Colossal dielectric response and relaxation behavior in novel system of Zr4+ and Nb5+ co-substituted CaCu3Ti4O12 ceramics

In this work, we developed a novel system of isovalent Zr⁴⁺ and donor Nb⁵⁺ co-doped CaCu₃Ti₄O₁₂ (CCTO) ceramics to enhance dielectric response. The influences of Zr⁴⁺ and Nb⁵⁺ co-substituting on the colossal dielectric response and relaxation behavior of the CCTO ceramics fabricated by a conventional solid-phase synthesis method were investigated methodically. Co-doping of Zr⁴⁺ and Nb⁵⁺ ions leads to a significant reduction in grain size for the CCTO ceramics sintered at 1060 °C for 10 h. XRD and Raman results of the CaCu₃Ti_3.8-xZr_xNb_0.2O₁₂ (CCTZNO) ceramics show a cubic perovskite structure with space group Im-3. The first principle calculation result exhibits a better thermodynamic stability of the CCTO structure co-doped with Zr⁴⁺ and Nb⁵⁺ ions than that of single-doped with Zr⁴⁺ or Nb⁵⁺ ion. Interestingly, the CCTZNO ceramics exhibit greatly improved dielectric constant (~10⁵) at a frequency range of 10²–10⁵ Hz and at a temperature range of 20–210 °C, indicating a giant dielectric response within broader frequency and temperature ranges. The dielectric properties of CCTZNO ceramics were analyzed from the viewpoints of defect-dipole effect and internal barrier layer capacitance (IBLC) model. Accordingly, the immensely enhanced dielectric response is primarily ascribed to the complex defect dipoles associated with oxygen vacancies by co-doping Zr⁴⁺ and Nb⁵⁺ ions into CCTO structure. In addition, the obvious dielectric relaxation behavior has been found in CCTZNO ceramics, and the relaxation process in middle frequency regions is attributed to the grain boundary response confirmed by complex impedance spectroscopy and electric modulus.     

小型无线场强探测传感器研究

近年来,微波加热因其高效性和清洁无污染等优点广泛应用于各个领域。然而,微波加热的不均匀性限制了微波作为高效加热能源的应用。通过测量和分析加热腔中的电场分布情况可以帮助设计人员改进微波加热腔体设计,提高微波加热的均匀性。现有的场强测量设备均为有线设备,应用场景极为有限。因此,本文提出了一种由探头、接收机和上位机三部分组成的无线场强探测传感器。介绍了无线场强探测传感器的结构和原理,采用横电磁波小室进行校准。通过一系列测量实验表明实测值与标准场强仪测量值一致性较好,可满足工程测量需求。     

Neural network-based flight control systems: Present and future

As the first review in this field, this paper presents an in-depth mathematical view of Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural networks. The rapid evolution of IFCSs in the last two decades in both the methodological and technical aspects necessitates a comprehensive view of them to better demonstrate the current stage and the crucial remaining steps towards developing a truly intelligent flight management unit. To this end, in this paper, we will provide a detailed mathematical view of Neural Network (NN)-based flight control systems and the challenging problems that still remain. The paper will cover both the model-based and model-free IFCSs. The model-based methods consist of the basic feedback error learning scheme, the pseudocontrol strategy, and the neural backstepping method. Besides, different approaches to analyze the closed-loop stability in IFCSs, their requirements, and their limitations will be discussed in detail. Various supplementary features, which can be integrated with a basic IFCS such as the fault-tolerance capability, the consideration of system constraints, and the combination of NNs with other robust and adaptive elements like disturbance observers, would be covered, as well. On the other hand, concerning model-free flight controllers, both the indirect and direct adaptive control systems including indirect adaptive control using NN-based system identification, the approximate dynamic programming using NN, and the reinforcement learning-based adaptive optimal control will be carefully addressed. Finally, by demonstrating a well-organized view of the current stage in the development of IFCSs, the challenging issues, which are critical to be addressed in the future, are thoroughly identified. As a result, this paper can be considered as a comprehensive road map for all researchers interested in the design and development of intelligent control systems, particularly in the field of aerospace applications.     

教学型智能制造生产线的设计

以智能制造主要技术元素为切入点,设计了教学型智能制造生产线。介绍了企业资源计划系统、制造执行系统、立体仓储单元、工业机器人、数控加工设备、激光打标设备、视觉检测设备、自动装配设备、物料传输设备等教学型智能制造生产线的组成结构,分析了工作流程。这一教学型智能制造生产线具有良好的柔性,可以根据客户需求增减工作单元、调整零件类型、定制商标等,具有较高的实用价值。     

基于DSP的智能电源控制单元设计与实现

本文利用TI公司TMS320F28335芯片高效的浮点运算能力,结合片上丰富的外设,设计并实现了一种具有高可靠性的智能电源控制单元。该控制单元周期性地对各片上外设进行自检维护,完成多路负载通道控制、电压、电流的实时监控,并对故障进行指示、处理和上报,同时提供人机交互界面更新状态信息。经过验证,该控制单元工作稳定,具备良好的工程应用价值。     

Utilizing sensor data to model students’ creativity in a digital environment

While creativity is essential for developing students’ broad expertise in Science, Technology, Engineering, and Math (STEM) fields, many students struggle with various aspects of being creative. Digital technologies have the unique opportunity to support the creative process by (1) recognizing elements of students’ creativity, such as when creativity is lacking (modeling step), and (2) providing tailored scaffolding based on that information (intervention step). However, to date little work exists on either of these aspects. Here, we focus on the modeling step. Specifically, we explore the utility of various sensing devices, including an eye tracker, a skin conductance bracelet, and an EEG sensor, for modeling creativity during an educational activity, namely geometry proof generation. We found reliable differences in sensor features characterizing low vs. high creativity students. We then applied machine learning to build classifiers that achieved good accuracy in distinguishing these two student groups, providing evidence that sensor features are valuable for modeling creativity.     

An agile model for the eco-design of electric vehicle Li-ion batteries

Numerous design choices need to be made at several levels when designing high-tech products: technology, processes, architecture, components, materials… and these choices need to be made in relation to the product life cycle with the corresponding experts for each stage of the life cycle. At the same time, to ensure product sustainability, a specific focus on the future potential environmental impacts is highly recommended. In this research, an agile model is proposed to help designers make decisions while monitoring environmental performance indicators of high-tech solutions. The concept of Critical Product Life Cycle Parameters had to be introduced to facilitate the eco-design of the final product. The approach is illustrated by the Electric Vehicle Li-Ion Batteries case study.     

A three-dimensional surface measurement system implemented with Gaussian process based adaptive sampling

Self-adaptive surface measurements that can reduce data redundancy and improve time efficiency are in high demand in many fields of science and technology. For this purpose, a system implemented with Gaussian process (GP) adaptive sampling is developed. The non-parametric GP model is applied to reconstruct the topography and guide the subsequent sampling position, which is determined from the inference uncertainty estimation. A criterion is proposed to terminate the GP adaptive measurement automatically without any prior model or data of the topography. Experiments on typical surfaces validate the intelligence, adaptability, and high accuracy of the GP method along with the stabilization of the automatic iteration termination. Compared with traditional raster sampling, data redundancy is reduced and the time efficiency is improved without sacrificing the surface reconstruction accuracy. The proposed method can be implemented in other systems with similar measurement principles, thus benefitting surface characterizations.     

Biologically Inspired Design of Context-Aware Smart Products

The rapid development of information and communication technologies (ICTs) and cyber–physical systems (CPSs) has paved the way for the increasing popularity of smart products. Context-awareness is an important facet of product smartness. Unlike artifacts, various bio-systems are naturally characterized by their extraordinary context-awareness. Biologically inspired design (BID) is one of the most commonly employed design strategies. However, few studies have examined the BID of context-aware smart products to date. This paper presents a structured design framework to support the BID of context-aware smart products. The meaning of context-awareness is defined from the perspective of product design. The framework is developed based on the theoretical foundations of the situated function–behavior–structure ontology. A structured design process is prescribed to leverage various biological inspirations in order to support different conceptual design activities, such as problem formulation, structure reformulation, behavior reformulation, and function reformulation. Some existing design methods and emerging design tools are incorporated into the framework. A case study is presented to showcase how this framework can be followed to redesign a robot vacuum cleaner and make it more context-aware.     

Assessing the cost-effectiveness of electric vehicles in European countries using integrated modeling

Electric vehicles (EVs) are considered alternatives to internal combustion engines due to their energy efficiency and contribution to CO₂ mitigation. The adoption of EVs depends on consumer preferences, including cost, social status and driving habits, although it is agreed that current and expected costs play a major role. We use a partial equilibrium model that minimizes total energy system costs to assess whether EVs can be a cost-effective option for the consumers of each EU27 member state up to 2050, focusing on the impact of different vehicle investment costs and CO₂ mitigation targets. We found that for an EU-wide greenhouse gas emission reduction cap of 40% and 70% by 2050 vis-à-vis 1990 emissions, battery electric vehicles (BEVs) are cost-effective in the EU only by 2030 and only if their costs are 30% lower than currently expected. At the EU level, vehicle costs and the capability to deliver both short- and long-distance mobility are the main drivers of BEV deployment. Other drivers include each state’s national mobility patterns and the cost-effectiveness of alternative mitigation options, both in the transport sector, such as plug-in hybrid electric vehicles (PHEVs) or biofuels, and in other sectors, such as renewable electricity.