Search Results (127)

The development of cost-effective and scalable air/oxygen electrode materials is crucial for the advancement of Zn–air batteries (ZABs). Porous carbon materials doped with heteroatoms have attracted considerable attention in energy and environmental fields because of their tunable nanoporosity and high electrical conductivity. In this work, we report the synthesis of a three-dimensional (3D) N and P co-doped porous carbon (PA@pDC-1000), derived from a conjugated polyaniline–phytic acid polymer. The cross-linked, rigid conjugated polymeric framework plays a crucial role in maintaining the integrity of micro- and mesoporous structures and promoting graphitization during carbonization. As a result, the material exhibits a hierarchical pore structure, a high specific surface area (1045 m² g⁻¹), and a large pore volume (1.02 cm³ g⁻¹). The 3D N, P co-doped PA@pDC-1000 catalyst delivers a half-wave potential of 0.80 V (vs. RHE) and demonstrates a higher current density compared to commercial Pt/C. A primary ZAB utilizing this material achieves an open-circuit voltage of 1.51 V and a peak power density of 217 mW cm⁻². This metal-free, self-templating presents a scalable route for the generating and producing of high-performance oxygen reduction reaction catalysts for ZABs. Full article

Brain organoid technology has seen significant development in recent years. This self-organized, three-dimensional, organ-oriented brain tissue model can recapitulate the process of neurogenesis and consists of diverse cell types and cellular architecture. Transplanting brain organoids in vivo could be a potential tool from bench to clinical research and has been studied for many purposes. To investigate and summarize the methodology, findings, and applications of this novel technique from current evidence, we conducted this systematic review by searching PubMed and the Embase databases for the literature ranging from 2013 to 2024. A total of 480 articles were identified, and 24 of them met the inclusion criteria. The results revealed that brain organoid transplantation had promising graft survival, neural proliferation, differentiation, and maturation, axonal growth, and functional integration into the host neuronal circuit, and has been applied to multiple applications, such as therapeutic usage, cell study platforms, and disease modeling. However, heterogeneity among studies, some significant challenges, and ethical issues remain to be considered. This comprehensive review will provide an update of what is known about this powerful, innovative method and discuss some practical aspects for future research. Full article

This paper presents the first demonstration and comparison of two identical oscillator circuits employing piezoelectric zinc oxide (ZnO) microelectromechanical systems (MEMS) resonators, implemented on conventional printed-circuit-board (PCB) and three-dimensional (3D)-printed acrylonitrile butadiene styrene (ABS) substrates. Both oscillators operate simultaneously at dual frequencies (260 MHz and 437 MHz) without the need for additional circuitry. The MEMS resonators, fabricated on silicon-on-insulator (SOI) wafers, exhibit high-quality factors (Q), ensuring superior phase noise performance. Experimental results indicate that the oscillator packaged using 3D-printed chip-carrier assembly achieves a 2–3 dB improvement in phase noise compared to the PCB-based oscillator, attributed to the ABS substrate’s lower dielectric loss and reduced parasitic effects at radio frequency (RF). Specifically, phase noise values between −84 and −77 dBc/Hz at 1 kHz offset and a noise floor of −163 dBc/Hz at far-from-carrier offset were achieved. Additionally, the 3D-printed ABS-based oscillator delivers notably higher output power (4.575 dBm at 260 MHz and 0.147 dBm at 437 MHz). To facilitate modular characterization, advanced packaging techniques leveraging precise 3D-printed encapsulation with sub-100 μm lateral interconnects were employed. These ensured robust packaging integrity without compromising oscillator performance. Furthermore, a comparison between two transistor technologies—a silicon germanium (SiGe) heterojunction bipolar transistor (HBT) and an enhancement-mode pseudomorphic high-electron-mobility transistor (E-pHEMT)—demonstrated that SiGe HBT transistors provide superior phase noise characteristics at close-to-carrier offset frequencies, with a significant 11 dB improvement observed at 1 kHz offset. These results highlight the promising potential of 3D-printed chip-carrier packaging techniques in high-performance MEMS oscillator applications. Full article

The growing demand for reliable micropower sources in extreme environments has accelerated the development of betavoltaic cells (BV cells) with high energy conversion efficiency and superior radiation resistance. This study demonstrates an advanced BV cell architecture utilizing three-dimensional TiO₂ nanorod arrays (TNRAs) integrated with a NiO_x hole transport layer (HTL). Monte Carlo simulations were employed to optimize the cell design and determine the fabrication parameters for growing TNRAs on FTO substrates via hydrothermal synthesis. The performance evaluation employed both electron beam (2.36 × 10⁹ e/cm²·s) and ⁶³Ni (3.4 mCi/cm²) irradiation methods. The simulation results revealed optimal energy deposition characteristics, with ~96% of β-particle energy effectively absorbed within the 2 μm thick FTO/TNRA/NiO_x/Au structure. The NiO_x-incorporated device achieved an energy conversion efficiency of 4.84%, with a short-circuit current of 119.9 nA, an open-circuit voltage of 324.2 mV, and a maximum power output of 24.0 nW, representing a 3.76-fold enhancement over HTL-free devices. Radioactive source testing confirmed stable power generation and linear efficiency scaling, validating electron beam irradiation as an effective accelerated testing methodology for BV cell research. Full article

In the era of artificial intelligence, the demand for rapid and efficient data processing is growing, and traditional computing architectures are increasingly struggling to meet these needs. Against this backdrop, memristor devices, capable of mimicking the computational functions of brain neural networks, have emerged as key components in neuromorphic systems. Despite this, memristors still face many challenges in biomimetic functionality and circuit integration. In this context, a starch–glycerol-based hydrogel memristor was developed using starch as the dielectric material. The starch–glycerol–water mixture employed in this study has been widely recognized in literature as a physically cross-linked hydrogel system with a three-dimensional network, and both high water content and mechanical flexibility. This memristor demonstrates a high current switching ratio and stable threshold voltage, showing great potential in mimicking the activity of biological neurons. The device possesses the functionality of auditory neurons, not only achieving artificial spiking neuron discharge but also accomplishing the spatiotemporal summation of input information. In addition, we demonstrate the application capabilities of this artificial auditory neuron in gain modulation and in the synchronization detection of sound signals, further highlighting its potential in neuromorphic engineering applications. These results suggest that starch-based hydrogel memristors offer a promising platform for the construction of bio-inspired auditory neuron circuits and flexible neuromorphic systems. Full article

This study presents an innovative approach to mitigating the urban heat island (UHI) effect by constructing a cold island spatial pattern (CSP) from the perspective of landscape connectivity, integrating three-dimensional (3D) urban morphology and meteorological factors for the first time. Unlike traditional studies that focus on isolated patches or single-city scales, we propose a hierarchical framework for urban agglomerations, combining morphological spatial pattern analysis (MSPA), landscape connectivity assessment, and circuit theory to a construct CSP at the scale of urban agglomeration. By incorporating wind environment data and 3D building features (e.g., height, density) into the resistance surface, we enhance the accuracy of cooling network identification, revealing 39 cold island sources, 89 cooling corridors, and optimal corridor widths (600 m) in the Changsha–Zhuzhou–Xiangtan urban agglomeration (CZXUA). Ultimately, a three-tiered heat island mitigation framework for urban agglomerations was established based on the CSP. This study offers an innovative perspective on urban climate adaptability planning within the context of contemporary urbanization. Our methodology and findings provide critical insights for future studies to integrate multiscale, multidimensional, and climate-adaptive approaches in urban thermal environment governance, fostering sustainable urbanization under escalating climate challenges. Full article

The growing complexities, power densities, and cooling demands of modern electronic systems and batteries—such as three-dimensional integrated circuit chip packaging, printed circuit board assemblies, and electronics enclosures—have pushed the urgency for efficient and dynamic thermal management strategies. Traditional numerical methods like computational fluid dynamics (CFD) and the finite element method (FEM) are computationally impractical for large-scale or real-time thermal analysis, especially when dealing with complex geometries, temperature-dependent material properties, and rapidly changing boundary conditions. These approaches typically require extensive meshing and repeated simulations for each new scenario, making them inefficient for design exploration or optimization tasks. Physics-informed neural networks (PINNs) emerge as a powerful alternative approach that incorporates physical principles such as mass and energy conservation equations into deep learning models. This approach delivers rapid and adaptable resolutions to the partial differential equations that govern heat transfer and fluid dynamics. This review examines the basic principle of PINN and its role in thermal management for electronics and batteries, from the small unit scale to the system scale. We highlight recent advancements in PINNs, particularly their superior performance compared to traditional CFD methods. For example, studies have shown that PINNs can be up to 300,000 times faster than conventional CFD solvers, with temperature prediction differences of less than 0.1 K in chip thermal models. Beyond speed, we explore the potential of PINNs in enabling efficient design space exploration and predicting outcomes for previously unseen scenarios. However, challenges such as training convergence in fine-grained or large-scale applications remain. Notably, research combining PINNs with LSTM networks for battery thermal management at a 2.0 C charging rate has achieved impressive results—an R² of 0.9863, a mean absolute error (MAE) of 0.2875 °C, and a root mean square error (RMSE) of 0.3306 °C—demonstrating high predictive accuracy. Finally, we propose future research directions that emphasize the integration of PINNs with advanced hardware and hybrid modeling techniques to advance thermal management solutions for next-generation electronics and battery systems. Full article

This study investigates the electromagnetic analysis and optimal design of outer rotor type brushless DC (BLDC) motors for fan filter applications. The primary objective is to develop a method that integrates three-dimensional (3D) structural effects with efficient two-dimensional (2D) equivalent analysis. This study proposes a 2D equivalent analysis method that addresses the unique features of outer rotor type BLDC motors, particularly the permanent magnet (PM) overhang structure. This approach transforms the operating point on the B–H curve to facilitate accurate modeling in a 2D framework, overcoming traditional analysis limitations. An analytical method using spatial harmonics is introduced to derive essential electromagnetic quantities, namely flux linkage and back electromotive force (EMF). The method compensates for slot effects using the Carter coefficient, ensuring precise evaluation of circuit parameters and electromagnetic losses. To optimize motor performance, a multi-objective optimization technique is implemented using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), aiming to maximize both efficiency and power density. The research validates the proposed analytical approach against the finite element analysis method (FEM) results to confirm its accuracy. Full article

This paper introduces a hybrid analytical model (HAM) for the evaluation of permanent-magnet (PM) eddy-current loss in dual-stator single-rotor axial flux permanent-magnet machine (AFPMM), accounting for stator saturation. The proposed model integrates the magnetic equivalent circuit (MEC) with an analytical model based on scalar magnetic potential, enabling simultaneous consideration of different rotor positions and stator slotting effects. The three-dimensional finite element method (3D-FEM) validates the no-load and armature reaction magnetic field calculated by HAM, as well as the PM eddy-current loss under both no-load and load conditions. Compared to 3D-FEM, the proposed model reduces the calculation time by more than 98% with an error of no more than 18%, demonstrating a significant advantage in terms of computational time. Based on the proposed model, the effects of air-gap length and slot opening width on PM eddy-current loss are analyzed; the results indicate that reducing the slot opening width can effectively mitigate PM eddy-current loss for AFPMM. Full article

Harmonic distortion caused by phase jumps in the phase-locked loop (PLL) during asymmetric faults poses a significant threat to the secure operation of renewable energy grid-connected systems. A harmonic suppression strategy based on Vague set theory is proposed for offshore wind power AC transmission systems. By employing the three-dimensional membership framework of Vague sets—comprising true, false, and hesitation degrees—phase-locked errors are characterized, and dynamic, real-time PLL proportional-integral (PI) parameters are derived. This approach addresses the inadequacy of harmonic suppression in conventional PLL, where fixed PI parameters limit performance under asymmetric faults. The significance of this research is reflected in the improved power quality of offshore wind power grid integration, the provision of technical solutions supporting efficient clean energy utilization in alignment with “Dual Carbon” objectives, and the introduction of innovative approaches to harmonic suppression in complex grid environments. Firstly, an equivalent circuit model of the offshore wind power AC transmission system is established, and the impact of PLL phase jumps on grid harmonics during asymmetric faults is analyzed in conjunction with PLL locking mechanisms. Secondly, Vague sets are employed to model the phase-locked error interval across three dimensions, enabling adaptive PI parameter tuning to suppress harmonic content during such faults. Finally, time-domain simulations conducted in PSCAD indicate that the proposed Vague set-based control strategy reduces total harmonic distortion (THD) to 1.08%, 1.12%, and 0.97% for single-phase-to-ground, two-phase-to-ground, and two-phase short-circuit faults, respectively. These values correspond to relative reductions of 13.6%, 33.7%, and 80.87% compared to conventional control strategies, thereby confirming the efficacy of the proposed method in minimizing grid-connected harmonic distortions. Full article

This paper presents a discrete Fourier transform (DFT)-based signal processing framework for eddy current non-destructive testing (NDT), aiming to enhance signal quality for precise defect characterization in critical nuclear components. By enforcing strict periodicity matching between sampling points and signal frequencies, the proposed approach mitigates DFT spectrum leakage, validated via phase linearity analysis with errors of ≤0.07° across the 20 Hz–1 MHz frequency range. A high-resolution 24-bit analog-to-digital converter (ADC) hardware architecture eliminates complex analog balancing circuits, reducing system-wide noise by overcoming the limitations of traditional 16-bit ADCs. A 6 × 6 mm application-specific integrated circuit (ASIC) for array sensors enables three-dimensional (3D) defect visualization, complemented by Gaussian filtering to suppress vibration-induced noise. Our experimental results demonstrate that the digital method yields smoother signal waveforms and superior 3D defect imaging for nuclear power plant tubes, enhancing result interpretability. Field tests confirm stable performance, showcasing clear 3D defect distributions and improved inspection performance compared to conventional techniques. By integrating DFT signal processing, hardware optimization, and array sensing, this study introduces a robust framework for precise defect localization and characterization in nuclear components, addressing key challenges in eddy current NDT through systematic signal integrity enhancement and hardware innovation. Full article

Using novel SiO₂ surface passivation and ultraviolet (UV) light anneal, a 12 nm thick SnO p-type FET (pFET) shows hole effective mobilities (µ_eff) of more than 100 cm²/V·s and 31.1 cm²/V·s at hole densities (Q_h) of 1 × 10¹¹ and 5 × 10¹² cm⁻², respectively. To further improve the on-current/off-current (I_ON/I_OFF), an ultra-thin 7 nm thick SnO nanosheet pFET shows a record-breaking I_ON/I_OFF of 6.9 × 10⁶ and remarkable µ_eff values of ~70 cm²/V·s and 20.7 cm²/V·s at Q_h of 1 × 10¹¹ cm⁻² and 5 × 10¹² cm⁻², respectively. This is the first report of an oxide semiconductor transistor achieving a hole effective mobility µ_eff that reaches 20% of that in single-crystal Si pFETs at an ultra-thin body thickness of 7 nm. In sharp contrast, the control SnO nanosheet pFET without surface passivation or UV anneal exhibits a small I_ON/I_OFF of 1.8 × 10⁴ and a µ_eff of only 6.1 cm²/V·s at 5 × 10¹² cm⁻² Q_h. The enhanced SnO pFET performance is attributed to reduced defects and improved quality in the SnO channel, as confirmed by decreased charges related to sub-threshold swing (SS) and threshold voltage (Vth) shift. Such a large improvement is further supported by the increased Sn²⁺ after passivation and UV anneal, as evidenced by X-ray photoelectron spectroscopy (XPS) analysis. The I_ON/I_OFF ratio exceeding six orders of magnitude, remarkably high hole µ_eff, and excellent two-month stability demonstrate that this pFET is a strong candidate for integration with SnON nFETs in next-generation ultra-high-definition displays and monolithic three-dimensional integrated circuits (3D ICs). Full article

Three-dimensional flexible solar fabrics based on hydrogenated amorphous silicon (a-Si:H) thin film solar cells were prepared and characterized. A glass fiber fabric with a polytetrafluoroethylene (PTFE) coating proved to be a suitable textile substrate. Interwoven metal wires enable an integrated electrical interconnection. An array of solar cells consisting of an a-Si:H layer stack with a highly p-type/intrinsic/highly n-type doping profile was deposited onto it. Silver was used as the back contact with indium tin oxide (ITO) as the front contact. The best solar cells show an efficiency of 3.9% with an open-circuit voltage of 876 mV and a short-circuit current density of 11.4 mA/cm². The high series resistance limits the fill factor to 39%. The potential of the textile solar cells is shown by the achieved pseudo fill factor of 79% when neglecting the series resistance, resulting in a pseudo efficiency of 7.6%. With four textile solar cells connected in a series, an open-circuit voltage of about 3 V is achieved. Full article

A 4H-silicon carbide (SiC) trench gate metal–oxide–semiconductor field-effect transistor (MOSFET) with dual integrated Schottky barrier diodes (SBDs) was characterized using numerical simulations. The advantage of three-dimensional stacked integration is that it allows the proposed structure to obtain an electric field of below 0.6 MV/cm in the gate oxide and SBD contacts and achieve ~10% lower forward voltage of SBDs than the planar gate SBD-integrated MOSFET (PSI-MOS) and the trench gate structure with three p-type-protecting layers (TPL-MOS). The dual-SBD-integrated MOSFET (DSI-MOS) also highlights the better influences of the more than 70% reduction in the miller charge, as well as the over 50% reduction in switching loss compared to the others. Furthermore, the short-circuit (SC) robustness of the three devices was identified. The DSI-MOS attains the critical energy and the aluminum melting point in a longer SC time interval than the TPL-MOS. The p-shield layers in the DSI-MOS are demonstrated to yield the huge benefit of improving the reliability of the contacts when SC reliability is considered. Full article