Hasil untuk "Electronics"

J. Rocabert, A. Luna, F. Blaabjerg et al.

B. Dunn, H. Kamath, J. Tarascon

A. Reina, X. Jia, John T. Ho et al.

Wenpin Tsai, S. Ghoshal

Gary Gereffi, J. Humphrey, T. Sturgeon

A. Jaffe

P. Wynn

I. Žutić, J. Fabian, S. Das Sarma

Spintronics, or spin electronics, involves the study of active control and manipulation of spin degrees of freedom in solid-state systems. This article reviews the current status of this subject, including both recent advances and well-established results. The primary focus is on the basic physical principles underlying the generation of carrier spin polarization, spin dynamics, and spin-polarized transport in semiconductors and metals. Spin transport differs from charge transport in that spin is a nonconserved quantity in solids due to spin-orbit and hyperfine coupling. The authors discuss in detail spin decoherence mechanisms in metals and semiconductors. Various theories of spin injection and spin-polarized transport are applied to hybrid structures relevant to spin-based devices and fundamental studies of materials properties. Experimental work is reviewed with the emphasis on projected applications, in which external electric and magnetic fields and illumination by light will be used to control spin and charge dynamics to create new functionalities not feasible or ineffective with conventional electronics.

A. Yariv

Chunxiang Qian, Wenxiang Du, Yudong Xie et al.

With the growing demand for large-scale infrastructure development in China—such as deep-sea, deep-underground, and urban subsurface projects—combined with the widespread use of general-purpose raw materials, there is an urgent need for more precise crack control technologies in concrete. This need stems from the imperative to reduce unnecessary material consumption and environmental impact caused by excessive safety margins. To address this, a set of governing equations that account for the mutual feedback between temperature and humidity was first proposed. A non-constant form of the diffusion coefficient was introduced, alongside latent heat terms and unsteady-state heat source terms, to establish a hygrothermal coupling model. This model was further enhanced by incorporating the effects of creep relaxation, reinforcement constraint, structural restraint, and thermal conduction characteristics of formwork, thereby forming a comprehensive multi-field coupling evaluation framework that encompasses the temperature field, moisture content field, strain field, and cracking index field. Subsequently, the proposed theoretical framework was applied to representative engineering scenarios, including large-scale concrete foundation slabs, bridge bearing platforms, large-area long-span side walls and prefabricated tunnel segments. The accuracy and reliability of the model were validated through comparisons between simulation results and field-monitored data. The results demonstrate that this method effectively overcomes the technical limitations of traditional concrete crack prediction models, particularly those relying on constant parameter assumptions and decoupled field interactions. It offers a practical and robust approach for engineering applications, providing a novel perspective for precision crack control in concrete and contributing to the broader goals of sustainability and resource efficiency.

Jiachang Bi, Ruyi Zhang, Xiong Yao et al.

The advancement of semiconductor materials has played a crucial role in the development of electronic and optical devices. However, scaling down semiconductor devices to the nanoscale has imposed limitations on device properties due to quantum effects. Hence, the search for successor materials has become a central focus in the fields of materials science and physics. Transition-metal nitrides (TMNs) are extraordinary materials known for their outstanding stability, biocompatibility, and ability to integrate with semiconductors. Over the past few decades, TMNs have been extensively employed in various fields. However, the synthesis of single-crystal TMNs has long been challenging, hindering the advancement of their high-performance electronics and plasmonics. Fortunately, progress in film deposition techniques has enabled the successful epitaxial growth of high-quality TMN films. In comparison to reported reviews, there is a scarcity of reviews on epitaxial TMN films from the perspective of materials physics and condensed matter physics, particularly at the atomic level. Therefore, this review aims to provide a brief summary of recent progress in epitaxial growth at atomic precision, emergent physical properties (superconductivity, magnetism, ferroelectricity, and plasmon), and advanced electronic and plasmonic devices associated with epitaxial TMN films.

Manuel Reis Carneiro, Anibal T. de Almeida, Mahmoud Tavakoli et al.

Despite advances in soft, sticker_like electronics, few efforts have dealt with the challenge of electronic waste. Here, this is addressed by introducing an eco friendly conductive ink for thin_film circuitry composed of silver flakes and a water_based polyurethane dispersion. This ink uniquely combines high electrical conductivity (1.6 x 105 S m_1), high resolution digital printability, robust adhesion for microchip integration, mechanical resilience, and recyclability. Recycling is achieved with an ecologically friendly processing method to decompose the circuits into constituent elements and recover the conductive ink with a decrease of only 2.4 per cent in conductivity. Moreover, adding liquid metal enables stretchability of up to 200 per cent strain, although this introduces the need for more complex recycling steps. Finally, on_skin electrophysiological monitoring biostickers along with a recyclable smart package with integrated sensors for monitoring safe storage of perishable foods are demonstrated.

YANG Hongwei, WANG Haifeng, YANG Jun, PU Renbin, YANG Can, JIN Chen

In order to enhance the long-term protective performance of water-based epoxy coatings，benzotriazole (BTAH) corrosion inhibitor was incorporated into hollow cerium oxide (CeO2) nanocontainers，resulting in the preparation of BTAH＠CeO2-doped epoxy coatings.The surface morphology，chemical composition and corrosion resistance of the epoxy/BTAH＠CeO2 composite coating were characterized using scanning electron microscopy (SEM)，X-ray photoelectron spectroscopy (XPS) and electrochemical impedance spectroscopy (EIS).The results showed that the loading amount of BTAH inhibitor in the CeO2 nanocontainers was 24.7%.The BTAH inhibitor was able to be rapidly released from the CeO2 nanocontainers，with a release amount reaching 92.6%after 8 h.The BTAH＠CeO2 particles were uniformly dispersed in the water-based epoxy resin and effectively filled the microscopic voids inside the coating.Electrochemical impedance testing results after corrosion in a 3.5%NaCl solution for 1 h indicated that the coating resistance of the epoxy/BTAH＠CeO2 composite coating was 16.7 times higher than that of pure epoxy coatings.After immersion in a 3.5%(mass fraction) NaCl solution for 30 d，the polarization resistance loss rate of the epoxy/BTAH＠CeO2 composite coating was only 10.6%compared to 1 h of immersion，demonstrating excellent long-term protective performance.

YUE Yan, LI Yu, ZHOU Xianxian et al.

[Purposes] Because of the high charging overpotential and lagging electrochemical reaction kinetics caused by the low electronic conductivity of Li2O2 in Li-O2 batteries, it is important to develop cathode catalysts with high activity. [Methods] By coating nitrogen-doped molybdenum disulfide ultra-thin nanosheets on the surface of nitrogen-doped carbon nanotubes, the N-MoS2/N-CNTs composite was prepared through hydrothermal method combined with ammonia annealing method. The morphology, surface element state, and Li-O2 battery electrochemical performance of N-MoS2/N-CNTs were characterized by X-ray diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy, and electrochemical tests. [Results] The cathode obtains high initial charge/discharge capacity (7909/10015 mAh g-1), low charging overpotential, and high catalytic activity. Moreover, the performance of Li-O2 battery is further improved at large O2 mass transfer area. According to electrochemical reaction engineering, it is proposed that the possible initial discharge reaction interface is electrode/Li2O2 interface, and the charging reaction interface is electrode/electrolyte/Li2O2 interface. Three overpotential theories are used to explain the capacity and rate performance improvement mechanism of N-MoS2/N-CNTs cathode Li-O2 batteries, which is the decrease of electrochemical reaction overpotential (ηR) providing more space for the increase of concentration overpotential (ηC).

Ziad F. Doughan, Sari S. Itani

This paper introduces Rectified Discriminatory Delta-Adjust (RDDA), a novel methodology that enhances interpolation-based predictive modeling through adaptive sensitivity parameters. Building upon the foundational Delta-Adjust algorithm, RDDA addresses the limitations of fixed sensitivity parameters by incorporating three dynamic sensitivity estimation methodologies: Sensitivity Analysis (SA), Vector Calculus (VC), and Higher-Order Derivative Methods. The research establishes theoretical foundations for local-to-global emergence in inductive AI systems, proving that local inference mechanisms can reconstruct global information structures through the equivalence of local propagation and global entanglement views of shared information. We demonstrate that temporal ordering in datasets affects information flow profiles, with discriminatory coding revealing that data correlations are non-uniformly distributed across datasets. RDDA’s modular architecture allows plug-in sensitivity estimators to replace fixed parameters with query-adaptive, data-driven sensitivity metrics. Experimental validation across classification, regression, and interpolation tasks demonstrates the competitiveness of the RDDA framework. Its variants sometimes outperform the vanilla Delta-Adjust method. On interpolation benchmarks, RDDA matches the accuracy of dedicated methods like IDW and RBF, while on classification and regression tasks, it delivers performance comparable to established models including SVMs, KNNs, and Random Forests. The methodology preserves Delta-Adjust’s linear time core complexity while adding modular sensitivity estimation overhead, enabling practical deployment in data-driven modeling applications where local-to-global emergence is essential.

Carlos Arriaga, Alejandro Pozo, Alvaro Alonso

Massive online and hybrid events have become important during and after the COVID-19 pandemic. These events aim to replicate live experiences by maintaining interaction between the speakers and the audience. However, existing streaming and videoconferencing solutions fail to provide sufficient scalability and real-time interactions. Streaming technologies lack support for live interaction, whereas videoconferencing technologies scale enough. Events such as panel debates, conference presentations, and sessions with live interpretation require both the ability to support a large number of participants and real-time voice interactions. In this paper, we propose a new tree-based architecture that meets both requirements using videoconferencing technologies. This approach combines the scalability of streaming architectures with the low latency of videoconferencing technologies. The objective was to increase the maximum number of participants that videoconference providers can accept while maintaining live interactions. A prototype implementation of the proposed architecture was developed to test and validate it. Finally, this study provides valuable information for implementing and adapting the proposed architecture to various production environments.

Wei Ren, Xi Zhang, Ziyan Zhu et al.

Electron collimation via a graphene pn-junction allows electrostatic control of ballistic electron trajectories akin to that of an optical circuit. Similar manipulation of novel correlated electronic phases in twisted-bilayer graphene (tBLG) can provide additional probes to the underlying physics and device components towards advanced quantum electronics. In this work, we demonstrate collimation of the electron flow via gate-defined moiré barriers in a tBLG device, utilizing the band-insulator gap of the moiré superlattice. A single junction can be tuned to host a chosen combination of conventional pseudo barrier and moiré tunnel barriers, from which we demonstrate improved collimation efficiency. By measuring transport through two consecutive moiré collimators separated by 1 um, we demonstrate evidence of electron collimation in tBLG in the presence of realistic twist-angle inhomogeneity.

Jorge Buzzio-Garcia, Jaime Vergara, Santiago Rios-Guiral et al.

In the contemporary cybersecurity landscape, robust attack detection mechanisms are important for organizations. However, the current state of research in Software-Defined Networking (SDN) suffers from a notable lack of recent SDN-OpenFlow-based datasets. This study seeks to bridge this gap by introducing a novel dataset for intrusion detection in Software-Defined Networking named SDNFlow. The dataset, derived from OpenFlow statistics gathered from real traffic, integrates a comprehensive range of network activities. An empirical evaluation leveraging diverse Machine and deep Learning algorithms was performed. Namely, Logistic regression, decision tree, random forest, K-nearest neighbors, Support Vector Machines, and Multilayer Perceptron were tested getting pretty good results with a precision average of 98% to 99% in binary classification and from 97% to 99% in multiclass classification depending of the attack, we highlight the efficacy of K-Nearest Neighbors (KNN) for traffic classification, particularly in detecting DDoS attacks and port scanning. The dataset is valuable for evaluating intrusion detection systems within SDN environments and deepening the understanding of traffic patterns in Software Defined Networks.

Francesco Toscano, Costanza Fiorentino, Nicola Capece et al.

Digital Precision Agriculture (DPA) is a comprehensive approach to agronomic management that utilizes advanced technologies, such as sensor data analysis and automation, to optimize crop productivity, enhance farm income, and minimize environmental impacts. DPA encompasses various agricultural domains, including pest control, pest management, fertilization, irrigation management, sowing, transplanting, crop health monitoring, yield forecasting, harvesting, and post-harvest stages. Among the enabling technologies for DPA, Unmanned Aerial Vehicles (UAVs) have gained significant attention and market growth. The advancements in control systems, robotics, electronics, and artificial intelligence have led to the development of sophisticated agricultural drones. UAVs offer advantages such as versatility, quick and accurate remote sensing capabilities, and high-quality imaging at affordable prices. Furthermore, the miniaturization of sensors and advancements in nanotechnology enable UAVs to perform multiple operations simultaneously without compromising flight autonomy. However, various variables, including aircraft mass, payload capacity, size, battery characteristics, flight autonomy, cost, and environmental conditions, impact the performance and applicability of UAV systems in agriculture. The economic considerations involve the purchase of drones, equipment, and the expertise of trained pilots for flight management and data processing. Payload capacity, flight range, and financial factors influence agriculture’s choice and implementation of UAVs. The research and patent trends show the growing interest in UAVs for agricultural applications. This paper provides a general review of UAV types, construction architectures, and their diverse applications in agriculture until 2022.

Dong Wang, Wenzhe Chen, Jiali Chen et al.

In individuals afflicted with hemophilia, characterized by a deficiency of coagulation factor VIII (FVIII), the occurrence of spontaneous recurrent intra-articular hemorrhage precipitates the emergence of hemophilic arthropathy (HA). Although clotting factor replacement therapy reduces joint bleeding clinically, clotting factors need to be injected frequently due to the rapid diffusion of the drug. Hence, a novel drug delivery approach may be developed to improve the drug therapy. Platelet-derived extracellular vesicles (PEVs) are known to possess anti-inflammatory and hemostatic properties and could be used as a potential HA therapy. In this study, we constructed a PEV-LS@FVIII nanotherapeutic system by combining thioketal (TK), liposomes (LS), and FVIII to form the LS@FVIII complexes, and then hybridizing PEV with LS@FVIII. Our results demonstrated that PEV-LS@FVIII could efficiently facilitate FVIII delivery and specifically target the injured knee joint. Both in vitro and in vivo studies showed a reduction in the M1 phenotype of macrophages and an enhancement of the M2 phenotype, compared to FVIII free control. Furthermore, PEV-LS@FVIII appeared to alleviate HA-induced cartilage damage. In conclusion, our findings demonstrate that PEV-LS@FVIII could delay the progression of HA by targeting bleeding joints, modulating macrophage polarization to suppress inflammation, and mitigating cartilage damage.