Search Results (40,683)

This study proposes a deep learning-based method to improve overlay alignment precision in laser direct writing systems. Alignment errors arise from multiple sources in nanoscale processes, including optical aberrations, mechanical drift, and fiducial mark imperfections. A significant portion of the residual alignment error stems from the interpretation of mark coordinates by the vision system and algorithms. Here, we developed a convolutional neural network (CNN) model to predict the coordinates calculation error of 66,000 sets of computer-generated defective crosshair marks (simulating real fiducial mark imperfections). We compared 14 neural network architectures (8 CNN variants and 6 feedforward neural network (FNN) configurations) and found a well-performing, simple CNN structure achieving a mean squared error (MSE) of 0.0011 on the training sets and 0.0016 on the validation sets, demonstrating 90% error reduction compared to the FNN structure. Experimental results on test datasets showed the CNN’s capability to maintain prediction errors below 100 nm in both X/Y coordinates, significantly outperforming traditional FNN approaches. The proposed method’s success stems from the CNN’s inherent advantages in local feature extraction and translation invariance, combined with a simplified network architecture that prevents overfitting while maintaining computational efficiency. This breakthrough establishes a new paradigm for precision enhancement in micro–nano optical device fabrication. Full article

Carbon nanotube field-effect transistors (CNTFETs) are becoming a strong competitor for the next generation of high-performance, energy-efficient integrated circuits due to their near-ballistic carrier transport characteristics and excellent suppression of short-channel effects. However, CNT FETs with large diameters and small band gaps exhibit obvious bipolarity, and gate-induced drain leakage (GIDL) contributes significantly to the off-state leakage current. Although the asymmetric gate strategy and feedback gate (FBG) structures proposed so far have shown the potential to suppress CNT FET leakage currents, the devices still lack scalability. Based on the analysis of the conduction mechanism of existing self-aligned gate structures, this study innovatively proposed a design strategy to extend the length of the source–drain epitaxial region (L_ext) under a vertically stacked architecture. While maintaining a high drive current, this structure effectively suppresses the quantum tunneling effect on the drain side, thereby reducing the off-state leakage current (I_off = 10⁻¹⁰ A), and has good scaling characteristics and leakage current suppression characteristics between gate lengths of 200 nm and 25 nm. For the sidewall gate architecture, this work also uses single-walled carbon nanotubes (SWCNTs) as the channel material and uses metal source and drain electrodes with good work function matching to achieve low-resistance ohmic contact. This solution has significant advantages in structural adjustability and contact quality and can significantly reduce the off-state current (I_off = 10⁻¹⁴ A). At the same time, it can solve the problem of off-state current suppression failure when the gate length of the vertical stacking structure is 10 nm (the total channel length is 30 nm) and has good scalability. Full article

In this study, we report the development of a novel magnetized coal fly ash-supported nano-silver composite (AgNPs/MCFA) for dual-functional applications in wastewater treatment: the efficient degradation of methyl orange (MO) dye and broad-spectrum antibacterial activity. The composite was synthesized via a facile impregnation–reduction–sintering route, utilizing sodium citrate as both a reducing and stabilizing agent. The AgNPs/MCFA composite was systematically characterized through multiple analytical techniques, including Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and vibrating sample magnetometry (VSM). The results confirmed the uniform dispersion of AgNPs (average size: 13.97 nm) on the MCFA matrix, where the formation of chemical bonds (Ag-O-Si) contributed to the enhanced stability of the material. Under optimized conditions (0.5 g·L⁻¹ AgNO₃, 250 °C sintering temperature, and 2 h sintering time), AgNPs/MCFA exhibited an exceptional catalytic performance, achieving 99.89% MO degradation within 15 min (pseudo-first-order rate constant k_a = 0.3133 min⁻¹) in the presence of NaBH₄. The composite also demonstrated potent antibacterial efficacy against Escherichia coli (MIC = 0.5 mg·mL⁻¹) and Staphylococcus aureus (MIC = 2 mg·mL⁻¹), attributed to membrane disruption, intracellular content leakage, and reactive oxygen species generation. Remarkably, AgNPs/MCFA retained >90% catalytic and antibacterial efficiency after five reuse cycles, enabled by its magnetic recoverability. By repurposing industrial waste (coal fly ash) as a low-cost carrier, this work provides a sustainable strategy to mitigate nanoparticle aggregation and environmental risks while enhancing multifunctional performance in water remediation. Full article

Artificial intelligence (AI) has become ubiquitous in modern computing systems, from high-performance data centers to resource-constrained edge devices. As AI applications continue to expand into mobile and IoT domains, the need for energy-efficient neural network implementations has become increasingly critical. To meet this requirement of energy-efficient computing, this work presents a BWNN (binary-weighted neural network) architecture implemented using FeRAM (Ferroelectric RAM)-based synaptic arrays. By leveraging the non-volatile nature and low-power computing of FeRAM-based CIM (computing in memory), the proposed CIM architecture indicates significant reductions in both dynamic and standby power consumption. Simulation results in this paper demonstrate that scaling the ferroelectric capacitor size can reduce dynamic power by up to 6.5%, while eliminating DRAM-like refresh cycles allows standby power to drop by over 258× under typical conditions. Furthermore, the combination of binary weight quantization and in-memory computing enables energy-efficient inference without significant loss in recognition accuracy, as validated using MNIST datasets. Compared to prior CIM architectures of SRAM-CIM, DRAM-CIM, and STT-MRAM-CIM, the proposed FeRAM-CIM exhibits superior energy efficiency, achieving 230–580 TOPS/W in a 45 nm process. These results highlight the potential of FeRAM-based BWNNs as a compelling solution for edge-AI and IoT applications where energy constraints are critical. Full article

In advanced Complementary Metal-Oxide-Semiconductor (CMOS) technologies, where diminished feature sizes amplify radiation-induced soft errors, the optimization of fault-tolerant circuit designs requires detailed transistor-level analysis of reliability–performance trade-offs. As a fundamental building block in digital systems and critical data paths, the 2:1 multiplexer, widely used in data-path routing, clock networks, and reconfigurable systems, provides a critical benchmark for assessing radiation-hardened design methodologies. In this context, this work aims to analyze the power consumption, area overhead, and delay of 2:1 multiplexer designs under transient fault conditions, employing the CMOS and Differential Cascode Voltage Switch Logic (DCVSL) logic styles and mitigation strategies. Electrical simulations were conducted using 32 nm high-performance predictive technology, evaluating both the original circuit versions and modified variants incorporating three mitigation strategies: transistor sizing, D-Cells, and C-Elements. Key metrics, including power consumption, delay, area, and radiation robustness, were analyzed. The C-Element and transistor sizing techniques ensure satisfactory robustness for all the circuits analyzed, with a significant impact on delay, power consumption, and area. Although the D-Cell technique alone provides significant improvements, it is not enough to achieve adequate levels of robustness. Full article

The article presents the first method based on high-performance liquid chromatography and ultraviolet detection (HPLC-UV) for the determination of timonacic (thioproline, 1,3-thiazolidine-4-carboxylic acid, tPro) in pharmaceutical tablets and face care products (creams, sera, foundations, suncreams). Sample preparation primarily involves solid-liquid extraction (SLE) of tPro with 0.2 mol/L phosphate buffer pH 6, derivatization with 0.25 mol/L 2-chloro-1-methylquinolinium tetrafluoroborate (CMQT), followed by polytetrafluoroethylene (PTFE) membrane filtration. The chromatographic separation of the stable UV-absorbing 2-S-quinolinium derivative is achieved within 14 min at 25 °C on a Zorbax SB-C18 (150 × 4.6 mm, 5 µm) column using gradient elution. The eluent consists of 0.1 mol/L trichloroacetic acid (TCA), pH 1.7, in a mixture with acetonitrile (ACN) delivered at a flow rate of 1 mL/min. The analyte is quantified by monitoring at 348 nm. The assay linearity was observed within 0.5–125 μmol/L. The limit of quantification (LOQ) was found to be 0.5 μmol/L. The accuracy ranged from 93.22% to 104.31% and 97.38% to 103.48%, while precision varied from 0.30% to 11.23% and 1.13% to 9.64% for intra- and inter-assay measurements, respectively. The method was successfully applied to commercially available on the Polish market pharmaceutical and cosmetic products. Full article

Based on the theory of optical sensing, we propose a high-precision plasmonic refractive index nanosensor, which consists of a symmetric rectangular waveguide and a circular ring containing a rectangular cavity. The designed novel tunable micro-resonant circular cavity filter based on surface plasmon excitations is able to confine light to sub-wavelength dimensions. The data show that different geometrical factors have different effects on sensing, with the geometry of the rectangular cavity and the radius of the circular ring being the key factors affecting the Fano resonance. Furthermore, the resonance bifurcation enables the structure to achieve a tunable dual Fano resonance system. The structure was tuned to obtain optimal sensitivity (S) and figure of merit values up to 3066 nm/RIU and 78. The designed structure has excellent sensing performance with sensitivities of 0.4767 nm·(mg/d${\mathrm{L}}^{-1}$) and 0.6 nm·(mg/d${\mathrm{L}}^{-1}$) in detecting Na⁺ and K⁺ concentrations in the electrolyte solution, respectively, and can be easily achieved by the spectrometer. The wavelength accuracy of 0.001 nm can be easily achieved by a spectrum analyzer, which has a broad application prospect in the field of optical integration. Full article

Background: Obesity is associated with insulin resistance (IR) and characterized by impaired activation of the PI3K/AKT route and glucose uptake. Elevated plasma levels of palmitic acid (PA) diminish insulin signaling in vitro and in vivo. Origanum vulgare L. essential oil (OVEO) is rich in monoterpenes with protective effects against IR. Objective: The study aimed to assess total phenols content and antioxidant activity of OVEO and its cytotoxicity, as well as its effect on insulin signaling and glucose uptake in PA-treated adipocytes. Methods: The quantification of total phenolic content was determined using the Folin–Ciocalteu method, while the antioxidant capacity of OVEO was assessed by DPPH (2,2-diphenyl-1-picrylhydrazyl) and FRAP (ferric reducing antioxidant power) methods. The cytotoxicity of OVEO (0.1–10 µg/mL) was assessed using the MTS assay. SW872 adipocytes were incubated with 0.4 mM PA for 24 h, with or without a 2 h preincubation of OVEO, and then stimulated with insulin (100 nM, 10 min) or a vehicle. Phosphorylation of Tyr-IRS-1, Ser-AKT, and Thr-AS160 was analyzed by Western blot, and glucose uptake was measured using 2-NBDG. Results: OVEO contained phenols and exhibits antioxidant capacity. All the concentrations of OVEO assessed were not cytotoxic on SW872 adipocytes. PA decreased basal phospho-AS160 as well as insulin-stimulated phospho-IRS1, phospho-AKT, phospho-AS160 and glucose uptake, while OVEO co-treatment enhanced these markers. Conclusions: These findings suggest a beneficial effect of OVEO on the PA-impaired insulin pathway and glucose uptake, which might be explained by its phenolic content and antioxidant capacity, highlighting its potential as a complementary therapeutic agent for IR and related metabolic disorders. Full article

Photoelectrochemical devices have garnered extensive research attention in the field of smart and multifunctional photoelectronics, owing to their lightweight nature, eco-friendliness, and cost-effective manufacturing processes. In this work, Bi₂S₃/Bi₂O₃/TiO₂ heterojunction film was successfully fabricated and functioned as the photoelectrode of photoelectrochemical devices. The designed Bi₂S₃/Bi₂O₃/TiO₂ photoelectrochemical photodetector possesses a broad light detection spectrum ranging from 400 to 900 nm and impressive self-powered characteristics. At 0 V bias, the device exhibits an on/off current ratio of approximately 1.3 × 10⁶. It achieves a commendable detectivity of 5.7 × 10¹³ Jones as subjected to a 0.8 V bias potential, outperforming both bare TiO₂ and Bi₂O₃/TiO₂ photoelectrochemical devices. Moreover, the Bi₂S₃/Bi₂O₃/TiO₂ photoelectrode film shows great promise in pollutant decomposition, achieving nearly 97.7% degradation efficiency within 60 min. The appropriate band energy alignment and the presence of an internal electric field at the interface of the Bi₂S₃/Bi₂O₃/TiO₂ film serve as a potent driving force for the separation and transport of photogenerated carriers. These findings suggest that the Bi₂S₃/Bi₂O₃/TiO₂ heterojunction film could be a viable candidate as a photoelectrode material for the development of high-performance photoelectrochemical optoelectronic devices. Full article

Selenium (Se) is an essential trace element involved in antioxidant redox regulation, thyroid hormone metabolism, and cancer prevention. Among its different forms, elemental selenium (Se⁰), particularly at the nanoscale, has gained growing attention in food, feed, and biomedical applications due to its lower toxicity and higher bioavailability compared to inorganic selenium species. However, the detection of Se⁰ in real samples remains challenging as current analytical methods are time-consuming, labour-intensive, and often unsuitable for rapid analysis. In this study, we developed a method for rapidly measuring Se⁰ using carbon nanodots (CNDs) produced from the Maillard reaction between glucose and glycine. The fabricated CNDs were water-dispersible and strongly fluorescent, with an average particle size of 3.90 ± 1.36 nm. Comprehensive characterisation by transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), fluorescence spectroscopy, and Raman spectroscopy confirmed their structural and optical properties. The CNDs were employed as fluorescent probes for the selective detection of Se⁰. The sensor showed a wide linear detection range (0–12.665 mmol L⁻¹), with a low detection limit (LOD) of 0.381 mmol L⁻¹ and a quantification limit (LOQ) of 0.465 mmol L⁻¹. Validation with spiked real samples—including ultra-pure water, tap water, and soft drinks—yielded high recoveries (98.6–108.1%) and low relative standard deviations (<3.4%). These results highlight the potential of CNDs as a simple, reliable, and environmentally friendly sensing platform for trace-level Se⁰ detection in complex food and beverage matrices. Full article

Background/Objectives: Heart rate variability (HRV) has been widely investigated as a predictor of disease and mortality across diverse patient populations; however, there remains no consensus on the optimal set or combination of time and frequency domain nor on nonlinear features for reliable prediction across clinical contexts. Given the relevance of the COVID-19 pandemic and the unique clinical profiles of these patients, this retrospective observational study explored the potential of HRV analysis for early prediction of in-hospital mortality using ECG signals recorded during the initial moments of ICU admission in COVID-19 patients. Methods: HRV indices were extracted from four ECG leads (I, II, III, and aVF) using sliding windows of 2, 5, and 7 min across observation intervals of 15, 30, and 60 min. The raw data posed significant challenges in terms of structure, synchronization, and signal quality; thus, from an original set of 381 records from 321 patients, after data pre-processing steps, a final dataset of 82 patients was selected for analysis. To manage data complexity and evaluate predictive performance, two feature selection methods, four feature reduction techniques, and five classification models were applied to identify the optimal approach. Results: Among the feature aggregation methods, compiling feature means across patient windows (Method D) yielded the best results, particularly for longer observation intervals (e.g., using LDA, the best AUC of $0.82\pm 0.13$ was obtained with Method D versus $0.63\pm 0.09$ with Method C using 5 min windows). Linear Discriminant Analysis (LDA) was the most consistent classification algorithm, demonstrating robust performance across various time windows and further improvement with dimensionality reduction. Although Gradient Boosting and Random Forest also achieved high AUCs and F1-scores, their performance outcomes varied across time intervals. Conclusions: These findings support the feasibility and clinical relevance of using short-term HRV as a noninvasive, data-driven tool for early risk stratification in critical care, potentially guiding timely therapeutic decisions in high-risk ICU patients and thereby reducing in-hospital mortality. Full article

The single-crystal diamond (SCD), owing to its extreme physical and chemical properties, serves as an ideal substrate for quantum sensing and high-frequency devices. However, crystal anisotropy imposes significant challenges on fabricating high-quality micro-nano structures, directly impacting device performance. This work investigates the effects of femtosecond laser processing on the SCD under two distinct crystallographic orientations via single-pulse ablation. The results reveal that ablation craters along the <100> orientation exhibit an elliptical shape with the major axis parallel to the laser polarization, whereas those along the <110> orientation form near-circular craters with the major axis at a 45° angle to the polarization. The single-pulse ablation threshold of the SCD along <110> is 9.56 J/cm², representing a 7.8% decrease compared to 10.32 J/cm² for <100>. The graphitization threshold shows a more pronounced reduction, dropping from 4.79 J/cm² to 3.31 J/cm² (31% decrease), accompanied by enhanced sp² carbon order evidenced by the significantly intensified G-band in the Raman spectra. In addition, a phase transition layer of amorphous carbon at the nanoscale in the surface layer (thickness of ~40 nm) and a narrow lattice spacing of 0.36 nm are observed under TEM, corresponding to the interlayer (002) plane of graphite. These observations are attributed to the orientation-dependent energy deposition efficiency. Based on these findings, an optimized crystallographic orientation selection strategy for femtosecond laser processing is proposed to improve the quality of functional micro-nano structures in the SCD. Full article

An anion exchange-assisted technique was used for the synthesis of platinum-decorated SnO₂ supports, providing nanocatalysts with enhanced activity for the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP). In this study, a series of SnO₂ supports, namely SnA (synthesized almost at room temperature), SnB (hydrothermally treated at 180 °C), and SnC (annealed at 600 °C), are systematically investigated, all loaded with 1 mol% Pt from H₂PtCl₆ under identical mild conditions. The chloride ions from the SnCl₄ precursors were efficiently removed via a strong-base anion exchange reaction, resulting in highly dispersed, crystalline ~5 nm cassiterite SnO₂ particles. All Pt/SnO₂ composites displayed mesoporous structures with type IVa isotherms and H₂-type hysteresis, with SP1a (Pt on SnA) exhibiting the largest surface area (122.6 m²/g) and the smallest pores (~3.5 nm). STEM-HAADF imaging revealed well-dispersed PtOx domains (~0.85 nm), while XPS confirmed the dominant Pt⁴⁺ and Pt²⁺ species, with ~25% Pt⁰ likely resulting from photoreduction and/or interactions with Sn–OH surface groups. Raman spectroscopy revealed three new bands (260–360 cm⁻¹) that were clearly visible in the sample with 10 mol% Pt and were due to the vibrational modes of the PtOx species and Pt-Cl bonds introduced due the addition and hydrolysis of H₂PtCl₆ precursor. TGA/DSC analysis revealed the highest mass loss for SP1a (~7.3%), confirming the strong hydration of the PtOx domains. Despite the predominance of oxidized PtOx species, SP1a exhibited the highest catalytic activity (k_app = 1.27 × 10⁻² s⁻¹) and retained 84.5% activity for the reduction of 4-NP to 4-AP after 10 cycles. This chloride-free low-temperature synthesis route offers a promising and generalizable strategy for the preparation of noble metal-based nanocatalysts on oxide supports with high catalytic activity and reusability. Full article

This study investigates the effects of copper nanoparticles (CuNPs) on KRT19 gene expression in four breast cancer cell lines (MDA-MB-231, MDA-MB-468, MCF7, and T47D), representing triple-negative and luminal subtypes. Using cytotoxicity assays, quantitative RT-PCR, and bioinformatics tools (STRING, g:Profiler), we demonstrate subtype-specific, dose-dependent KRT19 suppression, with epithelial-like cell lines showing greater sensitivity. CuNPs, characterized by dynamic light scattering (DLS) and transmission electron microscopy (TEM) with a mean size of 179 ± 15 nm, exhibited dose-dependent cytotoxicity. Bioinformatics analyses suggest KRT19′s potential as a biomarker for CuNP-based therapies, pending in vivo and clinical validation. These findings highlight CuNPs’ therapeutic potential and the need for further studies to optimize their application in personalized breast cancer treatment. Full article

The increasing prevalence of cancer necessitates the development of novel and effective therapeutic agents. This study evaluates the anticancer potential of biosynthesized copper oxide nanoparticles (CuO NPs) using Camellia sinensis extract against human colon and breast cancer cells. The CuO NPs were characterized using various techniques to confirm their structure, size, morphology, and functional groups. The average size of CuO NPs synthesized was 20–60 nm, with spherical shape. The cytotoxic effects of these CuO NPs reveal a dose-dependent reduction in cell viability with 50% inhibitory concentration (IC₅₀) at 58.53 ± 0.13 and 53.95 ± 1.1 μg/mL, respectively. Further investigation into the mechanism of action was conducted using flow cytometry and apoptosis assays, which indicated that CuO NPs induced cell cycle arrest and apoptosis in cancer cells. Reactive oxygen species (ROS) generation, caspase activity assay, and comet assay were also performed to elucidate the underlying pathways, suggesting that oxidative stress and DNA damage play pivotal roles in the cytotoxicity observed. Overall, our findings demonstrate that biosynthesized CuO NPs exhibit notable anticancer activity against colon and breast cancer cells, with moderate selectivity over normal cells, highlighting their potential as a therapeutic agent due to their biocompatibility. However, further studies are required to validate their selectivity and safety profile. Full article