Search Results (129)

Perovskite materials have garnered significant attention in both fundamental research and practical applications owing to their exceptional light absorption coefficients, low fabrication costs, and inherent advantages for thin-film and flexible device fabrication. Nevertheless, interface defects within perovskite films induce detrimental non-radiative carrier recombination and pronounced hysteresis effects, which collectively impose substantial limitations on the photovoltaic performance and long-term operational stability of perovskite solar cells (PSCs). Conventional passivation strategies, despite their demonstrated efficacy in mitigating interface defects, often inadvertently introduce secondary defects in originally defect-free regions, thereby restricting the extent of device performance improvement. To overcome this critical limitation, we have developed a precision defect passivation methodology that employs a targeted two-step immersion–cleaning process, achieving selective defect passivation while concomitantly eliminating residual passivating agents. This approach effectively prevents the formation of new defects in unaffected regions of the perovskite films, and the resultant PSC possesses a power conversion efficiency (PCE) of 21.08%, accompanied by a substantial mitigation of hysteresis behavior. Furthermore, unencapsulated devices demonstrate remarkable stability, retaining over 81% of their initial efficiency after 20 days of atmospheric storage under 50% relative humidity, which underscores the effectiveness of our passivation strategy in simultaneously enhancing both device performance and operational stability. Full article

Background: Physical activity is essential in the prevention and management of type 2 diabetes mellitus (T2D), yet adherence to recommended activity levels remains insufficient. Wearable electronic devices have emerged as tools to support physical activity through self-monitoring and enhanced user engagement. This review synthesizes current evidence on the effectiveness of wearable technologies in improving adherence to physical activity and promoting clinical and metabolic health in adults with T2D. Methods: The review was conducted using systematic search strategies in PubMed and Scopus. We included studies that involved the use of wearable devices to monitor physical activity for at least seven consecutive days. The reported outcomes were related to physical activity adherence or clinical–metabolic health. Thirty-two studies met the inclusion criteria and were analyzed in terms of study design, device type, intervention characteristics, and outcomes. Results: Wearable devices were used either for monitoring daily activity in free-living conditions or within structured, often supervised, interventions. Most studies reported increased physical activity, particularly in step count. Several studies showed improvements in blood pressure and lipid profile, while results for HbA1c and BMI were mixed. Structured interventions with behavioural support produced more consistent and clinically relevant outcomes than passive monitoring alone. Conclusions: Wearable technologies can support physical activity in adults with T2D, especially when integrated into structured behavioural programmes. From a clinical standpoint, they may serve as useful tools to enhance lifestyle adherence, particularly when combined with professional support. Their inclusion in care pathways could help personalize interventions and improve long-term self-management. Full article

This work investigates the effect of interface traps on the impedance spectra of dopant-free silicon solar cells. The studied device consists of a crystalline silicon absorber with an a-Si:H/MoOx/ITO stack as the front passivating hole-collecting contact and an a-Si:H/LiF/Al stack as the rear passivating electron-collecting contact. Experimental measurements, including illuminated current–voltage (I–V) characteristics and impedance spectroscopy, were performed on the fabricated devices and after a soft annealing treatment. The annealed cells exhibit an increased open-circuit voltage and a larger Nyquist plot radius. To interpret these results, a numerical model was developed in a TCAD environment. Simulations reveal that traps located at the p/i interface (MoOx/i-a-Si:H) significantly affect the impedance spectra, with higher trap concentrations leading to smaller Nyquist plot circumferences. The numerical impedance curves were aligned to the experimental data, enabling extraction of the interfacial traps concentration. The results highlight the sensitivity of impedance spectroscopy to interfacial quality and confirm that the performance improvement after soft annealing is primarily due to reduced defect density at the MoOx/i-a-Si:H interface. Full article

Inorganic halide perovskites have garnered significant attention as promising candidates for photovoltaic and optoelectronic applications, owing to their enhanced thermal and chemical stability relative to hybrid perovskite materials. This review synthesizes recent progress in vapor-phase deposition methodologies, such as co-evaporation, close space sublimation (CSS), continuous flash sublimation (CFS), and chemical vapor deposition (CVD), which enable the precise modulation of film composition and morphology. Advances in material systems, including the stabilization of CsPbI₂Br, the introduction of tin-doped phases, and the investigation of lead-free double perovskites like Cs₂AgSbI₆ and Cs₂AgBiCl₆, are critically evaluated with respect to their impact on device performance. The incorporation of these materials into photovoltaic devices and tandem configurations is explored, with particular emphasis on improvements in power conversion efficiency and operational durability. Furthermore, interface engineering approaches tailored to vacuum-deposited films—such as defect passivation and energy-level alignment—are examined in detail. The potential for scalable manufacturing is assessed through simulation analyses, throughput modeling, and pilot-scale demonstrations, underscoring the feasibility of industrial-scale production. By offering a comprehensive overview of these advancements, this review provides valuable perspectives on the current landscape and prospective trajectories of vapor-deposited inorganic perovskite technologies. Full article

Background/Objectives: The simulation of human movement offers transformative potential for the design of medical devices, particularly in understanding the cause–effect dynamics in individuals with neurological or musculoskeletal impairments. This study presents a simulation-driven framework to determine the optimal ankle–foot orthosis (AFO) stiffness for mitigating the risk of ankle sprains due to excessive subtalar inversion during high-impact activities, such as landing from a free fall. Methods: We employed biomechanical simulations to assess the influence of translational stiffness on subtalar inversion control, given that inversion angles exceeding 25 degrees are strongly correlated with injury risk. Simulations were conducted using a musculoskeletal model with and without a passive AFO; the stiffness varied in three anatomical directions. A Design of Experiments (DoE) approach was utilized to capture nonlinear interactions among stiffness parameters. Results: The results indicated that increased translational stiffness significantly reduced inversion angles to safer levels, though direction–dependent effects were noted. Based on these insights, we developed a 4D visualization tool that integrates simulation data with an interactive color–coded interface to depict ”safe design” zones for various AFO stiffness configurations. This tool supports clinicians in selecting stiffness values that optimize both safety and functional performance. Conclusions: The proposed framework enhances clinical decision-making and engineering processes by enabling more accurate and individualized AFO designs. Full article

Terahertz (THz) communications and simultaneous wireless information and power transfer (SWIPT) hold the potential to energize battery-less Internet-of-Things (IoT) devices while enabling multi-gigabit data transmission. However, severe path loss, blockages, and rectifier nonlinearity significantly hinder both throughput and harvested energy. Additionally, high-power THz beams pose safety concerns by potentially exceeding specific absorption rate (SAR) limits. We propose a sensing-adaptive power-focusing (APF) framework in which a reconfigurable intelligent surface (RIS) embeds low-rate THz sensors. Real-time backscatter measurements construct a spatial map used for the joint optimisation of (i) RIS phase configurations, (ii) multi-tone SWIPT waveforms, and (iii) nonlinear power-splitting ratios. A weighted MMSE inner loop maximizes the data rate, while an outer alternating optimisation applies semidefinite relaxation to enforce passive-element constraints and SAR compliance. Full-stack simulations at 0.3 THz with 20 GHz bandwidth and up to 256 RIS elements show that APF (i) improves the rate–energy Pareto frontier by 30–75% over recent adaptive baselines; (ii) achieves a 150% gain in harvested energy and a 440 Mbps peak per-user rate; (iii) reduces energy-efficiency variance by half while maintaining a Jain fairness index of 0.999;; and (iv) caps SAR at 1.6 W/kg, which is 20% below the IEEE C95.1 safety threshold. The algorithm converges in seven iterations and executes within <3 ms on a Cortex-A78 processor, ensuring compliance with real-time 6G control budgets. The proposed architecture supports sustainable THz-powered networks for smart factories, digital-twin logistics, wire-free extended reality (XR), and low-maintenance structural health monitors, combining high-capacity communication, safe wireless power transfer, and carbon-aware operation for future 6G cyber–physical systems. Full article

Despite the rapid efficiency advancement of perovskite solar cells (PSCs), non-radiative recombination at the buried interface between self-assembled monolayers (SAMs) and perovskite remains a critical bottleneck, primarily due to interfacial defects and energy level mismatch. In this study, we demonstrate a bifunctional interlayer engineering strategy by introducing 4,5-diiodoimidazole (4,5-Di-I) at the Me-4PACz/perovskite interface. This approach uniquely addresses two fundamental limitations of SAM-based interfaces: the insufficient defect passivation capability of conventional Me-4PACz due to steric hindrance effects and the poor perovskite wettability on hydrophobic SAM surfaces that exacerbates interfacial voids. The imidazole derivatives not only form strong Pb–N coordination bonds with undercoordinated Pb²⁺ but also modulate the surface energy of Me-4PACz, enabling the growth of pinhole-free perovskite films with preferential crystal orientation. The champion device with 4,5-Di-I modification achieves a power conversion efficiency (PCE) of 24.10%, with a V_OC enhancement from 1.12 V to 1.14 V, while maintaining 91% of initial PCE after 1300 h in N₂ atmosphere (25 °C), demonstrating superior stability under ISOS-L-2 protocols. This work establishes a universal strategy for interfacial multifunctionality design, proving that simultaneous defect suppression and crystallization control can break the long-standing trade-off between efficiency and stability in solution-processed photovoltaics. Full article

Continuous monitoring of glucose levels is important for diabetes management and prevention. While traditional glucose monitoring methods are often invasive and expensive, recent approaches using machine learning (ML) models have explored non-invasive alternatives—but many still depend on manually logged food intake and activity, which is burdensome and impractical for everyday use. In this study, we propose a novel approach that eliminates the need for manual input by utilizing only passively collected, automatically recorded multi-modal data from non-invasive wearable sensors. This enables practical and continuous glucose prediction in real-world, free-living environments. We used the BIG IDEAs Lab Glycemic Variability and Wearable Device Data (BIGIDEAs) dataset, which includes approximately 26,000 CGM readings, simultaneous ly collected wearable data, and demographic information. A total of 236 features encompassing physiological, behavioral, circadian, and demographic factors were constructed. Feature selection was conducted using random-forest-based importance analysis to select the most relevant features for model training. We evaluated the effectiveness of various ML regression techniques, including linear regression, ridge regression, random forest regression, and XGBoost regression, in terms of prediction and clinical accuracy. Biological sex, circadian rhythm, behavioral features, and tonic features of electrodermal activity (EDA) emerged as key predictors of glucose levels. Tree-based models outperformed linear models in both prediction and clinical accuracy. The XGBoost (XR) model performed best, achieving an R-squared of 0.73, an RMSE of 11.9 mg/dL, an NRMSE of 0.52 mg/dL, a MARD of 7.1%, and 99.4% of predictions falling within Zones A and B of the Clarke Error Grid. This study demonstrates the potential of combining feature engineering and tree-based ML regression techniques for continuous glucose monitoring using wearable sensors. Full article

Optimizing charge transport in organic semiconductors is crucial for advancing next-generation optoelectronic devices. The performance of organic field-effect transistors (OFETs) is significantly influenced by the alignment of films in the channel direction and the quality of the dielectric surface, which should be uniform, smooth, and free of charge-trapping defects. Our study reports the enhancement of OFET performance using large-area, uniform, and oriented thin films of regioregular poly[3-hexylthiophene] (RR-P3HT), prepared via the Floating Film Transfer Method (FTM) on octadecyltrichlorosilane (OTS) passivated SiO₂ surfaces. SiO₂ surfaces inherently possess dangling bonds that act as charge traps, but these can be effectively passivated through optimized surface treatments. OTS treatment has improved the optical anisotropy of thin films and the surface wettability of SiO₂. Notably, using octadecene as a solvent during OTS passivation, as opposed to toluene, resulted in a significant enhancement of charge carrier transport. Specifically, passivation with OTS-F (10 mM OTS in octadecene at 100 °C for 48 h) led to a >150 times increase in mobility and a reduction in threshold voltage compared to OTS-A (5 mM OTS in toluene for 12 h at room temperature). Under optimal conditions, these FTM-processed RR-P3HT films achieved the best device performance, with a saturated mobility (μ_sat) of 0.18 cm²V⁻¹s⁻¹. Full article

Optical neural networks are hardware neural networks implemented based on physical optics, and they have demonstrated advantages of high speed, low energy consumption, and resistance to electromagnetic interference in the field of image processing. However, most previous optical neural networks were designed for coherent light inputs, which required the introduction of an electro-optical conversion module before the optical computing device. This significantly hindered the inherent speed and energy efficiency advantages of optical computing. In this paper, we propose a diffraction algorithm for incoherent light based on mutual intensity propagation, and on this basis, we established a model of an incoherent optical neural network. This model is completely passive and directly performs inference calculations on natural light, with the detector directly outputting the results, achieving target classification in an all-optical environment. The proposed model was tested on the MNIST, Fashion-MNIST, and ISDD datasets, achieving classification accuracies of 82.32%, 72.48%, and 93.05%, respectively, with experimental verification showing an accuracy error of less than 5%. This neural network can achieve passive and delay-free inference in a natural light environment, completing target classification and showing good application prospects in the field of remote sensing. Full article

The improvement of microelectronic technologies and the practical application of some new materials has resulted in the realization of various highly efficient thin-film energy harvesters in the last few years. Self-powered supplies intended to work with thin-film harvesters have been developed. This type of power supply with integrated various thin-film harvesters has proven to be very suitable for providing electrical energy for wearable electronic sensor systems, with practical applications for implementing personalized medicine through continuously monitoring an individual’s state of health. The application of wearable electronics in medicine will become increasingly important in the next few years, as it can support timely decision-making, especially in high-risk patients. This paper presents a review and comparative analysis of the optimal circuit configurations used to design power supply devices with discrete and integrated components, obtaining electrical power from various thin-film piezoelectric generators, and storing electrical energy in low-power multilayer supercapacitors. Based on an analysis of the principle of operation of the selected circuit configurations, analytical expressions for the basic static and dynamic parameters have been obtained, taking into account the peculiarities of their integration with the biomedical signal processing system. Advantages and weaknesses are analyzed through simulation testing for each configuration, as the prospects for improvement are outlined. Also, for each group of circuit configurations, the key parameters and characteristics of recent high-impact papers, especially those focusing on low-power applications, are presented and analyzed in tabular form. As a result of the analysis of the various circuit configurations, some analytical recommendations have been defined regarding the optimal selection of passive and active elements, which can contribute to a better understanding of the design principles of battery-free power supplies converting electrical energy from some specific recently developed thin-film energy harvesters. Full article

High-stability photovoltaic devices are crucial for low-power or passive applications in fields such as renewable energy, wearable electronics, and deep-space exploration. However, achieving stable and controllable doping in two-dimensional (2D) materials remains challenging, hindering the optimization of photovoltaic performance. Here, we fabricate three high-performance, self-driven photodetectors based on layered WSe₂ with varying doping concentrations. By leveraging asymmetric Schottky barriers and introducing a defect-free, high-bandgap intrinsic region with a long mean free path, we construct a positive–intrinsic–negative (PIN) vertical homojunction that significantly enhances the photogenerated voltage, photon absorption, and carrier transport efficiency. The resulting PIN junction exhibits a photogenerated voltage of up to 0.58 V, a responsivity of 0.35 A/W, and an external quantum efficiency of 83.9%. Moreover, it maintains a reverse saturation current as low as 0.2 nA at 430 K. These results provide a promising route toward the development of high-responsivity, high-stability van der Waals devices and highlight the potential for 2D material-based technologies to operate reliably under extreme conditions. Full article

Internet of Things (IoT) technology has continuously advanced over the past decade. As a result, device-free indoor localization functions have become a crucial part of application areas such as healthcare, safety, and energy management. Passive infrared (PIR) sensors detecting changes in temperature in an environment are one of the suitable options for human localization due to their lower cost, low energy consumption, electromagnetic tolerance, and enhanced private awareness. Although existing localization methods, including machine/deep learning, have been proposed to detect multiple persons based on signal phase and amplitude, they still face challenges regarding signal quality, ambiguity, and interference caused by the complex, interleaving movements of multiple persons. This paper proposes a novel deep learning method for multi-person localization using channel separation and template-matching techniques. The approach is based on a deep CNN-LSTM architecture with ensemble models using a mean bagging technique for achieving higher localization accuracy. Our results show that the proposed method can estimate the locations of two participants simultaneously with a mean distance error of 0.55 m, and 80% of the distance errors are within 0.8 m. Full article

The flywheel energy storage system (FESS) of a mechanical bearing is utilized in electric vehicles, railways, power grid frequency modulation, due to its high instantaneous power and fast response. However, the lifetime of FESS is limited because of significant frictional losses in mechanical bearings and challenges associated with passing the critical speed. To suppress the unbalanced response of FESS at critical speed, a damping ring (DR) device is designed for a hybrid supported FESS with mechanical bearing and axial active magnetic bearing (AMB). Initially, the dynamic model of the FESS with DR is established using Lagrange’s equation. Moreover, the dynamic parameters of the DR are obtained by experimental measurements using the method of free vibration attenuation. Finally, the influence of the DR device on the critical speed and unbalanced response of FESS is analyzed. The results show that the designed DR device can effectively reduce the critical speed of FESS, and increase the first and second mode damping ratio. The critical speed is reduced from 13,860 rpm to 5280 rpm. Compared with FESS of the mechanical bearing, the unbalanced response amplitude of the FESS with DR is reduced by more than 87.8%, offering promising technical support for the design of active and passive control systems in FESS. Full article

In this work, we present the novel application of SiN_x stress-engineering techniques for the suppression of short-channel effects in AlGaN/GaN high-electron-mobility transistors (HEMTs), accompanied by a comprehensive analysis of the underlying mechanisms. The compressive stress SiN_x passivation significantly enhances the barrier height at the heterojunction beneath the gate, maintaining it above the quasi-Fermi level even as V_ds rises to 20 V. As a result, in GaN devices with a gate length of 160 nm, the devices with compressive stress SiN_x passivation exhibit significantly lower drain-induced barrier lowering (DIBL) factors of 2.25 mV/V, 2.56 mV/V, 4.71 mV/V, and 3.84 mV/V corresponding to drain bias voltages of 5 V, 10 V, 15 V, and 20 V, respectively. Furthermore, as V_ds increases, there is an insignificant degradation in transconductance, subthreshold swing, leakage current, or output conductance. In contrast, the devices with stress-free passivation show relatively higher DIBL factors (greater than 20 mV/V) and substantial degradation in pinch-off performance and output characteristics. These results demonstrate that the SiN_x stress-engineering technique is an attractive technique to facilitate high-performance and high-reliability GaN-based HEMTs for radio frequency (RF) electronics applications. Full article