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Open Access

Article

17 April 2026

Electrical and Thermal Performance of SiC Wide-Bandgap Power Devices: Influence of Package Configuration

Wide Bandgap (WBG) semiconductors, particularly Silicon Carbide (SiC), have become pivotal in advancing high-efficiency, high-power-density systems. Cascode configurations, combining a high-voltage SiC JFET with a low-voltage Si MOSFET, enable Normally-OFF operation while leveraging SiC’s superior switching and thermal properties. However, co-packaging these devices introduces critical design challenges related to parasitic inductance, thermal management, and reliability. This study investigates the impact of bonding configuration and die-attach material selection on dynamic and thermal performance in SiC-based modules. Double Pulse Test (DPT) results reveal that direct bonding provides a better tradeoff between switching losses and dynamic operation stability, mitigating VDS overshoot, gate oscillation, and EMI risk, thereby improving switching stability under system-level stress. Conversely, indirect bonding increases inductance, amplifying oscillations and dynamic stress during turn-off events. Thermal analysis demonstrates that while system-level cooling dominates Rthja, the adoption of sintered silver (Ag) as a die-attach material achieves ~20% reduction in Rthjc, lowering junction temperatures and enhancing reliability for high-power applications. These findings underscore the importance of interconnect design and attach material optimization in achieving robust, high-efficiency operation of wide-bandgap devices.

Keywords: SiC; JFET; Cascode; Double Pulse Test (DPT); Bonding topology; Interconnect; Die attach; Pressure-less sintered silver; RthJC; Thermal resistance; Wide‑bandgap (WBG) devices; Power modules
Intell. Sustain. Manuf.
2026,
3
(1), 10008; 
Open Access

Article

09 April 2026

Flexible Zinc-Ion Battery-Powered Wearable Devices for Vital Sign Monitoring

Wearable devices play a crucial role in real-time health monitoring by continuously tracking important physiological indicators such as heart rate, blood oxygen saturation, and body temperature. This not only helps achieve personalized health management but also enables early disease warning. However, traditional rigid power sources (such as lithium-ion batteries) are difficult to adapt to the dynamic deformations of wearable devices in use, such as bending and stretching, and also pose certain safety risks. Therefore, developing flexible energy storage systems that combine high safety, good mechanical flexibility, and high energy density has become an important research direction. Flexible zinc-ion batteries are regarded as a promising solution due to their use of non-flammable aqueous electrolytes, abundant resources, low cost, and good mechanical adaptability. This article systematically reviews the latest progress of flexible zinc-ion batteries, covering key components (electrodes, electrolytes, packaging), device structure design, integration solutions with wearable sensors, and their applications in scenarios such as electrocardiogram monitoring, body temperature tracking, and motion monitoring. The article also explores the current challenges that still exist in terms of energy density, cycle life, mechanical-electrochemical stability, and biocompatibility. Finally, the development directions of future practical applications were prospected, with a focus on innovative material design, structural optimization, intelligent system integration, and the promotion of related standardization.

Keywords: Flexible zinc-ion batteries; Wearable devices; Health monitoring; Flexible electronics; Energy integration; Aqueous electrolytes; Self powered system; Biocompatibility
Adv. Mat. Sustain. Manuf.
2026,
3
(2), 10006; 
Open Access

Review

31 March 2026

The Future of Environmentally Powered Gliders: Emerging Prospects and Trends

To address the endurance limitations of traditional electrically driven underwater gliders, which are constrained by onboard battery energy density, harnessing marine renewable energy for propulsion or supplemental power has emerged as a critical approach to overcoming their operational endurance bottleneck. This paper systematically reviews the research progress on underwater gliders powered by environmental energy sources, such as thermal and solar. It provides an in-depth analysis of the utilization mechanisms, core technologies, and current challenges associated with each energy type, with a focused exploration of technical pathways for achieving energy synergy and enhancing system endurance through multi-energy integration and intelligent energy management. Furthermore, this study is the first to establish a comprehensive technical evaluation framework for environmentally powered gliders from three dimensions: energy coupling, system design, and mission adaptability, offering a systematic reference for subsequent research. The paper also explores the application potential of this technology in advanced scenarios, such as long-term ocean observation and dynamic environmental monitoring. Future efforts should prioritize efficient multi-energy hybridization, dynamic energy management, and mission-adaptive control to comprehensively enhance the endurance and operational reliability of gliders in complex marine environments.

Keywords: Underwater glider; Environmental energy propulsion; Endurance enhancement; Long-term ocean observation
Mar. Energy Res.
2026,
3
(2), 10007 ; 
Open Access

Article

30 March 2026

A Fast Acting Quantized Energy Balance Criterion for Power System Instability Detection Based on WAMPAC GOOSE Pulses Induced by Small Speed Perturbations

A newly developed stability assessment tool for a power system is proposed in this paper based on estimating the kinetic energy-time variations. It aims to introduce a practical alternative to the Equal Area Criterion (EAC) method that is valid for multi-swing cases. It utilizes the Generic Object Oriented Substation Event (GOOSE) packets launched due to angle variations during swing by the Intelligent Electronic Devices (IEDs) measuring the generator bus angle. The scheme maps the GOOSE packets to quantized energy levels. The detector IED receives the launched GOOSE from disturbed generators through the Wide Area Monitoring, Protection and Control (WAMPAC) System and evaluates the system stability accordingly. The areas under the positive energy intervals above the time axis determine the stability for the oscillatory swing. It has been proven that the area under positive energy levels is proportional to the number of GOOSE packets emitted during these intervals. For the fast monotonic swing, the quantized energy pattern shows quasi-stable intermediate energy levels between two high energy levels, where the scheme detects the transition to the second higher level as an indication of instability, with enough time in advance for corrective measures. The scheme is Phasor Measurement Unit (PMU)-independent, thus eliminating the burden and cost of synchronization requirements. The new scheme has been tested using the IEEE 39 Bus System. The results show the scheme’s capability to predict instability 87 ms prior to its occurrence, which is an adequate time for remedial action.

Keywords: Quantized energy; Energy swing balance; Power swing; Stability assessment; GOOSE; WAMPAC
Smart Energy Syst. Res.
2026,
2
(1), 10005; 
Open Access

Article

30 March 2026

Evaluation of Power Grid Investment Effectiveness in New Power Systems Considering Decision Psychology and Sustainable Development: An Empirical Study Based on Chinese Urban Power Grid Simulation

The evaluation of investment effectiveness in power grids oriented towards new-type power systems is a critical issue for advancing grid transformation and enhancing the scientific basis of investment decision-making. To address the current challenges—such as single-dimensional evaluation, strong subjectivity in index weighting, and insufficient consideration of risks and decision-makers’ psychological factors—this paper aims to construct a hybrid evaluation framework that comprehensively reflects both objective data and subjective decision-making preferences. First, a comprehensive evaluation index system is established, encompassing four dimensions: low-carbon performance, safety, economic efficiency, and intelligence. Second, an innovative integration of the Back Propagation Neural Network (BPNN), the CRITIC method, and the Entropy Weight Method (EWM) is conducted. The combination weights are determined through game theory to scientifically quantify the importance of each index. Based on this, the Improved Cumulative Prospect Theory (ICPT) is introduced to characterize decision-makers’ psychological behavior under uncertainty. Furthermore, by combining Grey Relational Analysis (GRA) and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), an ICPT-GRA-TOPSIS comprehensive evaluation model is constructed. An empirical study of 13 typical urban power grids in China reveals that the proposed model can effectively identify the strengths and weaknesses of investment effectiveness across different regions, categorizing them into development tiers such as “multi-objective collaborative leading type”, “key breakthrough but unbalanced type”, and “system-lagging type”. More importantly, the sensitivity analysis of decision-making psychology demonstrates that the evaluation of investment strategies is highly dependent on decision-makers’ risk attitudes and value orientations. This provides critical quantitative decision-making references for formulating differentiated, precise investment strategies for power grids, offering significant theoretical and practical value for guiding power grid enterprises in optimizing resource allocation and supporting the construction of new-type power systems.

Keywords: New power system; Power grid investment effectiveness evaluation; Combined weighting method; Cumulative prospect theory; Comprehensive evaluation
Clean Energy Sustain.
2026,
4
(1), 10006; 
Open Access

Review

27 March 2026

Artificial Intelligence in Photovoltaic Power Systems: A Bibliometric and Thematic Analysis of Knowledge Structures, Research Evolution, and Emerging Directions Toward Sustainable Energy Systems

Artificial intelligence (AI) has rapidly become a core enabling technology in photovoltaic (PV) power systems, supporting improvements in forecasting accuracy, operational control, fault diagnosis, and system-level energy management. Despite the rapid growth of this field, a comprehensive understanding of its intellectual structure, thematic evolution, and emerging methodological directions remains fragmented. To address this gap, this study develops an integrated bibliometric-thematic analysis framework to systematically map the knowledge structure, research trajectories, and methodological frontiers of AI applications in PV power systems. The analysis is based on 4752 peer-reviewed journal articles indexed in Scopus (2006–2025). It combines performance analysis, co-citation analysis, keyword co-occurrence analysis, and bibliographic coupling to answer five structured research questions. The results demonstrate that PV power forecasting constitutes the central intellectual backbone of AI-based PV research, with the highest citation concentration and the strongest thematic connectivity across clusters. Thematic evolution analysis reveals a clear methodological transition from conventional machine learning models toward hybrid deep learning architectures, uncertainty-aware prediction frameworks, and physics-based AI integration. Furthermore, emerging research frontiers are characterized by generative learning models, multi-source data fusion strategies, and resilience-oriented fault diagnostics, while critical gaps persist in benchmarking standardization, uncertainty quantification, system-level integration, and large-scale industrial deployment. Unlike prior reviews that focus on isolated technical applications, this study provides the first integrated performance analysis and science-mapping synthesis that connects intellectual foundations, thematic evolution, and frontier innovations across the entire AI-based PV ecosystem. The findings offer a structured research roadmap and actionable guidance for researchers, PV plant operators, and policymakers aiming to design intelligent, scalable, and resilient PV energy systems that support the global low-carbon transition.

Keywords: Artificial intelligence; Photovoltaic power systems; Machine learning; Deep learning; Power forecasting; Intelligent control; Fault diagnosis; Bibliometric-thematic analysis
Open Access

Review

25 March 2026

Towards an Integrated Future: Examining Water, Climate, and Gender Dynamics for Sustainable Development in Kenya

Kenya’s sustainable development is increasingly shaped by climate variability and climate change, which affect both the availability and quality of water resources. Existing research shows that these impacts are often gendered, particularly where women and girls hold primary household responsibilities for water collection and water-related care work. Literature also indicates that impacts differ substantially by location (arid versus highland versus informal urban settlements), livelihood system (pastoral versus agro-pastoral versus peri-urban), socio-economic status, and age. This study presents a systematic review of peer-reviewed literature examining how water stress, climate pressures, and gender dynamics intersect in Kenya. Three recurring themes emerge: first, climate change makes water supplies less safe, more expensive, and harder to predict. Second, social and political structures dictate who suffers most from these changes. Third, while women drive local climate adaptation and advocacy, they still lack a consistent voice in formal decision-making. The study concludes by identifying points of agreement and disagreement in current literature, while highlighting remaining evidence gaps regarding the shifting dynamics of climate, water, and gender relations in Kenya.

Keywords: Kenya; Integrated water resources management (IWRM); Climate resilience; Gender-responsive policies; Women’s empowerment; Sustainable development goals (SDGs)
Rural Reg. Dev.
2026,
4
(2), 10010; 
Open Access

Article

16 March 2026

Research on the Bearing Characteristics of Bucket Foundations for Offshore Wind Turbines in Double-Layered Clay

Bucket foundations have been widely used in marine engineering, such as offshore wind power, due to their anti-overturning performance and convenient installation. In China’s coastal areas, clay soil is widely distributed, and most of the seabed has layered clay. However, the bearing capacity of bucket foundations in layered soil is significantly different from that in homogeneous soil. Currently, there is relatively little research on the bearing capacity of bucket foundations in layered clay. Therefore, the finite element analysis method is adopted to establish a bearing capacity calculation method of bucket foundations in double-layer clay. The axial failure mechanisms and ultimate bearing capacity of bucket foundations in double-layer clay are deeply discussed, and the corresponding ultimate bearing capacity calculation method is given based on the numerical analysis results. The combined bearing capacity of bucket foundations in double-layer clay is fully analyzed, and the evolution method of V-H, V-M, H-M, and V-H-M failure envelopes is given.

Keywords: Bucket foundation; Numerical analysis; Double-layered clay; Offshore wind power
Mar. Energy Res.
2026,
3
(1), 10004; 
Open Access

Article

16 March 2026

Domain-Specific Cloud Business Operating System for New Power Systems: Concept, Key Technologies and Initial Applications

The deep digitization of power system business faces three major challenges: computational resources are prone to crashes, business response is slow, and platform maintenance is unsustainable. To address these issues, this paper proposes a domain-specific cloud Business Operating System (BOS) for new power systems. BOS establishes a unified management paradigm for four core digital objects—Containers, Tasks, Programs, and Data—through their standardized definition and indexed organization. Building upon this foundation, it implements three dedicated plugins to enable synergistic task-container co-scheduling, plug-and-play program integration, and optimized data access. This paper elaborates on BOS’s architecture and its rationale as an operating system, detailing the key technologies for object management. Case studies on a real-world regional power grid demonstrate that BOS effectively ensures the efficient execution of large-scale computational tasks, supports the agile integration of domain-specific models and algorithms, achieves seamless and efficient data connectivity across business chains, thereby providing a robust foundation for next-generation power system digitization.

Keywords: Power system business digitalization; Cloud computing architecture; Computational resilience; Operational efficiency; Platform maintainability; Task-container co-scheduling; Plug-and-play integration; Unified data foundation
Smart Energy Syst. Res.
2026,
2
(1), 10004; 
Open Access

Review

13 March 2026

Recent Progress in Photonic Design and Charge Transport Optimization for Organic Solar Cells

Organic solar cells (OSCs) are attracting attention as a possible replacement for traditional photovoltaics because they are low-cost, lightweight, and have adjustable optoelectronic features. The commercialization of single-junction OSCs still faces challenges in achieving high power conversion efficiency (PCE) and operating stability. Recent developments in photonic crystals, plasmonics, nanophotonics, and metamaterials have significantly addressed these issues, especially in single-junction systems. This paper reviews the latest advancements in charge transport engineering, nanophotonic light-trapping methods, and nanostructured interfaces specifically designed for single-junction OSCs. It also highlights recent record-breaking efficiencies that exceed 20% PCE. We discussed integrating plasmonic nanoparticles, optical microcavities, nanostructured electrodes, and improved photonic materials to increase light absorption, exciton dissociation, and charge collection within the specific limitations of single-junction devices. Furthermore, we stress the important role of computational modeling and recent experimental breakthroughs in enhancing optical and electrical performance. Rather than treating optical and electrical processes independently, this review emphasizes the synergistic role of photonic enhancement strategies in simultaneously improving light trapping and charge transport, highlighting how nanophotonic designs influence carrier generation, recombination, and extraction in single-junction OSCs.

Keywords: Organic solar cells; Photonics; Nanophotonic; Plasmonic; Light-trapping; Optoelectronics; Power conversion efficiency; Metamaterials; Charge transport
Clean Energy Sustain.
2026,
4
(1), 10004; 
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