Reliability Issues Research Articles

Application of MXene Materials in Aqueous Zinc-Ion Batteries

As the global requirement for renewable energy grows, zinc-ion batteries (AZIBs) are an ideal replacement for lithium-ion batteries due to their plentiful zinc resources, inexpensive, and high level of security. Nevertheless, the energy density, circulation reliability, and zinc dendrite formation issues of AZIBs limit their widespread application. MXene materials, featuring a distinctive two-dimensional structure，high-conductivity, and abundant surface functional groups, show great potential in the cathode, anode, separator, and electrolyte of AZIBs. This study systematically explores the applications of MXene materials in various AZIB components, including their roles in enhancing zinc ion transport efficiency, suppressing dendrite growth, and improving battery cycling life.

Organic Permeable Base Transistors—Reliable Large‐Scale Anodization for High Frequency Devices

AbstractOrganic permeable base transistors (OPBTs) have demonstrated impressive performance and potential in various applications, such as display driving circuits, light‐emitting transistors, and logic circuits requiring high‐frequency operation. However, large‐scale implementation is hindered by fabrication reliability and repeatability issues, a problem also common with other types of organic transistors, leading to reliance on exceptional “hero” devices. To address this challenge, an electrochemical anodization process is scaled up and optimized for OPBTs to produce consistent performance across an entire 15 cm × 15 cm wafer. By controlling the Al base oxidation, an 87% yield of functional devices and a median transconductance of d−3is achieved S, proving that the anodization process does not degrade the device performance. Additionally, anodization reduces leakage current to below d−9A, increasing the current gain to a median of 106, and decreases the oxide capacitance (Cox) without affecting the transconductance (gm), resulting in a driving‐voltage normalized unity‐gain cutoff frequency (fT/V) of up to 2.6 MHzV−1. The validity of the experimental results is confirmed through properly calibrated technology computer‐aided design (TCAD) simulations, which rely on DC and small‐signal AC analysis of OPBTs, based on the underlying physical equations.

Application of the quantum effects of single-electron transistors in low-power

As the feature size of transistors approaches the 2nm limit, quantum effects become more pronounced as a result of devices that cannot work properly. Conventional MOSFET architectures are difficult to solve the problems. Therefore, new transistor architectures need to be developed. As a new transistor architecture, the single-electron transistor (SET) working based on quantum effects and has a very low power consumption. This paper analyzed working principle of single-electron transistor (SET) and compared the advantages of its extremely low power consumption in quantum computing with MOSFET. Although single-electron transistors (SET) have many advantages, there still are some challenges. Such as manufacturing technology, stability and reliability issues. As technology advances, single-electron transistor (SET) is expected to play an important role in the future of electronics.

KINDRED: Heterogeneous Split-Lock Architecture for Safe Autonomous Machines

With the increasing practicality of autonomous vehicles and drones, the importance of reliability requirements has escalated substantially. In many instances, traditional system designs tend to overlook reliability issues, emphasizing primarily on performance constraints. On the other hand, certain designers may opt for a lock-step (redundant) system design, duplicating every component, which in turn can result in significant performance, energy, and cost overheads. In software for autonomous machines, such as self-driving vehicles, performance degradation can increase reaction time, posing safety risks and reducing mission success rates. This paper introduces a novel multi-domain lock-step system design, Kindred , which places a strong emphasis on maximizing reliability while minimizing performance overhead. The proposed approach capitalizes on the inherent diversity in fault tolerance among various tasks within autonomous machine software, intelligently scheduling only the vulnerable nodes in the lock-domain. The primary challenge addressed in this study involves the intelligent task scheduling across different domains, complemented by efficient error detection and correction in the lock-domain. In a real system demonstration, we illustrate the effectiveness of Kindred , showcasing its ability to attain the same level of reliability as a full lock-step system while incurring only a mere 2.8% overhead, as opposed to a fully split system, indicating the advantages and potential of our multi-domain lock-step system design in achieving high reliability without compromising performance.

Dynamic reliability estimation of onshore wind turbine tower based on frequency-domain method

With the upscaling of wind turbine, the issue of dynamic reliability of wind turbine towers has become increasingly evident. However, the complexity and nonlinearity of wind turbine dynamics present significant challenges in evaluating their dynamic reliability under stochastic loads, requiring substantial computational resources. In this paper, a computationally cost-effective frequency-domain method is proposed as a means of estimating the dynamic reliability of an onshore wind turbine tower. An analytical approach is employed to obtain the power spectral density (PSD) of the rated wind speed and load on the rotating blades. Secondly, a dynamic model of onshore horizontal axis onshore wind turbine is established using flexible multi-body dynamics (MBD). The linear time-varying dynamic equation is transformed into a linear time-invariant form through the application of statistical linearization method. Subsequently, complex modal analysis is used to employ the displacements and internal forces of the tower. Moreover, the first-passage reliability and fatigue reliability of the wind turbine tower are determined through power spectral analysis. A numerical example of a 5-MW wind turbine is presented to demonstrate that the proposed method yields results in good agreement with Monte Carlo simulations (MCS), thereby demonstrating its effectiveness. The reliability analysis of the 5-MW wind turbine reveals that over a 20-year design life, the first-passage reliability is 0.9997 when adopting fore-after displacement at the tower top as the failure criterion, and the fatigue reliability of the tower base is 0.9445.

Amorphous Ga2O3 Semiconductor: A New Solution for Robust X‐Ray Dosimeters

AbstractAs most commonly used miniature solid‐state dosimeter, metal‐oxide‐semiconductor field effect transistors (MOSFETs) have been facing unavoidable gate leakage and robustness problems due to the double‐sided role of traps in oxide insulators. Herein, a new solution for X‐ray dosimeter has been proposed which leverages the conductivity change of amorphous Ga2O3 (a‐Ga2O3) channel instead of charge trapping in oxide insulators. Increasingly negatively‐shifted threshold voltage (Vth) of a‐Ga2O3 thin‐film transistor is recorded together with almost unchanged subthreshold swing (SS) and field‐effect mobility (µFE) after X‐ray irradiations. X‐ray‐induced‐variation of oxygen vacancy (VO) related defects in a‐Ga2O3 is revealed after a combined investigation of X‐ray photoelectron spectroscopy (XPS) and neutron reflectivity (NR) measurements, contributing to the indicative Vth shift related with X‐ray dosage. A functional recovery is realized through an annealing process in air condition, showing the high reliability of a‐Ga2O3 semiconductor. Moreover, the unique merit of no need for power supply during X‐ray irradiations, beneficial from the slow neutralization rate of ionized VO related defects, imparts an offline working capability to the dosimeter. This work provides a potential strategy to monitor X‐ray dosage via utilizing the X‐ray‐induced change of amorphous oxide semiconductor conductivity, hence addressing the reliability and repeatability issues in present MOSFET devices.

Default mode network functional connectivity as a transdiagnostic biomarker of cognitive function.

The default mode network (DMN) is intricately linked with processes such as self-referential thinking, episodic memory recall, goal-directed cognition, self-projection, and theory of mind. Over recent years, there has been a surge in examining its functional connectivity, particularly its relationship with frontoparietal networks (FPN) involved in top-down attention, executive function, and cognitive control. The fluidity in switching between these internal and external modes of processing-highlighted by anti-correlated functional connectivity-has been proposed as an indicator of cognitive health. Due to the ease of estimation of functional connectivity-based measures through resting state fMRI paradigms, there is now a wealth of large-scale datasets, paving the way for standardized connectivity benchmarks. This review delves into the promising role of DMN connectivity metrics as potential biomarkers of cognitive state across attention, internal mentation, mind wandering and meditation states, and investigating deviations in trait-level measures across aging and in clinical conditions such as Alzheimer's disease, Parkinson's, depression, ADHD, and others. Additionally, we tackle the issue of reliability of network estimation and functional connectivity and share recommendations for using functional connectivity measures as a biomarker of cognitive health.

The enhanced lifetime of printed GaS-based photodetectors with polymer encapsulation

Exhibiting excellent absorption in the UV–visible wavelength range makes layered gallium sulfide (GaS) semiconductor material a promising candidate for use in electronics and optoelectronics applications. Recently, a fully printed GaS-based photodetector has been proposed and fabricated, rendering a low-cost fabrication process in flexible electronics. However, the degradation of the semiconductor layer due to environmental conditions causes reliability issues and shortens their lifetime. Thus, in this study, an attempt has been made to encapsulate printed GaS-based photodetector using different polymers to hinder the degradation. It is demonstrated that encapsulating the printed GaS-based photodetector by utilizing the polymer-capping method with styrene co-polymers, Polystyrene-block-polyisoprene-block-polystyrene, highly hydrogenated poly(styrene)-block-poly(butadiene), partially hydrogenated poly(styrene)-block-poly(butadiene), increases the performance of the photodetector. The efficiency of the GaS-based photodetector printed on flexible polyethylene terephthalate (PET) substrate has reached up to 123 % in responsivity in 6 weeks after the polymer coating. Also, the device figure of merit, the detectivity value of the printed photodetector, has increased more than three times after the polymer coating compared to its as-deposited state. Meanwhile, it is observed that the fall and rise times of the printed GaS photodetector have remained constant. Based on these results attained in this study, it can be claimed that the polymer coating provides high performance and long stability in the printed GaS-based photodetectors on flexible substrates, which will pave the way for the further implementations of III-VI group layered semiconductor materials in electronics and optoelectronics applications.

Reliability and reproducibility of systematic reviews informing the 2020-2025 Dietary Guidelines for Americans: a pilot study.

Although high-quality nutrition systematic reviews (SRs) are important for clinical decision making, there remains debate on their methodological quality and reporting transparency. The objective of this study was to assess the reliability and reproducibility of a sample of SRs produced by the Nutrition Evidence Systematic Review (NESR) team to inform the 2020-2025 Dietary Guidelines for Americans (DGAs). We evaluated a sample of 8 SRs from the DGA dietary patterns subcommittee for methodological quality using the Assessment of Multiple Systematic Reviews 2 (AMSTAR 2) tool and for reporting transparency using the PRISMA 2020 and PRISMA literature search extension (PRISMA-S) checklists. We assessed the quality and reproducibility of the original search strategy of one selected SR using the Peer Review of Electronic Search Strategies checklist. The reporting transparency of the SR's narrative data synthesis was assessed using the Synthesis Without Meta-Analysis (SWiM) checklist. Interpretation bias was evaluated using existing spin bias classifications in systematic reviews. The AMSTAR 2 assessment identified critical methodological weaknesses, and all included SRs were judged to be of critically low quality. Overall, 74% of the PRISMA 2020 checklist items and 63% of the PRISMA-S checklist items were satisfactorily fulfilled. We identified several errors and inconsistencies in the search strategy and could not reproduce searches within a 10% margin of the original results. The SWiM assessment identified concerns regarding the reporting transparency of the narrative data synthesis, but the spin bias assessment revealed no evidence of interpretation bias. Several methodological quality and reporting concerns were identified, which could lead to reliability and reproducibility issues should a full reproduction attempt be made. However, additional research is needed to confirm the impact of these findings on conclusions statements and their generalizability across the NESR team SRs. This study was registered in the Open Science Framework (https://osf.io/ns6a9/).

A novel reliability estimation methodology towards the design and implementation of symmetric multilevel inverter for long run applications

AbstractMultilevel inverters (MLIs) are gaining attention in numerous applications due to their better performance attributes. Still, their utility in long‐run applications remains a critical concern due to the reliability issues. This work proposes a novel reliability estimation methodology tailored specifically for MLIs. The proposed reliability method employs advanced simulation techniques and statistical models to estimate the failure probabilities of critical components within the MLI. The proposed methodology provides a more optimal assessment of the MLI's expected reliability over time. This enables designers and engineers to make informed decisions regarding component selection, system configuration, and maintenance schedules to enhance the long‐term reliability of the MLI. Considering the drawbacks of the existing MLIs, this work has proposed a new symmetrical 7‐level inverter with promising functional and reliability traits. The proposed topology appears to surpass existing topologies in several key metrics, including switching losses, reliability, THD, and component count. The performance of the proposed MLI has been validated through hardware results. These results show that the reliability methodology implemented can accurately estimate the MLI's reliability across various scenarios, enabling the identification of potential failure points and the formulation of strategies to mitigate reliability risks.

Lights-out factories: Review and prospect

Lights-out factories represent the pinnacle of manufacturing advancement, utilizing automation, digitalization, and intelligent technologies for unmanned production. These factories employ advanced tools such as process control systems, smart sensors, and industrial robots to enhance efficiency. Constructing lights-out factories is complex, involving multiple disciplines, and there is a lack of comprehensive literature on the subject, posing challenges for interested companies. This paper presents a lights-out factory architecture diagram and reviews key literature on the topic, summarizing relevant technologies and their social impact. The lights-out factory model can help enterprises reduce costs, increase efficiency, improve production quality, enhance safety, and promote high-quality development. However, challenges remain, including high costs, reliability issues, personnel requirements, applicability concerns, and technological hurdles. Future advancements in sensor technology, digital twin technology, and other innovations will drive further development of lights-out factories.

Map-Matching Algorithm Based on Hidden Markov and Constraint Value Pruning

Map matching is the process of matching global positioning system (GPS) trajectory data with map data. Its purpose is to determine the actual route of the moving object. Because of factors such as positioning devices and the environment, the GPS trajectory data obtained may not be accurate. In location-based services, map matching can be used to address the accuracy and reliability issues of GPS location data. There are currently many map-matching algorithms, for example, spatio-temporal-based (STD) matching algorithm, improved interactive voting-based map-matching (IIVMM) algorithm, and turning-point-based (TPB) offline map-matching algorithm, but existing algorithms have some shortcomings, such as low matching accuracy on complex roads or low sampling rates, and routing calculation time bottlenecks. Therefore, this paper proposes a fast matching algorithm based on constrained value pruning that is suitable for complex roads. The algorithm considers the multi-directional features within the road and uses secondary calculations to determine candidate points, improving the accuracy of candidate point selection. Additionally, two pruning strategies based on constrained values are introduced to reduce the majority of the routing calculation process and improve the matching efficiency. Finally, comparative experiments are conducted on a real trajectory dataset. The results show that, compared with STD, IIVMM, and TPB algorithms, the algorithm accuracy is improved by about 2% to 4%, and the running time is reduced by about 30%.

Real-time cooperative voltage regulation strategy of distribution network based on approximate dynamic programming

Large-scale distributed renewable energy in the distribution network can result in reliability issues such as exceeding voltage limits and overloading power lines. Additionally, the rapid growth of electric vehicles has caused a surge in power demand in the distribution network. Therefore, how to guarantee the real-time stability of distribution network voltage under uncertain environment using available resources is an urgent problem to be solved. To this end, this paper proposes a cooperative voltage regulation of an on-load voltage regulator and electric vehicles for a distribution network considering multiple uncertainties. Firstly, an optimization model of the electric vehicle clusters considering the charging location and power is established, and the traditional on-load voltage regulator of distribution networks is also considered along with network operational constraints. Subsequently, a real-time cooperative voltage regulation strategy based on approximate dynamic programming is proposed, which employs segmented linear functions to process the value function to reduce the distribution network voltage offset and to ensure optimization accuracy. Numerical simulation results validate the feasibility and the effectiveness of the proposed cooperative voltage regulation technology involving electric vehicles and on-load tap changer in the distribution network.

Awareness Level of Farmers on Agricultural Related Softwares for Improved Agricultural Production: Panacea for Food Insecurity in Iseyin Local Government Area of Oyo State

Purpose: The study in its main objective assessed the awareness level of farmers on agricultural related softwares for improved agricultural production in Iseyin Local Government Area, Oyo State, Nigeria. Specifically, the study examined the socio-economic characteristics of respondents; evaluated the level of awareness on agricultural softwares in the study area; investigated the extent of factors influencing usage of agricultural related softwares; assessed the severity of various challenges to usage of agricultural related softwares. The research hypothesis examined significant relationship between the socio-economic characteristics of the respondents and their level of awareness of farmers on agricultural related softwares available to the respondents. Materials and Methods: A well- structured interview schedule was used to collect primary data. A total of 75 respondents were selected. Both descriptive statistics and inferential statistical analysis were employed in data analysis. Findings: The study revealed that male (64.0%) population is more than population of female (36.0%) in the study area. Results further revealed that aside automated poultry machine, weather forecasting tools was the most aware agricultural softwares in the study area. The study also deduced that factors influencing usage of agricultural softwares was access to technology with highest frequency of 97.3%. Limited digital infrastructure, regulatory and policy issues, reliability and connectivity issues and awareness and perception was ranked 1st in the challenges facing the respondents to usage agricultural related softwares. Chi-square analysis revealed a significant relationship between socio-economic characteristics of sex (x2 = 5.88, p= 0.015), religion (x2 = 26.16, p= 0.000002), marital status (x2 = 184.94, p= 0.00001), secondary occupation (x2 = 45.02, p = 0.001), year of farming experience (x2 = 6.72, p= 0.035) and aspect of farming enterprise (x2 = 174.54, p= 0.001) meanwhile, educational status do not to have a significant relationship on the awareness level of farmers on agricultural related softwares. Implications to Theory, Practice and Policy: The study recommended improved awareness of less-known agricultural softwares like precision agronomy and data management tools through targeted educational campaigns and demonstrations that highlight their benefits to farmers, addressing regulatory and policy barriers will be crucial, along with promoting digital literacy programs to increase farmers understanding and perceived benefits of using agricultural related softwares.

VERIFICATION OF ENERGY CHARACTERISTICS OF A THREE-PHASE BRIDGE COMPENSATION CONVERTER WITH ONE COMMUTATING LINK

The article considers the issue of reliability of the results of analytical calculation of the feedforward control angle of power electric valves and the commutate angle of a three-phase bridge compensating converter of electric energy with one commutating link. It is noted that the value of these angles determines the capabilities of the converter regarding the generation of reactive energy together with the power supply of the consumer of direct current electric energy. Based on the complexity of the analytical calculation of these characteristics, the issue of verification of the obtained results is relevant, which also confirms the adequacy of the applied research methodology. As a tool for achieving the goal of the work, the authors use circuit simulation in the Micro Cap package. The modeling technique is described in detail, the results of modeling several modes of converter operation are presented, and these results are analyzed. A comparative analysis of the numerical values ​​of the control and commutating angles obtained as a result of analytical calculation and circuit modeling of the same modes of converter operation showed that the discrepancy does not exceed 5%. This indicates the adequacy of the applied modeling technique and the acceptable accuracy of the results of analytical calculations. Refer. 3, fig. 3, table 3.

Fundamental understanding of quantum confinement effect on gate oxide reliability for gate-all around field-effect transistor

Gate oxide reliability has become a significant concern for emerging technology nodes, particularly as transistors continue to scale down. Quantum confinement effects in nano-scaled devices complicate the trapping dynamics near the interface. Although these behaviors can be modeled using density-functional theory (DFT) and Marcus theory, a more efficient method is essential for characterizing critical reliability issues at the nano-device level. This paper presents a pioneering numerical study that employs a Bohm potential and Marcus theory, examining carrier concentration decay near the channel/oxide interface to evaluate the charge-trapping process using density-gradient coupled Poisson equations. This approach incorporates vital quantum corrections to classical studies. Key physics-based parameters are initially derived from DFT calculations and subsequently calibrated against experimental data. Our findings indicate that charge trap rates decrease with carrier density at the interface, ultimately affecting the device's threshold voltage shift.

IFAL-SLAM: an approach to inertial-centered multi-sensor fusion, factor graph optimization, and adaptive Lagrangian method

Abstract In response to the issues of low accuracy, perception degradation, and poor reliability of single-sensor SLAM technologies in complex environments, this study presents a novel IMU-centered multi-sensor fusion SLAM algorithm (IFAL-SLAM) integrating LiDAR, vision, and IMU, based on factor graph elimination optimization (\textbf{I}MU-centered multi-sensor \textbf{F}usion, \textbf{A}daptive \textbf{L}agrangian methods). The proposed system leverages a multi-factor graph model, centering on the IMU, and applies a covariance matrix to fuse visual-inertial and LiDAR-inertial odometries for bias correction, using loop closure factors for global adjustments. To minimize the optimization costs post-fusion, a sliding window mechanism is incorporated, coupled with a QR decomposition elimination method based on Householder transformation to convert the factor graph into a Bayesian network. Finally, an adaptive Lagrangian relaxation method is proposed, employing matrix-form penalty parameters and adaptive strategies to enhance convergence speed and robustness under high rotational dynamics.Experimental results indicate that the proposed algorithm achieves absolute trajectory errors of approximately 0.58 m and 0.24 m in large and small complex scenes, respectively, surpassing classic algorithms in terms of accuracy and reliability.

Toward Reuse‐Ready PV: A Perspective on Recent Advances, Practices, and Future Challenges

Photovoltaic (PV) industry is facing challenges in end‐of‐life (EoL) management, as cumulative PV waste is expected to increase exponentially over the next two decades. The increase in revamping and repowering activities, especially of older PV fleets, underscores the need to refine EoL strategies and increase the reuse readiness of PV modules and other components. As PV systems transition from operational to the EoL regime, streamlined PV qualification and repair strategies become indispensable. This is the only way to ensure reusable PV systems and a bankable second‐life PV market. This perspective study sheds light on current research, innovations, practices, and future challenges toward higher PV reuse readiness in the PV industry, highlighting qualification methods, repair strategies, and standardization for PV reuse. An exemplary triage‐for‐reuse framework is discussed, involving four steps: 1) off‐site eligibility checks; 2) on‐site inspections and functionality tests; 3) collection and transportation; 4) deeper technical checks. The study also reviews recent advances and research in repair strategies for reuse—addressing notably reliability issues of backsheet, glass and interconnection components—as well as ongoing standardization efforts. Conclusions underscore the the pressing need for circularity in the entire PV products’ lifecycle: from design/material level to system, operations and maintenance, and EoL.

The issue of admissibility and reliability of expert opinions as evidence in criminal proceedings

This article is devoted to the problem of assessing the admissibility and reliability of an expert’s opinion in the context of criminal proceedings. The expert’s opinion, as an important evidence in criminal cases, is an integral part of the judicial process. However, its admissibility and reliability play a crucial role in the formation of court decisions. The purpose of this study is to conduct a comprehensive assessment of the admissibility and reliability of the expert’s opinion in criminal proceedings. The article discusses the main aspects of assessing the admissibility of expert opinions, including the issues of expert qualification, his independence, methodology of work, as well as compliance with professional standards. The importance of strict procedure and supervision of experts to ensure the objectivity of conclusions is noted.

Classification of Mandarin-speaking persons with aphasia: a discussion on validating the classification function of WAB-R

ABSTRACT Background The classical aphasia taxonomy has been incorporated into several widely utilised aphasia assessment tools, such as the Western Aphasia Battery (WAB). Validation of the WAB’s classification typically involves comparing it with statistical clustering analysis results, using overall agreement rates as the referential index. Nevertheless, previous studies have documented diverse agreement rates. The classification function of the Mandarin version of the revised WAB (WAB-R) has not been validated. Additionally, the discussion on validating classification function is inadequate. Aim The current study adopts the argument-based validation framework to validate the classification function of the Mandarin version of the WAB-R and discuss the efficacy of using cluster analysis as evidence for the validation. Methods & Procedures A validation argument for the classification function was developed, utilising the k-means cluster analysis and within-group linkage cluster analysis as statistical procedures. WAB-R testing score data were collected from 122 Mandarin-speaking persons with acquired aphasia (non-acute). Eight clusters were expected to be generated from statistical procedures as a confirmatory test. To explore the impact of cluster numbers, solutions of generating six and ten clusters were conducted for comparative analysis. The potential reasons for mismatches were analysed. A proposed modified fluency scale (raising the cutoff score from 4 to 5) was also tested on the current dataset. Outcomes & Results Under the solution of eight clusters, the overall agreement was 62.3% with the k-means cluster analysis and 56.6% with the within-group linkage cluster analysis. Agreement rates slightly increased with the number of clusters in the within-group linkage method and remained almost unchanged in the k-means method. Anomic aphasia presented the highest agreements, while the agreements of other subtypes varied across different solutions. The fundamental differences between the clustering algorithm and the rationale of the WAB-R classification criteria were the primary reason for mismatched cases, undermining the reliability of the validation procedure. The modified fluency scale was found to significantly improve the overall agreement rates. Conclusions The classification function of the WAB-R’s Mandarin adaptation was considered acceptable under the current method. The validation argument is suggested to be modified to enhance the rationale as the statistical cluster analysis showed reliability issues when being solely employed for validation. The mismatch rate did not form direct challenges to the validity of the classification function. Additionally, modifications to the classification criteria are suggested for further exploration as the modified fluency scale has demonstrated positive results.