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Background and Clinical Significance: Spina bifida in the cervical region is closely associated with Chiari malformation, which is an amalgamation of terminology for separate conditions with similar pathophysiological mechanisms and progression from one another. Chiari malformations are associated with varying degrees of dilation of the foramen magnum or lack of fusion of the occipital bone with syringomyelia, herniation of the cerebellum, occipitocele and occipitomyelocele; Case Presentation: A previously healthy 23-year-old primigravida presented to our institution due to fetal demise in the third lunar month, established on routine outpatient maternal consultation. Point-of-care ultrasound revealed an amniotic sac measuring 3 cm in diameter and containing a single fetus, without cardiac function. Due to these, the patient was scheduled for pregnancy termination, during which the cervix was noted to be spontaneously dilated and abrasion accomplished complete evacuation of the amniotic sac, without its rupture. Upon sectioning of the amniotic sac, a fetus, measuring 2.5 cm in length, was noted, with a significant cuffing of the occipital and cervical paraspinal region. Histology revealed fetal structures with an adequate maturation index for its gestational age, but it presented with a pronounced meningoencephalomyelocele in the cervical and thoracic regions, characterized by the complete absence of vertebral arches and spinous processes from the atlanto-occipital to the sacral region; Conclusions: In the present case, not only is a significant and complex form of Chiari type III reported, but the condition is also associated with spina bifida aperta in all spinal regions, leading to meningoencephalomyelocele, incompatible with life. Full article

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14 pages, 390 KB

Open AccessArticle

Deviant Behavior in Young People After COVID-19: The Role of Sensation Seeking and Empathy in Determining Deviant Behavior

by Marta Floridi, Allison Uvelli, Benedetta Tonini, Simon Ghinassi, Silvia Casale, Gabriele Prati, Giacomo Gualtieri, Alessandra Masti and Fabio Ferretti

COVID 2025, 5(10), 173; https://doi.org/10.3390/covid5100173 (registering DOI) - 12 Oct 2025

Abstract

Background: The COVID-19 pandemic significantly impacted adolescent development, increasing behavioral problems and emotional distress. This study aimed to examine the impact of sensation seeking, empathy, and COVID-19-related stressors on deviant behavior in adolescents. Methods: A cross-sectional study was conducted with 638 Italian adolescents and young adults (M = 18.8 years, SD = 3.51) recruited from schools, universities, and the general population in Tuscany and Emilia-Romagna. Participants completed validated measures assessing sensation seeking, empathy, COVID-19-related stress, and deviant behaviors. Multiple regression analyses examined predictors of deviant behavior, while mediation analyses tested whether empathy mediated the relationship between sensation seeking and deviant behavior. Results: Correlation analyses show a positive association between sensation seeking and deviant behavior and a weaker positive association with COVID-19 isolation. Conversely, affective empathy demonstrated negative correlations with both deviant behavior and sensation seeking. COVID-19 stress demonstrated differentiated effects: social isolation increased deviance, whereas fear of contagion was protective. Mediation analysis revealed that affective empathy partially mediated the relationship between sensation seeking and deviance. Conclusions: This study demonstrates that sensation seeking is a primary risk factor for deviant behavior in adolescents and young adults, while affective empathy acts as a protective mechanism that partially mediates this relationship. Furthermore, COVID-19-related stressors have shown complex effects, with social isolation amplifying the risk of deviance, while fear of contagion promotes more inhibited behavior. These findings underscore the importance of considering both stable personality traits and situational stressors when seeking to understand the pathways leading to adolescent behavioral problems during periods of social crisis. Full article

(This article belongs to the Section COVID Public Health and Epidemiology)

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30 pages, 11699 KB

Open AccessArticle

Urban Air Mobility Vertiports: A Bibliometric Analysis of Applications, Challenges, and Emerging Directions

by Yannan Lu, Weili Zeng, Wenbin Wei, Weiwei Wu and Hao Jiang

Appl. Sci. 2025, 15(20), 10961; https://doi.org/10.3390/app152010961 (registering DOI) - 12 Oct 2025

Abstract

Vertiports, as the foundational ground infrastructure for Urban Air Mobility (UAM), have garnered increasing scholarly attention in recent years. To examine how the existing literature has reviewed and summarized vertiport-related knowledge, this study conducts a bibliometric analysis of publications (2000–2024) from four major databases, including Web of Science and Scopus, using VOSviewer and CiteSpace. By analyzing co-citation and keyword co-occurrence patterns, the results suggest that vertiport research frontiers are shifting toward facility location, network planning, airspace and scheduling management, scalable infrastructure, and integration with ground transport systems. Scholars and institutions in the United States, China, Europe, and South Korea have taken leading roles in advancing this field, though collaboration among research organizations still requires strengthening. Overall, the findings reveal future research pathways and provide support for the planning and integration of vertiport infrastructure in UAM operations. Full article

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33 pages, 66841 KB

Open AccessArticle

VR Human-Centric Winter Lane Detection: Performance and Driving Experience Evaluation

by Tatiana Ortegon-Sarmiento, Patricia Paderewski, Sousso Kelouwani, Francisco Gutierrez-Vela and Alvaro Uribe-Quevedo

Sensors 2025, 25(20), 6312; https://doi.org/10.3390/s25206312 (registering DOI) - 12 Oct 2025

Abstract

Driving in snowy conditions challenges both human drivers and autonomous systems. Snowfall and ice accumulation impair vehicle control and affect driver perception and performance. Road markings are often obscured, forcing drivers to rely on intuition and memory to stay in their lane, which can lead to encroachment into adjacent lanes or sidewalks. Current lane detectors assist in lane keeping, but their performance is compromised by visual disturbances such as ice reflection, snowflake movement, fog, and snow cover. Furthermore, testing these systems with users on actual snowy roads involves risks to driver safety, equipment integrity, and ethical compliance. This study presents a low-cost virtual reality simulation for evaluating winter lane detection in controlled and safe conditions from a human-in-the-loop perspective. Participants drove in a simulated snowy scenario with and without the detector while quantitative and qualitative variables were monitored. Results showed a 49.9% reduction in unintentional lane departures with the detector and significantly improved user experience, as measured by the UEQ-S (p = 0.023, Cohen’s d = 0.72). Participants also reported higher perceived safety, situational awareness, and confidence. These findings highlight the potential of vision-based lane detection systems adapted to winter environments and demonstrate the value of immersive simulations for user-centered testing of ADASs. Full article

(This article belongs to the Topic Extended Reality: Models and Applications)

17 pages, 2514 KB

Open AccessArticle

Numerical Investigation of Pyrolytic Coking and Its Effects on Heat Transfer of RP-3

by Xizhuo Hu, Peng Zhang, Jianqin Zhu, Zeyuan Cheng and Shuang Sun

Aerospace 2025, 12(10), 919; https://doi.org/10.3390/aerospace12100919 (registering DOI) - 12 Oct 2025

Abstract

Hydrocarbon fuels are extensively employed as coolants in the regenerative cooling systems of scramjet engines. However, the pyrolytic coking of hydrocarbon fuels at high temperatures introduces complex adverse effects on the flow and cooling processes. In this study, a numerical model was developed to investigate the coupling processes of fluid flow, heat transfer, pyrolysis and pyrolytic coking in the heated tube, under both a constant outer wall heat flux of 1.8 MW/m² and a constant outer wall temperature of 1150 K. The multi-step pyrolytic reaction mechanism and the kinetic coking model were applied to simulate the pyrolytic coking processes of RP-3. The results reveal that the amounts of catalytic coking and lateral growth exhibit significant differences in magnitude, as well as in their spatial and temporal variations. Under a constant outer wall heat flux, coking evidently increases the outer wall temperature and thermal resistance, leading to a narrowed flow passage and a reduction in the residence time and RP-3 conversion rate. Under a constant outer wall temperature, coking decreases the heat absorption flux, resulting in a lower fluid temperature, which primarily affects the efficiency of the endothermic pyrolytic reaction. The results obtained in this research can provide practical insights for the development of regenerative cooling technology. Full article

(This article belongs to the Section Aeronautics)

20 pages, 2431 KB

Open AccessReview

Advancing Clinical and Pathophysiological Insights into Pancreatitis Using Lipidomics and Metabolomics

by Faizan Ahmed, Xueheng Zhao, Kenneth D. R. Setchell and Maisam Abu-El-Haija

Metabolites 2025, 15(10), 666; https://doi.org/10.3390/metabo15100666 (registering DOI) - 12 Oct 2025

Abstract

Acute pancreatitis (AP) and chronic pancreatitis (CP) are distinct inflammatory conditions with significant clinical burden, including associated complications and mortality. These pancreatic conditions share overlapping pathophysiologic features. Although AP can be followed by recurrent episodes (recurrent acute pancreatitis, RAP), most CP does not follow a simple linear progression from AP; rather, CP reflects sustained processes causing injury to the pancreas (e.g., toxic-metabolic, genetic, obstructive), leading to fibrosis and organ dysfunction. Lipidomics and metabolomics can provide insights into the pathophysiology of the disease. Although researchers have extensively explored lipids and metabolites to better understand disease mechanisms, comprehensive detailed insights into the pathways and intricate roles these molecules play in pancreatitis remain unidentified. This gap can be partially attributed to limited availability of human samples from disease subgroups in pancreatitis, and current technological constraints in analytical methods, particularly regarding complete lipid and metabolite detection, identification, and quantification. In this review, we summarize lipidomic and metabolomic workflows in the context of understanding pancreatitis pathophysiology, including their design and analytical strategies. We also highlight clinical studies on pancreatitis, utilizing lipidomics and metabolomics as a tool to identify altered or dysregulated lipids or metabolites, and their association with the disease state and its progression. Full article

(This article belongs to the Special Issue Lipidomic Signatures in Pediatric Metabolic Disorders)

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16 pages, 2574 KB

Open AccessArticle

Addressing a Special Case of Zero-Crossing Range Adjustment Detection in a Passive Autoranging Circuit for the FBG/PZT Photonic Current Transducer

by Burhan Mir, Grzegorz Fusiek and Pawel Niewczas

Sensors 2025, 25(20), 6311; https://doi.org/10.3390/s25206311 (registering DOI) - 12 Oct 2025

Abstract

This paper analyses a special case in evaluating the passive autoranging (AR) technique that dynamically extends the measurement range of a fiber Bragg grating/piezoelectric transducer (FBG/PZT) operating with a current transformer (CT) to realize a dual-purpose metering and protection photonic current transducer (PCT). The technique relies on shorting serially connected burden resistors operating with the CT, using MOSFET switches that react to a changing input current to extend measurement range. The rapid changes in the voltage at the FBG/PZT transducer that are associated with the MOSFET switching are then used on the FBG interrogator side to select the correct measurement range. However, when the MOSFET switching in the AR circuit occurs near the zero-crossing of the input current, the rapid changes in the voltage presented to the FBG/PZT no longer occur, rendering the correct range setting at the interrogator side problematic. The basic switching detection algorithm based on voltage derivative (dV/dt) thresholds proposed in the previous research is not sufficiently sensitive in these conditions, leading to incorrect range selection. To address this, a new detection algorithm based on temporal slope differencing around the zero-crossing is proposed as an additional detection mechanism for these special cases. Thus, the improved hybrid algorithm additionally computes the derivative dV/dt at the FBG/PZT voltage signal within a focused 6 ms temporal window centered around the zero-crossing point, a 3 ms window before and after each zero-crossing instance. It then compares the difference between these two values to a predefined threshold. If the difference exceeds the threshold, a switching event is identified. This method reliably detects even subtle switching events near zero crossings, enabling the accurate reconstruction of the burden current. The performance of the improved algorithm is validated through simulations and experimental results involving zero-crossing switching scenarios. Results indicate that the proposed algorithm improves MOSFET switching detection and facilitates reliable waveform reconstruction without requiring additional hardware. Full article

(This article belongs to the Special Issue Optical Sensing in Power Systems)

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17 pages, 7770 KB

Open AccessArticle

Long-Term Runoff Prediction Using Large-Scale Climatic Indices and Machine Learning Model in Wudongde and Three Gorges Reservoirs

by Feng Ma, Xiaoshan Sun and Zihang Han

Water 2025, 17(20), 2942; https://doi.org/10.3390/w17202942 (registering DOI) - 12 Oct 2025

Abstract

Reliable long-term runoff prediction for Wudongde and Three Gorges reservoirs, two major reservoirs in the upper Yangtze River basin, is crucial for optimal operation of cascade reservoirs and hydropower generation planning. This study develops a data-driven model that integrates large-scale climate factors with a Gated Recurrent Unit (GRU) neural network to enhance runoff forecasting at lead times of 7–18 months. Key climate predictors were systematically selected using correlation analysis and stepwise regression before being fed into the GRU model. Evaluation results demonstrate that the proposed model can skillfully predict the variability and magnitude of reservoir inflow. For Wudongde Reservoir, the model achieved a mean correlation coefficient (CC) of 0.71 and Kling–Gupta Efficiency (KGE) of 0.57 during the training period, and values of 0.69 and 0.53 respectively during the testing period. For Three Gorges Reservoir, the CC was 0.67 (training) and 0.66 (testing), and the KGE was 0.52 and 0.49 respectively. The model exhibited robust forecasting capabilities across a range of lead times but showed distinct seasonal variations, with superior performance in summer and winter compared to transitional months (April and October). This framework provides a valuable tool for long-term runoff forecasting by effectively linking large-scale climate signals to local hydrological responses. Full article

(This article belongs to the Section Hydrology)

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21 pages, 2552 KB

Open AccessArticle

Equitable Allocation of Interprovincial Industrial Carbon Footprints in China Based on Economic and Energy Flow Principles

by Jing Zhao, Yongyu Wang, Xiaoying Shi and Muhammad Umer Arshad

Sustainability 2025, 17(20), 9036; https://doi.org/10.3390/su17209036 (registering DOI) - 12 Oct 2025

Abstract

The equitable allocation of carbon emission responsibility is fundamental to advancing China’s industrial decarbonization, achieving its dual-carbon goals, and realizing regional sustainable development. However, prevailing interprovincial carbon accounting frameworks often neglect the coupled dynamics of economic benefits, energy flows, and ecological capacity, leading to systematic misattribution of industrial carbon footprint transfers. Here, we develop an integrated analytical framework combining multi-regional input–output (MRIO) modeling and net primary productivity (NPP) assessment to comprehensively quantify industrial carbon footprints and their transfers across 30 Chinese provinces. By embedding both the benefit principle (aligning responsibility with trade-generated economic gains) and the energy flow principle (accounting for interprovincial energy trade), we construct a dual-adjustment mechanism that rectifies spatial and sectoral imbalances in traditional accounting. Our results reveal pronounced east-to-west industrial carbon footprint transfers, with resource-rich provinces (e.g., Inner Mongolia, Xinjiang) disproportionately burdened by external consumption, impacting the balance of sustainable development in these regions. Implementing benefit and energy flow adjustments redistributes responsibility more fairly: high-benefit, energy-importing provinces (e.g., Shanghai, Jiangsu, Beijing) assume greater carbon obligations, while energy-exporting, resource-dependent regions see reduced responsibilities. This approach narrows the gap between production- and consumption-based accounting, offering a scientifically robust, policy-relevant pathway to balance regional development and environmental accountability. The proposed framework provides actionable insights for designing carbon compensation mechanisms and formulating equitable decarbonization policies in China and other economies facing similar regional disparities. Full article

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34 pages, 9892 KB

Open AccessArticle

Fluid–Structure Interaction Mechanisms of Layered Thickness Effects on Lubrication Performance and Energy Dissipation in Water-Lubricated Bearings

by Lun Wang, Xincong Zhou, Hanhua Zhu, Qipeng Huang, Zhenjiang Zhou, Shaopeng Xing and Xueshen Liu

Lubricants 2025, 13(10), 445; https://doi.org/10.3390/lubricants13100445 (registering DOI) - 12 Oct 2025

Abstract

Traditional single-layer water-lubricated rubber or plastic bearings suffer from water film rupture, excessive frictional losses, and insufficient load-carrying capacity, which limit performance and service life in marine propulsion and ocean engineering. To address these issues, this study introduces an innovative laminated bearing consisting of a rubber composite layer and an ultra-high-molecular-weight polyethylene (UHMWPE) layer. A three-dimensional dynamic model based on fluid–structure interaction theory is developed to evaluate the effects of eccentricity, rotational speed, and liner thickness on lubrication pressure, load capacity, deformation, stress–strain behavior, and frictional power consumption. The model also reveals how thickness matching governs load transfer and energy dissipation. Results indicate that eccentricity, speed, and thickness are key determinants of lubrication and structural response. Hydrodynamic pressure and load capacity rise with eccentricity above 0.8 or higher speeds, but frictional losses also intensify. The rubber layer performs optimally at a thickness of 5 mm, while excessive or insufficient thickness leads to stress concentration or reduced buffering. The UHMWPE layer exhibits optimal performance at 5–7 mm, with greater deviations resulting in increased stress and deformation. Proper thickness matching improves pressure distribution, reduces local stresses, and enhances energy dissipation, thereby strengthening bearing stability and durability. Full article

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18 pages, 5224 KB

Open AccessArticle

Study on the Negative Skin Friction on Bridge Pile Foundations Induced by Backfilling in Karst Areas

by Huiyun Chen, Zhongju Feng, Xiaodong Wei and Ya Li

Buildings 2025, 15(20), 3672; https://doi.org/10.3390/buildings15203672 (registering DOI) - 12 Oct 2025

Abstract

The load transfer mechanism of piles in karst cavity areas was investigated through field tests, and an orthogonal test was carried out to establish a calculation method for negative skin friction induced by backfilling. The results indicate that the negative skin friction of piles is strongly influenced by the type of cavity. When cavities were completely filled with limestone breccia mixed with silty clay and the applied load reached 3628 kN, the unit side friction ranged from 15 to 22 kPa. In contrast, when cavities remained unfilled, soil settlement occurred around the pile after backfilling, leading to the development of negative skin friction. For cavities with heights of 3–12 m, it is recommended that the bearing capacity of piles be calculated by considering negative skin friction at depths of 0H, 0.106H, 0.214H, and 0.271H (where H denotes the cavity height). Based on 21 orthogonal tests, the sensitivity ranking of factors affecting negative skin friction was determined as follows: cavity height > elastic modulus of backfill > pile diameter > cavity span > pile length > cavity position. The calculated values of negative skin friction were further validated against engineering data, showing a variation trend consistent with the test results, with a relative error of only 7.4%. Full article

(This article belongs to the Section Building Structures)

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24 pages, 943 KB

Open AccessReview

A Review on AI Miniaturization: Trends and Challenges

by Bin Tang, Shengzhi Du and Antonie Johan Smith

Appl. Sci. 2025, 15(20), 10958; https://doi.org/10.3390/app152010958 (registering DOI) - 12 Oct 2025

Abstract

Artificial intelligence (AI) often suffers from high energy consumption and complex deployment in resource-constrained environments, leading to a structural mismatch between capability and deployability. This review takes two representative scenarios—energy-first and performance-first—as the main thread, systematically comparing cloud, edge, and fog/cloudlet/mobile edge computing (MEC)/micro data center (MDC) architectures. Based on a standardized literature search and screening process, three categories of miniaturization strategies are distilled: redundancy compression (e.g., pruning, quantization, and distillation), knowledge transfer (e.g., distillation and parameter-efficient fine-tuning), and hardware–software co-design (e.g., neural architecture search (NAS), compiler-level, and operator-level optimization). The purposes of this review are threefold: (1) to unify the “architecture–strategy–implementation pathway” from a system-level perspective; (2) to establish technology–budget mapping with verifiable quantitative indicators; and (3) to summarize representative pathways for energy- and performance-prioritized scenarios, while highlighting current deficiencies in data disclosure and device-side validation. The findings indicate that, compared with single techniques, cross-layer combined optimization better balances accuracy, latency, and power consumption. Therefore, AI miniaturization should be regarded as a proactive method of structural reconfiguration for large-scale deployment. Future efforts should advance cross-scenario empirical validation and standardized benchmarking, while reinforcing hardware–software co-design. Compared with existing reviews that mostly focus on a single dimension, this review proposes a cross-level framework and design checklist, systematizing scattered optimization methods into reusable engineering pathways. Full article

(This article belongs to the Topic The Future of Artificial Intelligence: Trends, Challenges, and Developments)

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30 pages, 538 KB

Open AccessArticle

Differences in Online Consumer Behavior: A Multi-Dimensional Comparative Study in the Context of European Digital Commerce

by Radovan Madlenak, Roman Chinoracky, Natalia Stalmasekova and Lucia Madlenakova

Behav. Sci. 2025, 15(10), 1384; https://doi.org/10.3390/bs15101384 (registering DOI) - 12 Oct 2025

Abstract

The aim of this study was to analyze international differences in online consumer behavior. The analysis was carried out on a sample of 763 participants from the countries of Spain, France, Poland and Russia. Online consumer behavior was examined from the perspective of seven dimensions: shipping-related concerns and preferences, price sensitivity and perceived cost advantage, quality perception, security concerns, time-related benefits, availability and quality of information, and shopping service satisfaction. Data were verified using Average inter-item correlation, the Shapiro–Wilk test and Levene Statistic. Subsequently, Welch’s ANOVA and one-way ANOVA and the Games–Howell and Tukey HSD post hoc tests were applied. Statistically significant differences were fully identified in all examined dimensions. The largest differences were recorded in price sensitivity, shipping-related concerns and security concerns. The effect measurements, in addition to ANOVA and post hoc tests, confirm the significance of these differences. National context, shaped by culture, institutional trust and digital infrastructure, continues to influence online consumer behavior. The strategies that the businesses should adopt should focus on approaches that are tailor-made for a specific market. This means that adapting pricing models, strengthening trust (e.g., through secure payments and strengthening safe return policies), and adapting delivery options to local preferences can lead to improved customer satisfaction in cross-border e-commerce. Full article

(This article belongs to the Special Issue Exploring the Dynamics of Consumer Behavior in Digital Commerce)

15 pages, 636 KB

Open AccessReview

Audiovestibular Dysfunction in Hyper-IgE Syndrome: A Systematic Review of Characteristics, Pathophysiology, Diagnosis, and Management

by Jiann-Jy Chen, Chih-Wei Hsu, Brendon Stubbs, Tien-Yu Chen, Chih-Sung Liang, Yen-Wen Chen, Bing-Yan Zeng and Ping-Tao Tseng

Int. J. Mol. Sci. 2025, 26(20), 9932; https://doi.org/10.3390/ijms26209932 (registering DOI) - 12 Oct 2025

Abstract

Hyper-IgE syndrome (HIES) is a rare genetic immunodeficiency characterized by elevated serum IgE levels and associated immune dysregulation, manifesting in recurrent infections, eczema, and skeletal abnormalities. Emerging evidence suggests a link between HIES and audiovestibular dysfunction, potentially mediated by IgE-driven inflammation in the inner ear, which is not immunologically privileged. However, the nature of this association remains poorly understood. This systematic review synthesizes current evidence on the characteristics, pathophysiology, diagnostic approaches, and management of audiovestibular dysfunction in HIES patients. Literature searches across PubMed, Embase, ClinicalKey, Web of Science, and ScienceDirect (up to 6 August 2025) were conducted in accordance with PRISMA guidelines. Key findings indicate that HIES-related audiovestibular issues, including sensorineural hearing loss and vestibular impairment, may arise from IgE-mediated endolymphatic sac inflammation, leading to hydrops and hair cell damage. Diagnostic tools such as audiometry, electrocochleography, and allergen challenge tests show promise, with elevated IgE correlating with abnormal otoacoustic emissions and prolonged auditory brainstem response latencies. Treatment focuses on immunomodulation (e.g., corticosteroids, dupilumab) to mitigate IgE effects, though evidence is limited to case reports. A proposed schematic diagram illustrates pathophysiology, emphasizing IgE’s role in inner ear toxicity. Timely recognition and intervention may prevent progression to permanent hearing loss or vestibular disability, improving quality of life. Future research should explore genetic–immunologic mechanisms and prospective trials for targeted therapies. Trial registration: PROSPERO CRD420251120600. Full article

(This article belongs to the Special Issue Hearing Loss: Molecular Biological Insights, 2nd Edition)

32 pages, 5297 KB

Open AccessReview

Research Progress on the Influence of Cathode Materials on Thermal Runaway Behavior of Lithium-Ion Batteries

by Yanru Yang, Yang Gao, Yu Miao, Yuan Liang and Xiaoqiang Ren

Batteries 2025, 11(10), 373; https://doi.org/10.3390/batteries11100373 (registering DOI) - 12 Oct 2025

Abstract

The structure, chemical composition, thermal stability, and abuse responses of cathode materials are critical to the safety and economy of lithium-ion batteries (LIBs). This review systematically summarizes advances in research on how cathode materials influence LIB thermal runaway (TR) behavior. It analyzes the oxygen release from cathodes in TR mechanisms and the hazards of such oxygen generation during TR, expounds on how differences in cathode structure, chemical composition, and thermal stability affect TR behavior, and summarizes the thermal characteristics of LIBs with different cathodes under mechanical, electrical, and thermal abuse. Results indicate that oxygen released from cathode decomposition during TR oxidizes electrolytes, releasing substantial heat and gas and causing more severe TR hazards. Structural instability of cathodes leads to accelerated release of lattice oxygen, speeding up TR initiation. Chemical composition regulates thermal stability, phase transition pathways, and gas generation rates during TR, while elemental ratios affect the ease of TR triggering. Cathodes with poor thermal stability have lower thermal decomposition onset temperatures, making TR more likely to occur and intensifying reaction severity. All three abuse types trigger inherent risks of cathodes, inducing TR and significantly increasing its occurrence probability. Differences in intrinsic properties further extend to the system level, also influencing thermal runaway propagation and fire dynamics at the module level. Future research focusing on the intrinsic properties of cathodes and external abuse is of great significance for addressing LIB TR behavior. Full article

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