Search Results (97)

We developed dye-sensitized solar cells based on anatase–titanium dioxide (A-TiO₂) nanotubes (TiNTs) and nanocubes (TiNcs) with {001} crystal facets generated using simple and facile electrochemical anodization. We also demonstrated a simple way of developing one-dimensional, two-dimensional, and three-dimensional self-assembled TiO₂ nanostructures via electrochemical anodization, using them as an electron-transporting layer in DSSCs. TiNTs maintain tubular arrays for a limited time before becoming nanocrystals with {001} facets. Using FESEM and TEM, we observed that the TiO₂ nanobundles were transformed into nanocubes with {001} facets and lower fluorine concentrations. Optimizing the reaction approach resulted in better-ordered, crystalline anatase TiNTs/Ncs being formed on the Ti metal foil. The anatase phase of as-grown TiO₂ was confirmed by XRD, with (101) being the predominant intensity and preferred orientation. The nanostructured TiO₂ had lattice values of a = 3.77–3.82 and c = 9.42–9.58. The structure and morphology of these as-grown materials were studied to understand the growth process. The photoconversion efficiency and impedance spectra were explored to analyze the performance of the designed DSSCs, employing N719 dye as a sensitizer and the I⁻/I³⁻ redox pair as electrolytes, sandwiched with a Pt counter-electrode. As a result, we found that self-assembled TiNTs/Ncs presented a more effective photoanode in DSSCs than standard TiO₂ (P25). TiNcs (0.5 and 0.25 NH₄F) and P25 achieved the highest power conversion efficiencies of 3.47, 3.41, and 3.25%, respectively. TiNcs photoanodes have lower charge recombination capability and longer electron lifetimes, leading to higher voltage, photocurrent, and photovoltaic performance. These findings show that electrochemical anodization is an effective method for preparing TiNTs/Ncs and developing low-cost, highly efficient DSSCs by fine-tuning photoanode structures and components. Full article

Dehydration is a serious medical problem for elderly patients and young children. The most widely used diagnostics are measurements of sodium ion (Na⁺) and potassium ion (K⁺) in blood serum. Dehydration is difficult to diagnose even by trained health care professionals because the body compensates to maintain the appearance of skin. These measurements required a blood draw because specific tests are generally not available for only Na⁺ and K⁺. The blood samples are analyzed by an electrolyte panel (EP) or a basic metabolic panel (BMP). Most hospitals limit EP and BMP to one per day to control costs. More frequent measurements of Na⁺ and K⁺ are needed, especially during rehydration. We designed a dehydration contact lens that can provide the Na⁺ and K⁺ concentrations as needed or for continuous monitoring. The measurements are obtained from the fluorescent lifetime or wavelength-ratiometric intensities of the Na⁺- and K⁺-sensitive fluorophores. The dehydration contact lens does not contain electronic components and are inexpensive to prepare. Full article

Life testing of products often requires extended observation periods. To shorten the duration of these tests, products can be subjected to more extreme conditions than those encountered in normal use; an approach known as accelerated life testing (ALT) is considered. This study investigates the estimation of unknown parameters and the acceleration factor for the modified Fréchet-Lomax exponential distribution (MFLED), utilizing Type II progressively first-failure censored (PFFC) samples obtained under the framework of constant-stress partially accelerated life testing (CSPALT). Maximum likelihood (ML) estimation is employed to obtain point estimates for the model parameters and the acceleration factor, while the Fisher information matrix is used to construct asymptotic confidence intervals (ACIs) for these estimates. To improve the precision of inference, two parametric bootstrap methods are also implemented. In the Bayesian context, a method for eliciting prior hyperparameters is proposed, and Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) method. These estimates are evaluated under both symmetric and asymmetric loss functions, and the corresponding credible intervals (CRIs) are computed. A comprehensive simulation study is conducted to compare the performance of ML, bootstrap, and Bayesian estimators in terms of mean squared error and coverage probabilities of confidence intervals. Finally, real-world failure time data of light-emitting diodes (LEDs) are analyzed to demonstrate the applicability and efficiency of the proposed methods in practical reliability studies, highlighting their value in modeling the lifetime behavior of electronic components. Full article

This paper presents the design, implementation, and experimental validation of a Condition Monitoring (CM) circuit for SiC-based Power Electronics Converters (PECs). The paper leverages in situ drain–source resistance (R_ds,on) measurements, interfaced with cloud connectivity for data processing and lifetime assessment, addressing key limitations in current state-of-the-art (SOTA) methods. Traditional approaches rely on expensive data acquisition systems under controlled laboratory conditions, making them unsuitable for real-world applications due to component variability, time delay, and noise sensitivity. Furthermore, these methods lack cloud interfacing for real-time data analysis and fail to provide comprehensive reliability metrics such as Remaining Useful Life (RUL). Additionally, the proposed CM method benefits from noise mitigation during switching transitions by utilizing delay circuits to ensure stable and accurate data capture. Moreover, collected data are transmitted to the cloud for long-term health assessment and damage evaluation. In this paper, experimental validation follows a structured design involving signal acquisition, filtering, cloud transmission, and temperature and thermal degradation tracking. Experimental testing has been conducted at different temperatures and operating conditions, considering coolant temperature variations (40 °C to 80 °C), and an output power of 7 kW. Results have demonstrated a clear correlation between temperature rise and R_ds,on variations, validating the ability of the proposed method to predict device degradation. Finally, by leveraging cloud computing, this work provides a practical solution for real-world Wide Band Gap (WBG)-based PEC reliability and lifetime assessment. Full article

This study systematically investigates the effects of trap concentration on self-heating and terahertz (THz) responses in GaN HEMTs using Sentaurus TCAD. Traps, inherently unavoidable in semiconductors, can be strategically introduced to engineer specific energy levels that establish competitive dynamics between the electron momentum relaxation time and the carrier lifetime. A simulation-based exploration of this mechanism provides significant scientific value for enhancing device performance through self-heating mitigation and THz response optimization. An AlGaN/GaN heterojunction HEMT model was established, with trap concentrations ranging from 0 to $5\times {10}^{17} {\mathrm{c}\mathrm{m}}^{-3}$. The analysis reveals that traps significantly enhance channel current (achieving 3× gain at $1\times 10^{17} {\mathrm{c}\mathrm{m}}^{-3}$) via new energy levels that prolong carrier lifetime. However, elevated trap concentrations (>$1\times {10}^{16} {\mathrm{c}\mathrm{m}}^{-3}$) exacerbate self-heating-induced current collapse, reducing the min-to-max current ratio to 0.9158. In THz response characterization, devices exhibit a distinct DC component (${\mathrm{U}}_{\mathrm{d}\mathrm{c}}$) under non-resonant detection ($\mathsf{\omega }\mathsf{\tau }\ll 1$). At a trap concentration of $1\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$, ${\mathrm{U}}_{\mathrm{d}\mathrm{c}}$ peaks at $0.12 \mathrm{V}$ when ${\mathrm{V}}_{\mathrm{g}}\mathrm{D}\mathrm{C}=-7.8 \mathrm{V}$. Compared to trap-free devices, a maximum response attenuation of 64.89% occurs at ${\mathrm{V}}_{\mathrm{g}}\mathrm{D}\mathrm{C}=-4.9 \mathrm{V}$. Furthermore, ${\mathrm{U}}_{\mathrm{d}\mathrm{c}}$ demonstrates non-monotonic behavior with concentration, showing local maxima at $4\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$ and $7\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$, attributed to plasma wave damping and temperature-gradient-induced electric field variations. This research establishes trap engineering guidelines for GaN HEMTs: a concentration of $4\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$ optimally enhances conductivity while minimizing adverse impacts on both self-heating and the THz response, making it particularly suitable for high-sensitivity terahertz detectors. Full article

Toxoplasma gondii is an Apicomplexan parasite that possesses a well-developed system of scavengers of reactive oxygen species (ROS). Among its components, T. gondii mitochondrial superoxide dismutase (TgSOD2) is essential, as predicted by the CRISPR phenotype index and evidenced by the non-viability of its constitutive knockouts. As an obligate intracellular parasite, TgSOD2 is upregulated during extracellular stages. Herein, we generated a viable TgSOD2 knockdown mutant using an inducible auxin–degron system to explore the biological role of TgSOD2 in T. gondii. Depletion of TgSOD2 led to impaired parasite growth and replication, reduced mitochondrial membrane potential (MMP), abnormalities in the distribution of ATP synthase within its mitochondrial electron transport chain (mETC), and increased susceptibility to mETC inhibitors. Through a proximal biotinylation approach, we identified the interactions of TgSOD2 with complexes IV and V of its mETC, suggesting that these sites are sensitive to ROS. Our study provides the first insights into the role of TgSOD2 in maintaining its mitochondrial redox homeostasis and subsequent parasite replication fitness. Significance: Toxoplasma gondii infects nearly a third of the world population and can cause fetal miscarriages or life-threatening complications in vulnerable patients. Current therapies do not eradicate the parasite from the human hosts, rendering them at risk of recurrence during their lifetimes. T. gondii has a single mitochondrion, which is well-known for its susceptibility to oxidative damage that leads to T. gondii’s death. Therefore, targeting T. gondii mitochondrion remains an attractive therapeutic strategy for drug development. T. gondii’s mitochondrial superoxide dismutase is an antioxidant protein in the parasite mitochondrion and is essential for its survival. Understanding its biological role could reveal mitochondrial vulnerabilities in T. gondii and provide new leads for the development of effective treatments for T. gondii infections. Full article

The battery pack is a critical component of electric vehicles, with lithium-ion cells being a frequently preferred choice. Lithium-ion cells are known for long life, high power and energy density, and are reliable for a broad range of temperatures. However, these batteries have a drawback of over-voltage, under-voltage, thermal runaway, and especially, state of charge or voltage imbalance. Among these, the cell imbalance is particularly important because it causes an uneven power dissipation in each cell, resulting in non-uniform temperature distribution. This uneven temperature distribution negatively affects the lifetime and efficiency of a battery pack. Cell imbalance is mitigated by cell balancing techniques, of which several methods have been presented over the last few years. These methods consider different power electronics circuits and control approaches to optimise cell balancing characteristics. This paper reviews basic to advanced cell balancing techniques and compares their circuit designs, costs, switching stresses, complexity, sizes, and control techniques to highlight the recent trends and future directions. This paper also compares the recent trend of machine learning integration with basic cell balancing topologies and provides a critical analysis of the outcomes. Full article

Generating chaos from originally non-chaotic systems is a promising issue. Indeed, chaos has been successfully applied in many fields to improve system performance. In this work, a Buck converter is chaotified using a combination of the switching piecewise-constant characteristic and of anticontrol of chaos feedback. For electromagnetic compatibility compliance reasons, this feedback control method is able, at the same time, to achieve low spectral emissions and to maintain a small ripple of the output voltage and the inductance current. This new feedback implies a fast and non-linear switching action of the Buck MOSFET on a period of the ramp generator. Thus, it is essential to analyze its thermal performance. This is why we propose an original analysis of the influence of anticontrol of chaos and switching frequency variation on junction temperature: we investigate the correlation between the lifetime of the power electronic switching component and its thermal stress due to the addition of chaos. It appeared that a reduction in the current ripple did not degrade the MOSFET junction thermal performance, despite the fast switching of the MOSFET. Furthermore, a small degradation in the MOSFET lifetime was indicated for chaotic behavior versus periodic behavior. Thus, this leads to the conclusion that using anticontrol of chaos produces a low accumulated fatigue effect on a Buck converter semiconductor. Full article

This study explores the effect of vibrations generated by wind turbines on the lifespan of the IGBT module. Since wind turbines operate under varying dynamic loads, they produce vibrations that might influence the performance and longevity of electronic components like IGBTs. To investigate this concern, a modal analysis was carried out using the finite element analysis (FEA) in ANSYS to identify the natural frequencies of the module. These frequencies were then compared with typical load frequencies encountered in wind turbine operations. Furthermore, random vibration analysis, incorporating power spectral density (PSD), was conducted to assess the module’s deformation under stochastic vibration conditions. The simulation results demonstrated that the IGBT module located inside the wind turbine nacelle has an exceptionally long operational lifetime under random vibration conditions. This indicates that the impact of vibrations on the module’s durability is minimal. As a result, this study concludes that vibrations induced by wind turbine operations pose no significant threat to the lifespan of the IGBT module, reinforcing its reliability in power electronic systems, even in vibration-prone environments. Full article

Research on lithium-ion batteries has been driven by the growing demand for electric vehicles to mitigate greenhouse gas emissions. Despite advances, batteries still face significant challenges in efficiency, lifetime, safety, and material optimization. In this context, the objective of this research is to develop a predictive model based on Deep deep-Learning learning techniques. Based on Deep Learning techniques that combine Transformer and Physicsphysics-Informed informed approaches for the optimization and design of electrochemical parameters that improve the performance of lithium batteries. Also, we present a training database consisting of three key components: numerical simulation using the Doyle–Fuller–Newman (DFN) mathematical model, experimentation with a lithium half-cell configured with a zinc oxide anode, and a set of commercial battery discharge curves using electronic monitoring. The results show that the developed Transformer–Physics physics-Informed informed model can effectively integrate deep deep-learning DNF to make predictions of the electrochemical behavior of lithium-ion batteries. The model can estimate the battery battery-charge capacity with an average error of 2.5% concerning the experimental data. In addition, it was observed that the Transformer could explore new electrochemical parameters that allow the evaluation of the behavior of batteries without requiring invasive analysis of their internal structure. This suggests that the Transformer model can assess and optimize lithium-ion battery performance in various applications, which could significantly impact the battery industry and its use in Electric Vehicles vehicles (EVs). Full article

The performance of ultrafast scintillators under ultrahigh dose rate is highly important for applications utilizing brilliant radiation sources. In this work, the scintillation properties of β-Ga₂O₃, a high-performance ultrafast wide-bandgap semiconductor scintillator, are systematically investigated under dose rates of 10⁷ to 10⁹ Gy/s for the first time by employing ultrashort high-charge electron bunches (bunch charge from 500 fC to 50 pC) generated from a superconducting radio-frequency accelerator. Our results show that in spite of the ultrahigh dose rate, the scintillation intensity was still linearly proportional to the electron bunch charge. Lifetime analysis reveals a fast decay component ranging from 3 to 4 ns, along with an average lifetime of 20 ns. These findings establish a solid foundation for the application of β-Ga₂O₃ as the scintillation material for high-charge electron sources such as laser-wakefield accelerated electrons. Full article

The long-term usage of polymer products necessitates addressing the appropriate preservation of their low oxidation state that extends the warranty period. The addition of pertinent stabilization components into the composite formulations (synthesis and natural antioxidants, pristine and doped oxides, clays or couples of them) produces an improvement in the kinetic parameters characterizing the accelerated degradation that occurs during high-energy exposures. The competition between the material ageing and the mitigation of oxidation is controlled by the protection efficiency. In this paper, the main advantages of inorganic structures in comparison to classical organic antioxidants are emphasized. A significant improvement in stability, simultaneously associated with the enhancing of functional characteristics, the lack of migration, low cost and easy accessibility, make the reevaluation of certain fillers as stabilizers appropriate. The correlation between the functional properties and the filler nature in polymer materials may be reconsidered for the assessment of the participation capability of inorganic structures in the inhibition of oxidation by the inactivation of free radicals. The lifetimes of degradation intermediates extended by the activities of inorganic compounds are increased by means of electrical interactions involving the unpaired electrons of molecular fragments. These physical contributions are reflected in chemical stability. An essential feature for the presented inorganic options is a strong impact on the recycling technologies of polymers by radiation processing. Plastic products, including all categories of macromolecular materials, can gain an increased durability through the inorganic alternative of protection. Full article

Temperature has a significant impact on the operational lifetime of electronic components, as excessive heat can lead to accelerated degradation and ultimately failure. In safety-critical applications, it is important that real-time monitoring is employed to reduce the risk of system failures and maintain the safety, reliability, and integrity of the connected systems. In the case of printed circuit boards (PCBs), it is often not feasible to install enough sensors to adequately cover all of the temperature sensitive components. In this study, we present a novel method for the temperature monitoring of PCBs using ultrasonic guided waves and machine learning techniques. Our approach utilizes a small number of low-cost, unobtrusive piezoelectric wafer active sensors (PWAS) sensors for propagating ultrasonic guided waves across a PCB. Through interaction with board features, the temperature of components can be predicted using multi-output regression algorithms. Our technique has been applied to three different PCBs, each with five hotspot positions, achieving an RMSE of <3.5 °C and $R^2$ > 0.95 in all three cases. Full article

This study investigates the effects of negative bias temperature (NBT) stress and irradiation on the threshold voltage (V_T) of p-channel VDMOS transistors, focusing on degradation, recovery after each type of stress, and operational behavior under varying conditions. Shifts in V_T (ΔV_T) were analyzed under different stress orders, showing distinct influence mechanisms, including defects creation and their removal and electrochemical reactions. Recovery data after each type of stress indicated ongoing electrochemical processes, influencing subsequent stress responses. Although the ΔV_T is not particularly pronounced during the recovery after irradiation, changes in subthreshold characteristics indicate the changes in defect densities that affect the behavior of the components during further application. Additionally, the findings show that the ΔV_T during the NBT stress after irradiation (up to certain doses and conditions) remains relatively stable, but this is the result of a balance of competing mechanisms. A subthreshold characteristic analysis provided a further insight into the degradation dynamics. A particular attention was paid to analyzing ΔV_T with a focus on predicting the lifetime. In practical applications, especially under pulsed operation, prior stresses altered the device’s thermal and electrical performance. It was shown that self-heating effects were more pronounced in pre-stressed components, increasing the power dissipation and thermal instability. These insights additionally highlight the importance of understanding stress-induced degradation and recovery mechanisms for optimizing VDMOS transistor reliability in advanced electronic systems. Full article

LED lamp beads (hereinafter referred to as LEDs) are complex electronic components, and their degradation process shows multi-stage characteristics. Ignoring the effects of multi-stage degradation and stress coupling will lead to a higher theoretical lifespan. In this paper, a Wiener process model based on generalized coupling is proposed for the staged degradation of LEDs. This paper first conducts accelerated degradation tests on LEDs under different temperature, humidity, and current stress combinations to obtain three index parameters of LEDs. Light output performance (LOP) is selected as the degradation characteristic quantity, and the Shapiro–Wilk test is used to determine whether the parameters conform to the normal distribution. Then, the unknown parameters of the multi-stage Wiener process are estimated and a generalized coupling model is established using the unknown parameters and accelerated degradation test data. Finally, the LED life under standard stress is extrapolated based on the multiple stress acceleration factors. The analysis of LED reliability experimental data shows that the proposed method can realize reliability assessment and has higher lifetime prediction accuracy compared with the multi-stage model without considering stress coupling. Full article