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•Structure and electrochemical mechanism of Na0.44MnO2 is summarized.•The relationship between synthesis, morphology and property is discussed.•The remaining challenges and feasible ...strategies for Na0.44MnO2 are commented.
Sodium-ion battery has been widely studied because of its abundant sodium resources and expectable electrochemical performance. The unique tunnel Na0.44MnO2 has attracted wide attention as one of the available cathode materials because of its low cost, as well as long cycle stability and rate capability in the non-aqueous and aqueous batteries. During the past decades, much efforts have been made to improve the electrochemical performance of the Na0.44MnO2. This review concisely describes the research progress of Na0.44MnO2 cathode for both non-aqueous and aqueous sodium-ion batteries, mainly focuses on the crystal structure, morphology, charge–discharge mechanism and influence of different synthesis and modification methods on the morphology and electrochemical performance. In addition, the main opportunities and challenges in this field are briefly commented and discussed.
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•Electrode architecture design and manufacturing processes are of high importance to high-performing lithium-ion batteries.•This work investigates the effects of electrode thickness, ...porosity, pore size and particle size at the electrode level.•This work summaries recent progress in electrode manufacturing techniques, including slurry casting, templating, additive manufacturing and laser ablation.•The merits and limitations of various manufacturing processes are discussed and compared.
The development of next-generation electrodes is key for advancing performance parameters of lithium-ion batteries and achieving the target of net-zero emissions in the near future. Electrode architecture and design can greatly affect electrode properties and the effects are sometimes complicated. The architecture of current electrodes is designed mainly based on empirical studies by making trade-offs between battery performance parameters. Thus, a holistic understanding of the relationships between electrode architecture-property-performance is urgently needed. Additionally, the implementation of next-generation electrodes with optimised architectures also relies on manufacturing capability. Various manufacturing processes have been proposed to produce electrodes with characteristic architectures. Nevertheless, the merits and limitations of the manufacturing processes are not well understood and selecting appropriate manufacturing processes is challenging. Herein, ten manufacturing processes are illustrated, which have been classified into four categories of slurry casting, templating, additive manufacturing, laser ablation. The overall performance of all the manufacturing processes is first qualitatively compared from five different aspects of architectural controllability, scalability, sustainability, simplicity and cost, followed by a quantitative comparison using a Weighted Manufacturing Score method. This work provides a guideline for future electrode architectural design illustrating the limitations and potential advantages of different methodologies to stimulate the development of the next-generation LIB electrodes.
Due to the open and diverse features of the Internet, applications need an effective method of performing a workflow reconfiguration to achieve both the functional behaviors and non-functional ...requirements of workflow changes when a service failure occurs. This paper proposes a service selection method for workflow reconfiguration based on interface operation matching. First, formal models of service workflow and interface operations of Web services are defined, and functional behavior comparisons of service selections are performed to determine the operation coverage set that will fulfill all activities that predefine the form of an abstract process. Second, reconfiguration patterns are introduced to describe different solution types for service patterns, including one-to-one, one-to-many, many-to-many, and many-to-one modes. Third, to consider the quality of service (QoS), the quality of service workflow (QoW) is proposed according to control structures and service interface computing, and the unified QoW formula is then provided to effectively rank each reconfiguration plan to provide a top-k solution recommendation. Fourth, related algorithms and a case study are discussed to show the service selection process during the workflow reconfiguration. To support the engineering implementation, a novel service workflow reconfiguration architecture is designed to provide guidance, which ranges from monitoring to recommendations for project implementation. Finally, experiments are conducted to demonstrate the effectiveness and efficiency of the proposed method.
•Formal models of service workflow and interface operations are defined.•Reconfiguration patterns are introduced to handle service failure.•The unified QoW formula is provided to rank each reconfiguration plan.•A novel service workflow reconfiguration architecture is designed.
Aiming at the problem of the “inverse relationship” between the hardness (wear resistance) and toughness of the traditional single homogeneous structure coating on the surface of titanium alloy, the ...design and development of a high hardness, high toughness and wear-resistant coating with high reliability and long life is great significance for expanding the application of titanium alloy. Inspired by the microstructure of high-performance organisms in nature, the design ideas of multi-phase, multi-level and multi-scale hybrid reinforcement are used to give full play to the synergy, coupling and multi-functional response mechanism between different phases in the coating to obtain the wear-resistant coating with high hardness and high toughness. This article mainly reviews the research progress of several typical wear-resistant coatings with high hardness and high toughness on the surface of titanium alloy from the aspects of preparation process, microstructure, mechanical properties, and strengthening-toughening mechanisms, such as gradient structure coating, multi-scale structure coating and layered structure coating. On this basis, it is pointed out that in the future, the wear-resistant coating with high hardness and high toughness on the surface of titanium alloy should develop in the direction of developing intelligent manufacturing technology, optimal design and precise tailoring of microstructural architectures, and constructing the numerical simulation technology of composition-structure-performance. Furthermore, the authors propose the technology route for the controllable preparation of wear-resistant coating with high hardness and high toughness on the surface of titanium alloy, namely, through the coordination of theoretical calculations, numerical simulations, and intelligent manufacturing technologies to achieve the controllable preparation of the optimal structural coatings on the surface of titanium alloy, establish the functional relationship between composition-structure-performance, and accurately reveal the mechanism of strengthening and toughening, which provides a new idea for alleviating and balancing the bottleneck of the “inverse relationship” between hardness (wear resistance) and toughness, and achieving the preparation of titanium-based surface composite with excellent comprehensive properties.
In the present paper a new additive manufacturing processing route is introduced for ultra-high performance concrete. Interdisciplinary work involving materials science, computation, robotics, ...architecture and design resulted in the development of an innovative way of 3D printing cementitious materials. The 3D printing process involved is based on a FDM-like technique, in the sense that a material is deposited layer by layer through an extrusion printhead mounted on a 6-axis robotic arm. The mechanical properties of 3D printed materials are assessed. The proposed technology succeeds in solving many of the problems that can be found in the literature. Most notably, this process allows the production of 3D large-scale complex geometries, without the use of temporary supports, as opposed to 2.5D examples found in the literature for concrete 3D printing. Architectural cases of application are used as examples in order to demonstrate the potentialities of the technology. Two structural elements were produced and constitute some of the largest 3D printed concrete parts available until now. Multi-functionality was enabled for both structural elements by taking advantage of the complex geometry which can be achieved using our technology for large-scale additive manufacturing.
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•A novel large-scale 3D printing process is proposed for cementitious materials.•Structures with complex geometry are produced without temporary supports.•The tangential continuity method for slicing is used, providing mechanical stability.•3D-printed concrete structures produced are some of the largest available today.•Geometric complexity enables multifunctionality and multiscale architecturation.
Mobility as a Service (MaaS) is a smart mobility model that integrates mobility services to deliver transportation needs through a single interface, offering users flexible and personalizd mobility. ...This paper presents a structural approach for developing a MaaS system architecture under Autonomous Transportation Systems (ATS), which is a new transition from the Intelligent Transportation Systems (ITS) with emerging technologies. Five primary components, including system elements, user needs, services, functions, and technologies, are defined to represent the system architecture. Based on the components, we introduce three architecture elements: functional architecture, logical architecture and physical architecture. Furthermore, this paper presents an evaluation process, links the architecture elements during the process and develops a three-layer structure for system performance evaluation. The proposed MaaS system architecture design can help the administration make services planning and implement planned services in an organized way, and support further technical deployment of mobility services.
Recent advances in Convolutional Neural Networks (CNNs) have obtained promising results in difficult deep learning tasks. However, the success of a CNN depends on finding an architecture to fit a ...given problem. A hand-crafted architecture is a challenging, time-consuming process that requires expert knowledge and effort, due to a large number of architectural design choices. In this article, we present an efficient framework that automatically designs a high-performing CNN architecture for a given problem. In this framework, we introduce a new optimization objective function that combines the error rate and the information learnt by a set of feature maps using deconvolutional networks (deconvnet). The new objective function allows the hyperparameters of the CNN architecture to be optimized in a way that enhances the performance by guiding the CNN through better visualization of learnt features via deconvnet. The actual optimization of the objective function is carried out via the Nelder-Mead Method (NMM). Further, our new objective function results in much faster convergence towards a better architecture. The proposed framework has the ability to explore a CNN architecture’s numerous design choices in an efficient way and also allows effective, distributed execution and synchronization via web services. Empirically, we demonstrate that the CNN architecture designed with our approach outperforms several existing approaches in terms of its error rate. Our results are also competitive with state-of-the-art results on the MNIST dataset and perform reasonably against the state-of-the-art results on CIFAR-10 and CIFAR-100 datasets. Our approach has a significant role in increasing the depth, reducing the size of strides, and constraining some convolutional layers not followed by pooling layers in order to find a CNN architecture that produces a high recognition performance.
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•We summarize the state-of-the-art of convolutional neural architecture search.•We model the convolutional neural network design as a bi-level optimization problem.•We develop ...BLOP-CNN as a new solution approach to our bi-level model.•We evaluate the performance of our proposal with respect to relevant existing works.
During the last decade, deep neural networks have shown a great performance in many machine learning tasks such as classification and clustering. One of the most successful networks is the CNN (Convolutional Neural Network), which has been applied in many application domains such as pattern recognition, medical diagnosis, and signal processing. Despite the very interesting performance of CNNs, their architecture design is still so far a major challenge for researchers and practitioners. Several works have been proposed in the literature with the aim to find optimized architectures such as ResNet and VGGNet. Unfortunately, most of these architectures are either manually defined by experts or automatically designed by greedy induction algorithms. Recent works suggest the use of Evolutionary Algorithms (EAs) thanks to their ability to escape locally-optimal architectures. Despite the fact that EAs have shown interesting performance, researchers in this direction have considered the design task as a single-level optimization problem; which represents the main research gap we tackle in this paper. The main contribution behind our work consists in the fact that CNN architecture design has a hierarchical nature and thus could be seen as a Bi-Level Optimization Problem (BLOP) where: (1) the upper level minimizes the network complexity defined by the number of blocks and the number of nodes per block; and (2) the lower level optimizes the convolution block ‘graphs’ topologies by maximizing the classification accuracy. Motivated by the originality of our observation with respect to the state of the art, we frame for the first time the CNN architecture design problem as a BLOP and then solve it using an adapted version of an existing efficient bi-level EA; through the definition of the solution encoding, the fitness function, and the variation operators at each level. The adapted EA is named BLOP-CNN and is assessed on the image classification task using the commonly employed CIFAR-10 and CIFAR-100 benchmark data sets. The analysis of our experimental results show the merits of our proposed method in providing the user with optimized architectures that outperform many recent and prominent architectures coming from the three different approaches, namely: manual design, reinforcement learning-based generation, and evolutionary optimization. Moreover, to show the applicability of our approach, we have conducted a case study on the detection of the COVID-19 using a set of benchmark chest X-ray and Computed Tomography (CT) images.
Learning quality can be improved by utilizing technology and digital media in teaching and learning. Based on a survey conducted in 2021 at 33 elementary schools in Madiun City, most teachers still ...use WhatsApp Group media in delivering material. However, schools with good technological facilities can better understand technology for teachers and students. This research is downstream from previous research that recommended the development of LMS-based e-learning in elementary schools in Madiun City. The importance of good management in documenting the teaching and learning process can be used as monitoring and evaluation material to improve the quality of learning. Data collection in this study was carried out by direct observation at SDN 01 and SDN 03 Manisrejo Madiun City, as well as surveys conducted at 33 elementary schools in the Madiun City Education Office. The results of this research are internal and external condition analysis, business process analysis, Data, and Information architecture design, application architecture design, technology architecture design, and people architecture design which can be used as Pecel-AE application development framework documents.
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