明高压直流缓冲器能够有效地抑制短路电流的峰值和燃弧时间;然后对高压直流缓冲器的非线性等效电路进行动态响应分析,分析结果表明高压直流缓冲器只有工作于过阻尼状态才能有效地抑制短路电流;最后结合高压直流缓冲器和高压直流断路器,提出一种混合式高压直流短路保护方案,并对其可行性进行了分析。

关键词：高压直流缓冲器直流输电直流断路器故障抑制

Study on the Electric Actuation of Liquid Metal Column in Confining ystem

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Chinese Journal of Mechanical Engineering 2022年第3期 221-224页

作者： Shuting Liang Zengwei Wang Fengjiao Li Mengjun Huang ge Ding China College of Chemical and Environmental Engineering Chongqing University of Arts and Sciences Chongqing Key Laboratory of Environmental Materials and Remediation Technologies Chongqing University of Arts and Sciences Shenzhen Automotive Research Institute Beijing Institute of Technology

Research on micro-machines is becoming popular. In this paper, the electric driving behavior of liquid metal columns in confining channel was studied. When the electric field was applied, the liquid metal near the negative electrode became flat, longer. The naOH electrolyte(1.0 mol/L) could flow from the positive electrode to the negative electrode from a small space above the liquid metal column. Besides, the length and volume of the liquid metal would affect its motion and deformation behavior. Both cylindrical liquid column(R = 5 mm, L = 5 cm) and linear liquid column(R = 5 mm, L = 40 cm) exhibit deformable movements, which are similar to the bionic movements of earthworms. The electrically driven liquid metal in closed systems could provide a theoretical basis for droplet actuation in *** has a very wide application prospect in the field of micro-drive machines.

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长江中下游典型湖泊营养盐历史变化模拟

湖泊科学 2016年第4期28卷 875-886页

作者：郭娅于革中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室南京210008

湖泊营养盐变化在自然条件下受到气候水文因素控制,同时受到湖泊生态系统生物群落作用和反馈.作为动力机制探讨,本文试图基于水文和生态动力学方法,分别构建气候-流域水文作用于湖泊营养盐的外源模式和湖泊生物群落作用于湖泊营养盐的... 详细信息

湖泊营养盐变化在自然条件下受到气候水文因素控制,同时受到湖泊生态系统生物群落作用和反馈.作为动力机制探讨,本文试图基于水文和生态动力学方法,分别构建气候-流域水文作用于湖泊营养盐的外源模式和湖泊生物群落作用于湖泊营养盐的內源模式.针对长江中下游典型湖泊,经过控制实验和率定,发现营养盐模拟与观测数据在时间序列上达到90%百分位的正相关,因此用来模拟1640 1840 A.D.期间的营养盐演变历史.研究表明:(1)模拟的湖泊营养盐变化与沉积钻孔揭示的历史营养盐变化基本一致,沉积记录与模式模拟的7个湖泊的营养盐变化均显著相关;(2)气候因素是湖泊营养盐历史演变的主控因子,来自于湖泊生物群落的反馈作用贡献约占40%;(3)在温度和降水因子的驱动下,湖泊营养盐历史变化主要受降水控制,在极端干旱时期,60%的营养盐变化同步响应于降水变化.同时,面积在400 km2以下的湖泊营养盐对气候变化的响应比2000 km2以上的大湖更为敏感.研究结果对长江中下游湖泊营养状态的长期变化机理认识和趋势控制提供科学依据.

关键词：气候驱动湖泊生态系统生物量模拟总磷长期变化

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油液速度对悬浮流特性的影响分析

中国石油大学学报（自然科学版） 2017年第4期41卷 167-173页

作者：陈彬刘阁重庆工商大学废油资源化技术与装备工程研究中心重庆400067

油液中含有颗粒物会影响设备的正常运行,考察不同初始速度条件下含颗粒油液的悬浮流中各相的动态特征,利用连续介质模型建立含悬浮颗粒油液的动力学模型,并通过特征线法进行数值求解,得到在不同初始速度条件下各相参数的变化趋势。结果... 详细信息

油液中含有颗粒物会影响设备的正常运行,考察不同初始速度条件下含颗粒油液的悬浮流中各相的动态特征,利用连续介质模型建立含悬浮颗粒油液的动力学模型,并通过特征线法进行数值求解,得到在不同初始速度条件下各相参数的变化趋势。结果表明:不同初始速度条件下管路始端、中段和终端油液的压力、流速都分别在T/4的奇数倍、整数倍、偶数倍时刻产生跃变,且它们的周期(T)都随着初始速度的增加而减小;悬浮颗粒的浓度分布与油液压力的变化趋势相反。

关键词：连续介质模型特征线法油液速度悬浮颗粒浓度分布

Deep convolutional Ritz method: parametric PDE surrogates without labeled data

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Applied Mathematics and Mechanics(English Edition) 2023年第7期44卷 1151-1174页

作者： J.n.FUHG A.KARMARKAR T.KADEETHUM H.YOOn n.BOUKLAS Sibley School of Mechanical and Aerospace Engineering Cornell UniversityNew York 14853U.S.A geomechanics Department Sandia National LaboratoriesAlbuquerque 87123U.S.A.

The parametric surrogate models for partial differential equations(PDEs)are a necessary component for many applications in computational sciences,and the convolutional neural networks(Cnns)have proven to be an excellent tool to generate these surrogates when parametric fields are *** are commonly trained on labeled data based on one-to-one sets of parameter-input and PDE-output ***,residual-based deep convolutional physics-informed neural network(DCPInn)solvers for parametric PDEs have been proposed to build surrogates without the need for labeled *** allow for the generation of surrogates without an expensive *** this work,we present an alternative formulation termed deep convolutional Ritz method(DCRM)as a parametric PDE *** approach is based on the minimization of energy functionals,which lowers the order of the differential operators compared to residualbased *** on studies involving the Poisson equation with a spatially parameterized source term and boundary conditions,we find that Cnns trained on labeled data outperform DCPInns in convergence speed and generalization *** surrogates generated from the DCRM,however,converge significantly faster than their DCPInn counterparts,and prove to generalize faster and better than the surrogates obtained from both Cnns trained on labeled data and *** hints that the DCRM could make PDE solution surrogates trained without labeled data possibly.

关键词： physics-informed constraint physics-informed neural network(PInn) deep energy network convolutional neural network(Cnn)

Effects of Layer Thickness and Edge Conditions to Thermoelastic Characteristics on Thermal Barrier Coatings

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Applied Mathematics 2014年第16期5卷 2417-2425页

作者： Jaegwi Go je-Hyun Lee Department of Mathematics Changwon National University Changwon South Korea School of nano and Advanced Materials Engineering Changwon National University Changwon South Korea

The thermoelastic behaviors of such as temperature distribution, displacements, and stresses in thermal barrier coatings (TBC) are seriously influenced by top coat thickness and edge conditions. The top coat of TBC specimens prepared with TriplexPro?-200 system was controlled by changing the processing parameter and feedstock, showing the various thicknesses and microstructures. A couple of governing partial differential equations were derived based on the thermoelastic theory. Since the governing equations were too involved to solve analytically, a finite volume method was developed to obtain approximations. The thermoelastic behaviors of TBC specimens with the various thicknesses and microstructures were estimated through mathematical approaches with different edge conditions. The results demonstrated that the microstructure and thickness of the top coat, and the edge condition in theoretical analysis were crucial factors to be considered in controlling the thermoelastic characteristics of plasma-sprayed TBCs.

关键词： Thermal Barrier Coatings Air Plasma Spray Layer Thickness Thermoelastic Characteristics Finite Volume Method

A machine learning approach for accelerated design of magnesium alloys. Part A:Alloy data and property space

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Journal of Magnesium and Alloys 2023年第11期11卷 3620-3633页

作者： M.Ghorbani M.Boley P.n.H.nakashima n.Birbilis Department of Materials Science and Engineering Monash UniversityVIC3800Australia Faculty of Information Technology Monash UniversityVIC3800Australia College of Engineering and Computer Science Australian National UniversityACT2601Australia Faculty of Engineering Science and the Built EnvironmentDeakin UniversityVIC3125Australia

Typically, magnesium alloys have been designed using a so-called hill-climbing approach, with rather incremental advances over the past century. Iterative and incremental alloy design is slow and expensive, but more importantly it does not harness all the data that exists in the field. In this work, a new approach is proposed that utilises data science and provides a detailed understanding of the data that exists in the field of Mg-alloy design to date. In this approach, first a consolidated alloy database that incorporates 916 datapoints was developed from the literature and experimental work. To analyse the characteristics of the database, alloying and thermomechanical processing effects on mechanical properties were explored via composition-process-property matrices. An unsupervised machine learning(ML) method of clustering was also implemented, using unlabelled data, with the aim of revealing potentially useful information for an alloy representation space of low dimensionality. In addition, the alloy database was correlated to thermodynamically stable secondary phases to further understand the relationships between microstructure and mechanical properties. This work not only introduces an invaluable open-source database, but it also provides, for the first-time data, insights that enable future accelerated digital Mg-alloy design.

关键词： Magnesium Alloy design Mg-alloy database Data analysis Data visualisation Unsupervised machine learning

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一类完整系统的Mei对称性与守恒量

物理学报 2008年第11期57卷 6714-6717页

作者：葛伟宽湖州师范学院物理系湖州313000

对一类完整系统的方程给出其Mei对称性的定义和判据.如果Mei对称性是noether对称性,则可找到noether守恒量.如果Mei对称性是Lie对称性,则可找到Hojman型守恒量.举例说明结果的应用.

关键词：分析力学完整系统 Mei对称性守恒量