Search Results (589)

A plasma-assisted ammonia jet flame igniter was developed in this study to address the limitations of conventional spark ignition at high pressures. The effect of pressure on plasma discharge characteristics, optical emission spectra, and exhaust gas emission was systematically investigated, providing new insights into the mechanisms of plasma-assisted ammonia ignition under high-pressure conditions. The results indicate that increased chamber pressure elevates gas density, which in turn raises the voltage required to sustain an arc discharge at 0.4 MPa and markedly reduces the frequency of arc drift. Spectral analysis shows that higher pressure inhibits atomic oxygen lines (777.2 nm and 844.6 nm) while intensifying the molecular nitrogen bands between 350–450 nm. A corresponding decrease in electron excitation temperature is also observed. In terms of exhaust composition, hydrogen concentration demonstrates a bifurcated behavior, rising with pressure under fuel-rich conditions (the equivalence ratio φ > 1.2) and falling under fuel-lean conditions (φ ≤ 1). Conversely, NO concentration consistently decreases with increasing pressure across all test conditions. The ammonia concentration in the exhaust gas shows opposite pressure dependencies at different equivalence ratios. It increases with rising pressure for φ ≥ 1, while it decreases with increasing pressure for φ < 1. Full article

We present, for the first time, a design and measured data for a meanderline reflective quarter-wave plate suitable for operation in the 3- to 5-micron MWIR band. Across this spectral range, the reflection coefficient is around 80%, the axial ratio is less than 2, and the polarization conversion ratio is above 75%. We also demonstrate experimentally that the meanderline structure has stable performance as a reflective quarter-wave plate over a 20-degree angular bandwidth centered around incident angles between 35 and 55 degrees. One notable difference as compared to LWIR meanderline waveplates is that the vertical height of the grid lines is necessarily larger, to keep the relative phase between TE and TM near 90°. Full article

Vegetation indices (VIs) enable rapid, non-destructive biochemical monitoring in olive fruits, yet their performance across diverse germplasm and ripening stages remains systematically uncharacterized. This exploratory screening systematically evaluated 87 VIs for predicting chlorophyll and polyphenol content across 31 cultivars at four ripening stages, prioritizing genetic diversity to establish species-level biochemical–spectral relationships through integration of hyperspectral data (380–1080 nm) with biochemical analyses. Modified Chlorophyll Absorption Ratio Index 3 (MCARI 3) and Transformed Chlorophyll Absorption Ratio Index (TCARI) achieved 91 strong correlations (|r| ≥ 0.9) across 124 cultivar-stage combinations. High-performing indices incorporated 550 nm with red/red-edge bands (670–710 nm) and non-linear formulations. Moderate inter-cultivar variability indicated that cultivar-specific calibrations may be necessary. Principal component analysis captured the totality of variance, revealing three biochemical clusters, high-chlorophyll cultivars (n = 5; 91.8 and 7385.6 mg kg⁻¹ chlorophyll/polyphenols, respectively), typical-range cultivars (n = 22; 126.6 and 4016.8 mg kg⁻¹), and elite cultivars (n = 5; 790.4 and 5799.8 mg kg⁻¹), demonstrating VIs’ capacity for cultivar discrimination. Chlorophyll degradation exhibited conserved patterns, supporting universal tracking models. Conversely, polyphenol dynamics displayed marked genotype-dependency, with cultivars showing positive, negative, or minimal variation, yielding non-significant population-level effects, despite robust cultivar-specific trends. Full article

Running shoe midsoles are designed to attenuate impact forces while maintaining or improving performance. However, the literature is equivocal, likely due to measurement systems, whereas in vitro testing is conclusively favourable. This study investigated three densities of ATPU foam, comparing in vitro mechanical properties with in vivo plantar force spectral characteristics derived from individualised pressure distributions during treadmill running at varied speeds. In vitro results of slab foam and shoes showed strong positive relationships between impact variables normalised to total impact energy and foam density (r² > 0.90), and strong negative relationships for time-domain variables normalised to deformation (mm) as density increased (r² > 0.89). During running, lower midsole density increased ground contact time across speeds (p = 0.041), while spatially resolved high-frequency PSD and peak impact force both decreased (p = 0.043; p = 0.030). However, there were no differences between total vertical force and midsole density (p = 0.232). Relationships between in vitro Peak G and high-frequency PSD were strong across all speeds (r² = 0.63–0.91). Conversely, reducing midsole density increased active peak force across speeds (p = 0.003), which was strongly related to in vitro energy return (r² > 0.89). Therefore, plantar force spectra and spatially resolved analyses demonstrate how foam density properties translate from in vitro to in vivo treadmill running, with lower-density foam improving impact attenuation but elevating propulsive forces. Future work needs to verify this in an outdoor setting. Full article

The simultaneous measurement of strain and temperature using Fiber Bragg Grating (FBG) sensors presents a significant challenge due to the intrinsic cross-sensitivity of the Bragg wavelength. While recent studies have increasingly employed “black-box” machine learning algorithms to address this ambiguity, such approaches often overlook the physical limitations of the sensor’s spectral response. This paper challenges the assumption that advanced algorithms alone can compensate for data that is physically ambiguous. We propose a “Sensor-Algorithm Co-Design” methodology, demonstrating that robust discrimination is achievable only when the sensor architecture exhibits a unique, orthogonal physical signature. Using a rigorous Transfer Matrix Method (TMM) and 4 × 4 polarization analysis, we evaluate three distinct architectures. Quantitative analysis reveals that a standard Quadratically Chirped FBG (QC-FBG) functions as an “ill-conditioned baseline” failing to distinguish measurands due to feature space collapse ($K_{cond}>4600$). Conversely, we validate two robust co-designs: (1) An Amplitude-Modulated Superstructure FBG (S-FBG) paired with an Artificial Neural Network (ANN), utilizing thermally induced duty-cycle variations to achieve high accuracy ($~3.4 °\mathrm{C}$ error) under noise; and (2) A Polarization-Diverse Inverse-Gaussian FBG (IG-FBG) paired with a 4 × 4 K-matrix, exploiting strain-induced birefringence ($K_{cond}\approx 64$). Furthermore, we address the data scarcity issue in AI-driven sensing by introducing a Physics-Informed Neural Network (PINN) strategy. By embedding TMM physics directly into the loss function, the PINN improves data efficiency by 2.2× compared to standard models, effectively bridging the gap between physical modeling and data-driven inference, addressing the critical data scarcity bottleneck identified in recent optical sensing roadmaps. Full article

Understanding the influence of solvent environments on the excited-state charge transfer process remains a fundamental question in molecular photophysics and photochemistry. While twisted intramolecular charge transfer (TICT) is crucial in determining fluorescence efficiency and photostability, the combined effects of solvent polarity and hydrogen bonding interactions are still elusive. Here, we employ steady-state and femtosecond transient absorption (fs-TA) spectroscopy with density functional theory (DFT) calculations to investigate the excited-state dynamics of 7-(diethylamino)coumarin-3-carboxylic acid (7-DCCA) in different solvents. Our findings reveal that in highly polar solvents with strong hydrogen-donating and hydrogen-accepting capabilities, 7-DCCA undergoes significant TICT formation, resulting in fluorescence quenching. Conversely, in environments with low polarity or weak hydrogen-bonding interactions, this transformation is largely suppressed. Quantitative correlation analysis utilizing the Kamlet–Taft and Catalán four-parameter models further elucidates the synergistic role of solvent polarity and specific hydrogen-bonding parameters in modulating the steady-state spectral behavior of 7-DCCA. This study provides microscopic insights into solvent–charge transfer interactions and establishes a general framework for enhancing the luminescence efficiency and structural robustness of organic optoelectronic materials through strategic solvent engineering. Full article

A scheme of a photonic convolution processor based on a tunable electro-optic frequency comb is proposed. The optical frequency comb (OFC) is generated using a dual-parallel Mach–Zehnder modulator (DPMZM) driven by an RF signal. By adjusting the working parameters of the DPMZM, OFCs with different line number and frequency spacing can be produced to reconfigure the convolution kernel dimensions. A linearly chirped fiber Bragg grating (LCFBG) is employed to implement interleaving of temporal and spectral dimensions. The interleaved signals are sampled at specific time and summed after optoelectronic conversion, and the convolution operation is completed. In this work, using a 10 GHz RF signal, a 4-line OFC with a frequency spacing of 20 GHz and a 2-line OFC with a spacing of 40 GHz are generated to obtain a 2 × 2 and 1 × 2 convolution kernels, respectively. The convolution results are fed into an electronic pooling layer and a fully connected layer for classifying the images of the MNIST handwritten digit dataset. The results demonstrate that a classification accuracy of 95.7% is achieved using the 2 × 2 convolution kernel, and a higher classification accuracy of 96.5% is obtained with the 1 × 2 convolution kernel. Full article

The development of rapid and intelligent methods is urgently needed for wheat quality evaluation. Using the prediction of wet gluten content as a case study, this work systematically investigated the performance of various machine learning algorithms and their optimization for content prediction, based on hyperspectral data from the visible and near-infrared ranges of wheat grains and flour. The results revealed that the random forest regression (RFR) algorithm delivered the best predictive performance under two conditions: first, when applied directly to visible spectra; and second, when applied to fused visible and near-infrared spectral data. This held true for both grains and flour. Conversely, its direct application to NIR spectra alone yielded relatively worse performance. Following data optimization, the first-derivative (FD) visible spectra of wheat grains were smoothed using a Savitzky–Golay (SG) filter and subsequently used as input for the RFR model. This optimized approach achieved a coefficient of determination (r²) of 0.8579, a root mean square error (RMSE) of 0.0216, and a relative percent deviation (RPD) of 2.6978. Under the same conditions, for wheat flour, the corresponding values were 0.8383, 0.0231, and 2.5293, respectively. Similarly, for wheat flour, the RFR model was applied to the SG-filtered FD spectra derived from the fused visible and near-infrared data, yielding an r² of 0.8474, an RMSE of 0.0224, and an RPD of 2.6034. Under the same conditions, wheat grains yielded an r² of 0.8494, an RMSE of 0.0223, and an RPD of 2.6208. This efficient and rapid intelligent prediction scheme demonstrates considerable potential for the quality assessment and control of relevant food products. Full article

This study aimed to detect dementia using intelligent hyperspectral imaging (HSI), which enables the extraction of detailed spectral information from retinal tissues. A total of 3256 ophthalmoscopic images collected from 137 participants were analyzed. The spectral signatures of selected retinal regions were reconstructed using hyperspectral conversion techniques to examine wavelength-dependent variations associated with dementia. To assess the diagnostic capability of deep learning models, four convolutional neural network (CNN) architectures—ResNet50, Inception_v3, GoogLeNet, and EfficientNet—were implemented and benchmarked on two datasets: original ophthalmoscopic images (ORIs) and hyperspectral images (HSIs). The HSI-based models consistently demonstrated superior accuracy, achieving 84% with ResNet50, 83% with GoogLeNet, and 82% with EfficientNet, compared with 80–81% obtained from ORIs. Inception_v3 maintained an accuracy of 80% across both datasets. These results confirm that integrating spectral information enhances model sensitivity to dementia-related retinal changes, highlighting the potential of HSI for early and noninvasive detection. Full article

Developing organic photothermal agents that are highly stable and have tunable electronic properties is important for advancing low-invasive cancer therapy. In this study, we present the synthesis and evaluation of three conjugated photothermal agents inspired by non-fullerene Y-series acceptors: the small molecule BTPT-OD, as well as two of its polymer derivatives with regular (r-BTPT) and irregular (ir-BTPT) structures. All of the compounds absorb light effectively in the red and near-infrared spectral ranges, with absorption maxima from 734 to 746 nm, and form stable nanoparticles (NPs) via nanoprecipitation, ranging in size from 13 to 39 nm. NPs exhibited negative surface charges, with ζ-potentials of −12.9, −15.5, and −17.9 mV for BTPT-OD, r-BTPT, and ir-BTPT NPs, respectively. Irradiation at a wavelength of 730 nm revealed that r-BTPT and ir-BTPT polymer NPs exhibited a 22- to 40-fold greater phototoxicity against A-549, Sk-Br-3, and MCF-7 human carcinoma cells than the non-polymeric analogue BTPT-OD. The measured photothermal conversion efficiencies ranged from 24 to 27 ± 5%. At the same time, the intracellular ROS generation quantified by the 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA) assay was low, allowing us to propose heat-mediated photothermal therapy as a more significant cell death predictor than ROS-mediated photodynamic therapy. This work is one of the first to compare small and polymeric non-fullerene acceptor materials for phototherapy purposes, demonstrating the advantages of using polymers. Full article

Photoluminescent liquid crystals with photoluminescence (PL) and liquid-crystalline (LC) properties have attracted attention as PL-switching materials owing to their thermally induced phase transitions, such as crystal → smectic A/nematic → isotropic phase transitions. Our group previously developed tetrafluorinated tolane mesogenic dimers linked by flexible alkylene-1,n-dioxy spacers, demonstrating that the position of the tetrafluorinated aromatic ring critically influences the LC behavior. However, these compounds exhibited very weak fluorescence owing to an insufficient D–π–A character of the π-conjugated mesogens, which facilitated internal conversion from emissive ππ* to non-emissive πσ* states. We designed and synthesized derivatives in which the mesogen–spacer linkage was modified from ether to ester, thereby enhancing the D–π–A character. Thermal and structural analyses revealed spacer-length parity effects: even-numbered spacers induced nematic phases, whereas odd-numbered spacers stabilized smectic A phases. Photophysical studies revealed multi-state PL across solution, crystal, and LC phases. Strong blue PL (Φ_PL = 0.39–0.48) was observed in solution, while crystals exhibited aggregation-induced emission enhancement (Φ_PL = 0.48–0.77) with spectral diversity. In LC states, Φ_PL values up to 0.36 were maintained, showing reversible intensity and spectral shifts with phase transitions. These findings establish design principles that correlate spacer parity, phase behavior, and PL properties, enabling potential applications in PL thermosensors and responsive optoelectronic devices. Full article

The management of age-related macular degeneration (AMD) presents a significant challenge attributable to high disease heterogeneity. Patient realization of symptoms is poor and it is urgent to treat before permanent anatomic damage results in vision loss. This is true for the initial conversion from non-exudative intermediate AMD (iAMD) to exudative AMD (nAMD), and for the recurrence of nAMD undergoing treatment. Starting from the essential requirements that any practical solution needs to fulfill, we will reflect on how persistent navigation towards innovative solutions during a 25-year journey yielded significant advances towards improvements in personalized care. An early insight was that the acute nature of AMD progression requires frequent monitoring and therefore diagnostic testing should be performed at the patient’s home. Four key requirements were identified: (1) A tele-connected home device with acceptable diagnostic performance and a supportive patient user interface, both hardware and software. (2) Automated analytics capabilities that can process large volumes of data. (3) Efficient remote patient engagement and support through a digital healthcare provider. (4) A low-cost medical system that enables digital healthcare delivery through appropriate compensation for both the monitoring provider and the prescribing physician services. We reviewed the published literature accompanying first the development of Preferential Hyperacuity Perimetry (PHP) for monitoring iAMD, followed by Spectral Domain Optical Coherence Tomography (SD-OCT) for monitoring nAMD. Emphasis was given to the review of the validation of the core technologies, the regulatory process, and real-world studies, and how they led to the release of commercial services that are covered by Medicare in the USA. We concluded that while during the first quarter of the 21st century, the two main pillars of management of AMD were anti-VEGF intravitreal injections and in-office OCT, the addition of home-monitoring-based digital health services can become the third pillar. Full article

The implementation of photoelectric conversion in photoelectric integrated systems requires the design of photodetectors (PDs) with quick response times and low power consumption. In this work, the self-powered photodetector was prepared by antimony selenide (Sb₂Se₃) microwires (MW)/Se microtube (MT) heterojunction by coating Ag nanowires (NW). The incorporation of Ag-NW involves dual enhancement mechanisms. First, the surface plasmon resonance (SPR) effect amplifies the light absorption across UV–vis–NIR spectra, and the conductive networks facilitate the rapid carrier transport. Second, the type-II band alignment between Sb₂Se₃ and Se synergistically separates photogenerated carriers, while the Ag-NW further suppress the recombination through built-in electric field modulation. The optimized device achieves remarkable responsivity of 122 mA W⁻¹ at 368 nm under zero bias, with a response/recovery time of 8/10 ms, outperforming most reported Sb₂Se₃-based detectors. The heterostructure provides an effective strategy for developing self-powered photodetectors with broadband spectral adaptability. The switching ratio, responsivity, and detectivity of the Sb₂Se₃-MW/Se-MT/Ag-NW device increased by 260%, 810%, and 849% at 368 nm over the Sb₂Se₃-MW/Se-MT device, respectively. These results show that the addition of Ag-NW effectively improves the photoelectric performance of the Sb₂Se₃-MW/Se-MT heterojunction, providing new possibilities for the application of self-powered optoelectronic devices. Full article

Accurate and robust classification of dementia subtypes using non-invasive electroencephalography (EEG) signals remains a critical challenge for clinicians and researchers in the field of neuroscience. Traditional methods often rely on limited spectral features, overlooking the rich structural and geometric information inherent in EEG dynamics. CONECT (Complex Network Conversion and Topology), a novel framework, is introduced and built upon four core innovations. First, EEG time series are transformed into weighted networks using a novel Angle-Relation Connection (ARC) rule, a geometry-based approach that links time points based on angular monotonicity. Secondly, a tunable edge-weighting function is introduced by integrating amplitude, temporal, and angular components, providing adaptable heuristics adaptable to the most promising biomarker, i.e., curvature-driven features in dementia. Additionally, two new graph-based EEG features, the Weighted Angular Irregularity Index (WAII) and the Curvature-Based Edge Feature Index (CBEFI), are proposed as potential biomarkers to capture localized irregularity and signal geometry, respectively. For the first time in a dementia EEG classification study using the OpenNeuro ds004504 dataset (raw), Ant Colony Optimization (ACO) is applied as a feature selection technique to select the most discriminative features and improve model classification and transparency. The classification results demonstrate CONECT’s potential as a promising, interpretable, and geometry-informed framework for accurate and practical dementia subtype diagnosis. Full article

A novel wavelength-selective absorber is numerically designed and analyzed using a three-dimensional finite-difference time-domain method. The proposed solar thermal absorber consists of an array of asymmetric tungsten ring nanowires deposited on a tungsten thin film. This structure achieves high solar absorption efficiency (78.5%) and low thermal emissivity (5%) at 100 °C, resulting in a photothermal conversion efficiency of 73.55% under standard solar illumination. The selective absorption arises from the excitation of magnetic polaritons and surface plasmon polaritons. To further elucidate the physical mechanisms behind the spectral response, an equivalent inductor–capacitor circuit model is employed. The absorber also exhibits polarization-insensitive and angle-independent performance up to 50° for both transverse magnetic and transverse electric polarizations. These results demonstrate the potential of the proposed metamaterial absorber for advanced applications in solar energy harvesting, photothermal conversion, and thermal emission. Full article