Search Results (270)

Pain following orthodontic treatment is the chief complaint of patients undergoing this form of treatment. Although the use of diode lasers has been suggested for pain reduction, the mechanism of laser-induced analgesic effects remains unclear. Neuropeptides, such as substance P (SP) and calcitonin gene-related peptide (CGRP), contribute to the transmission and maintenance of inflammatory pain. Heat shock protein (HSP) 70 plays a protective role against various stresses, including orthodontic forces. This study aimed to examine the effects of diode laser irradiation on neuropeptides and HSP 70 expression in periodontal tissues induced by experimental tooth movement (ETM). For inducing ETM for 24 h, 50 g of orthodontic force was applied using a nickel–titanium closed-coil spring to the upper left first molar and the incisors of 20 male Sprague Dawley rats (7 weeks old). The right side without ETM treatment was considered the untreated control group. In 10 rats, diode laser irradiation was performed on the buccal and palatal sides of the first molar for 90 s with a total energy of 100.8 J/cm². A near-infrared (NIR) laser with a 808 nm wavelength, 7 W peak power, 560 W average power, and 20 ms pulse width was used for the experiment. We measured the number of facial groomings and vacuous chewing movements (VCMs) in the ETM and ETM + laser groups. Immunohistochemical staining of the periodontal tissue with SP, CGRP, and HSP 70 was performed. The number of facial grooming and VCM periods significantly decreased in the ETM + laser group compared to the ETM group. Moreover, the ETM + laser group demonstrated significant suppression of SP, CGRP, and HSP 70 expression. These results suggest that the diode laser demonstrated analgesic effects on ETM-induced pain by inhibiting SP and CGRP expression, and decreased HSP 70 expression shows alleviation of cell damage. Thus, although further validation is warranted for human applications, an NIR diode laser can be used for reducing pain and neuropeptide markers during orthodontic tooth movement. Full article

The inspection of encapsulated MEMS devices typically relies on destructive methods which compromise the structural integrity of samples. In this work, we present the concept and preliminary experimental validation of a laser scanning setup to non-destructively inspect silicon-encapsulated microstructures by measuring small variations of transmitted light intensity in the near-infrared spectrum. This method does not require any particular sample preparation or damage, and it is based on the higher degree of transparency of silicon in the near-infrared and the transmission contrast resulting from the Fresnel reflections observed at the interfaces between the different materials of the MEMS device layers. We characterise the small feature resolving performance of the laser scanning setup using standard targets, and experimentally demonstrate the inspection of a MEMS latching device enclosed within silicon covers, comparing the contrast measurements with theoretical predictions. Full article

Palladium (Pd) and titanium (Ti) exhibit opposite dielectric responses upon hydrogenation, with stronger effects observed in the near-infrared (NIR) region. Leveraging this contrast, we investigated Ti/Pd bilayer thin films as a platform for NIR hydrogen sensing—particularly at telecommunication-relevant wavelengths, where such devices have remained largely unexplored. Ti/Pd bilayers coated with Teflon AF (TAF) and fabricated via sequential electron-beam and thermal evaporation were characterized using optical transmission measurements under repeated hydrogenation cycles. The Ti (5 nm)/Pd (x = 2.5 nm)/TAF (30 nm) architecture showed a 2.7-fold enhancement in the hydrogen-induced optical contrast at 1550 nm compared to Pd/TAF reference films, attributed to the hydrogen ion exchange between the Ti and Pd layers. The optimized structure, with a Pd thickness of x = 1.9 nm, exhibited hysteresis-free sensing behavior, a rapid response time (${\mathrm{t}}_{90}$ < 0.35 s at 4% ${\mathrm{H}}_2$), and a detection limit below 10 ppm. It also demonstrated excellent selectivity with negligible cross-sensitivity to $\mathrm{C}{\mathrm{O}}_2$, $\mathrm{C}{\mathrm{H}}_4$, and CO, as well as high durability, showing less than 6% signal degradation over 135 hydrogenation cycles. These findings establish a scalable, room-temperature NIR hydrogen sensing platform with strong potential for deployment in automotive, environmental, and industrial applications. Full article

Optical tactile sensing is gaining traction as a foundational technology in collaborative and human-interactive robotics, where reliable touch and pressure feedback are critical. Traditional systems based on total internal reflection (TIR) and frustrated TIR (FTIR) often require complex infrared setups and lack adaptability to curved or flexible surfaces. To overcome these limitations, we developed OptoSkin—a novel tactile platform leveraging direct time-of-flight (ToF) LiDAR principles for robust contact and pressure detection. In this extended study, we systematically evaluate how key optical properties of waveguide materials affect ToF signal behavior and sensing fidelity. We examine a diverse set of materials, characterized by varying light transmission (82–92)%, scattering coefficients (0.02–1.1) cm⁻¹, diffuse reflectance (0.17–7.40)%, and refractive indices 1.398–1.537 at the ToF emitter wavelength of 940 nm. Through systematic evaluation, we demonstrate that controlled light scattering within the material significantly enhances ToF signal quality for both direct touch and near-proximity sensing. These findings underscore the critical role of material selection in designing efficient, low-cost, and geometry-independent optical tactile systems. Full article

This study investigates a noninvasive continuous glucose monitoring (NI-CGM) system optimized for earlobe application, leveraging the site’s anatomical advantages—absence of bone, muscle, and thick skin—for enhanced optical transmission. The system integrates multimodal sensing, combining near-infrared (NIR) diffuse transmission with temperature and pressure sensors. A novel Multi-Wavelength Slope Efficiency Near-Infrared Spectroscopy (MW-SE-NIRS) method is introduced, enhancing noise robustness through the slope efficiency-based parameterization of NIR signal dynamics. By employing three NIR wavelengths with distinct scattering and absorption properties, the method improves glucose detection reliability, addressing tissue heterogeneity and physiological noise in noninvasive monitoring. To validate the feasibility, a pilot clinical trial enrolled five participants with normal or pre-diabetic glucose profiles. Continuous glucose data capturing pre- and postprandial variations were analyzed using a 1D convolutional neural network (Conv1D). For three subjects under stable physiological conditions, the model achieved 97.0% Clarke error grid (CEG) A-Zone accuracy and a mean absolute relative difference (MARD) of 5.2%. Across all participants, results showed 90.9% CEG A-Zone accuracy and a MARD of 8.4%, with performance variations linked to individual factors such as earlobe thickness variability and physical activity. These outcomes demonstrate the potential of the MW-SE-NIRS system for noninvasive glucose monitoring and highlight the importance of future work on personalized modeling, sensor optimization, and larger-scale clinical validation. Full article

High-repetition-rate targets present an opportunity for developing diagnostic tools for on-demand calibration at high-power laser facilities for consistent performance and reproducibility during experimental campaigns. The non-linear change in transmission associated with a laser-driven plasma mirror, based on high-repetition rate targets, has been used in a Frequency Resolved Optical Gating (FROG) configuration to analyze the spectral phase for near-infrared pulses far from the Fourier limit. Three types of targets were compared for characterizing pulses in the 1–8 ps range: a glass slide, a polymer tape, and a thin liquid sheet created by two impinging micrometer-scale jets. The thin liquid film had the best mechanical stability and introduced the least spectral distortion, allowing the most robust reconstruction of the temporal intensity profile. The spectral phase was reconstructed using a non-iterative algorithm, which reproduced the second-order phase distortions induced with an acousto-optic programmable dispersive filter with an RMS error of 6.2%, leading to measured pulse durations with an RMS deviation ranging from 1% for pulses of 6.8–7.8 ps up to 7.5% for pulses around 1 ps. Full article

This paper demonstrates the sorting and detection of near-infrared vortex light using a nonlinear Dammann vortex grating. By incorporating a forked structure into the nonlinear Dammann grating, the resulting nonlinear Dammann vortex grating is capable of converting near-infrared Gaussian light into a visible vortex array. The array comprises 49 independent detection channels, each of which can precisely control the inherent topological charge values. When the topological charge value of a detection channel’s vortex light matches that of the incident vortex, the vortex degenerates into a Gaussian spot, thereby enabling the detection of the incident vortex’s topological charge. Our experimental results show that this grating, with its 49 independent detection channels, can detect the topological charge values of vortex light in the near-infrared range from l = −12 to +12 in real-time. Compared to existing solutions, this grating offers enhanced versatility and has potential applications in optical communication systems for the transmission, reception, and multiplexing of OV beams. Full article

A novel nested structure of hollow-core anti-resonant optical fiber is proposed to achieve low loss, large effective mode area, and wide transmission band simultaneously in the near-infrared range of 1200–2200 nm. It is composed of six elliptical cladding tubes nested with six large circular cladding tubes, and six small circular cladding tubes are introduced in the gap of the elliptical tubes. The transmission characteristics of the hollow-core anti-resonant optical fiber are numerically investigated using the full-vector finite element method. The effects of structural parameters such as the cladding tube thickness and the tube diameters on the fiber transmission characteristics are analyzed in detail. The results indicate that within the wavelength range of 1200–2200 nm, the confinement loss remains below 0.017 dB/km, and the minimum confinement loss can be as low as 1.2 × 10⁻⁴ dB/km at 1500 nm. The effective mode area remains as large as ~1142.5 μm². It should be noted that in the wide wavelength range of 1000 nm, the dispersion exhibits excellent characteristics ranging from 0.7 to 1.4 ps/(nm·km). Our fiber can find potential applications in ultra-long-distance and ultra-high-power transmission systems with a wide operating wavelength band. Full article

Extreme ultraviolet (EUV) imagers are key tools to monitor the space environment and forecast space weather. EUV filters are important components to block radiation in the ultraviolet (UV), visible, and near-infrared (IR) regions. In this study, various characterization methods were proposed for the nickel mesh-supported indium (In) filter, and their spectral characteristics were comprehensively studied. The material and thickness of the filter were chosen based on atomic scattering principles, determined through theoretical calculation and software simulation. The metal film was deposited using the vacuum-resistive thermal evaporation method. The measured transmission of the filter was 10.06% at 83.4 nm. The surface elements of the sample were analyzed using X-ray photoelectron spectroscopy (XPS). The surface and cross-sectional morphologies of the filter were observed using a scanning electron microscope (SEM). The impact of the oxide layer and carbon contamination on the filter’s transmittance was investigated using an ellipsometer. A multilayer “In-In₂O₃-C” model was established to determine the thickness of both the oxide layer and carbon contamination layer on the filter. This model introduces the filling factor based on the original model and considers the diffusion of the contamination layer, resulting in more accurate fitting results. The transmittance of the filter in the visible light range was measured using a UV-VIS spectrophotometer, and the measurement error was analyzed. This article provides preparation methods and test methods for the 83.4 nm EUV filter and conducts a detailed analysis of the spectral characteristics of the prepared optical filters, which hold significant value for space exploration applications. Full article

The use of solar energy to convert CO₂ into value-added chemicals is a promising sustainable development strategy. In this study, a black graphitic carbon nitride (CN-B) photocatalyst was fabricated through a single-step calcination process, employing phloxine B and urea as the precursor materials. The catalysts were characterized using TEM, XRD, FTIR, XPS and so on. The amount of prepolymer phloxine B was 25 mg, 35 mg and 45 mg, respectively, and the obtained samples were CN-B-0.025, CN-B-0.035 and CN-B-0.045. All samples were used for visible-catalyzed CO₂ reduction. The experimental findings indicate that the CO evolution rate of the optimal photocatalyst CN-B-0.035 reaches 27.56 μmol g_cat.⁻¹ h⁻¹. This value is nine-fold higher than that of pure CN, which has a CO evolution rate of 3.22 μmol g_cat.⁻¹ h⁻¹. The excellent photocatalytic reduction performance is due to the following factors: Firstly, the exceedingly thin nanosheet structure of the catalyst enhances the velocity of the charge transfer, and transmission electron microscopy (TEM) analysis shows that the nanosheet thickness of the catalyst CN-B is significantly thinner. Secondly, the light absorption capacity of the catalyst is enhanced. The absorbance of CN-B increases significantly in the ultraviolet region and extends to the near-infrared region, as shown with UV diffuse reflection spectroscopy. Finally, the photothermal effect of CN-B causes the catalyst temperature to rise rapidly from 20 °C to 131 °C within 120 s, which further promotes photogenerated carrier separation. This research offers a novel approach to the development of photocatalysts aimed at the photothermal-assisted photocatalytic conversion of CO₂. Full article

To address the issues of insufficient rigor in existing methods for quantifying apple watercore severity and the complexity and low accuracy of traditional classification models, this study proposes a method for watercore quantification and a classification model based on a deep convolutional neural network. Initially, visible/near-infrared transmission spectral data of apple samples were collected. The apples were then sliced into 4.5 mm thick sections using a specialized tool, and image data of each slice were captured. Using BiSeNet and RIFE algorithms, a three-dimensional model of the watercore regions was constructed from the apple slices to calculate the watercore severity, which was subsequently categorized into five distinct levels. Next, methods such as the Gramian Angular Summation Field (GASF), Gram Angular Difference Field (GADF), and Markov Transition Field (MTF) were applied to transform the one-dimensional spectral data into two-dimensional images. These images served as input for training and prediction using the ConvNeXt deep convolutional neural network. The results indicated that the GADF method yielded the best performance, achieving a test set accuracy of 98.73%. Furthermore, the study contrasted the classification and prediction of watercore apples using traditional methods with the existing quantification approaches for watercore levels. The comparative results demonstrated that the proposed GADF-ConvNeXt model is more straightforward and efficient, achieving superior performance in classifying watercore grades. Furthermore, the newly proposed quantification method for watercore levels proved to be more effective. Full article

Optical sensing technologies play a crucial role in various fields such as biology, medicine, and food safety by measuring changes in material properties, such as the refractive index, light absorption, and scattering. Dielectric metasurfaces, with their subwavelength-scale geometric features and the ability to achieve high-quality-factor (Q-value) resonances through specific meta-atom designs, offer a new avenue for achieving faster and more sensitive material detection. The resonant wavelength, as one of the key indicators in meta-atom design, is usually determined using traditional solving methods such as electromagnetic simulations, which, although capable of providing high-precision prediction results, suffer from slow computational speed and long processing times. To address this issue, this paper proposes a forward prediction network for the amplitude spectrum of dielectric metasurfaces. Test results demonstrated that the mean square error of this network was consistently less than ${10}^{-3}$, and the neural network required less than 1 s, indicating its high-precision prediction capability. Furthermore, we employed transfer learning to apply this network to predict the near-infrared transmission spectra of high-Q-value resonant dielectric metasurfaces, achieving significant effectiveness. This method greatly enhanced the efficiency of metasurface design, and the designed network could serve as a universal backbone model for the forward prediction of spectral responses for other types of dielectric metasurfaces. Full article

Due to a lower InN bandgap $\mathrm{e}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{y} {\mathrm{E}}_{\mathrm{g}}~0.7 \mathrm{e}\mathrm{V}$, ${\mathrm{I}\mathrm{n}}_{\mathrm{x}}{\mathrm{G}\mathrm{a}}_{1-\mathrm{x}}\mathrm{N}/\mathrm{S}\mathrm{a}\mathrm{p}\mathrm{p}\mathrm{h}\mathrm{i}\mathrm{r}\mathrm{e}$ epifilms are considered valuable in the development of low-dimensional heterostructure-based photonic devices. Adjusting the composition x and thickness d in epitaxially grown films has offered many possibilities of light emission across a wide spectral range, from ultraviolet through visible into near-infrared regions. Optical properties have played important roles in making semiconductor materials useful in electro-optic applications. Despite the efforts to grow ${\mathrm{I}\mathrm{n}}_{\mathrm{x}}{\mathrm{G}\mathrm{a}}_{1-\mathrm{x}}\mathrm{N}$/Sapphire samples, no x- and d-dependent optical studies exist for ultrathin films. Many researchers have used computationally intensive methods to study the electronic band structures ${\mathrm{E}}_{\mathrm{j}}\left(\overrightarrow{\mathrm{k}}\right),$ and subsequently derive optical properties. By including inter-band transitions at critical points from ${\mathrm{E}}_{\mathrm{j}}\left(\overrightarrow{\mathrm{k}}\right)$, we have developed a semiempirical approach to comprehend the optical characteristics of InN, GaN and ${\mathrm{I}\mathrm{n}}_{\mathrm{x}}{\mathrm{G}\mathrm{a}}_{1-\mathrm{x}}\mathrm{N}$. Refractive indices of ${\mathrm{I}\mathrm{n}}_{\mathrm{x}}{\mathrm{G}\mathrm{a}}_{1-\mathrm{x}}\mathrm{N}$ and sapphire substrate are meticulously integrated into a transfer matrix method to simulate d- and x-dependent reflectivity $\mathrm{R}\left(\mathrm{E}\right)$ and transmission $\mathrm{T}\left(\mathrm{E}\right)$ spectra of nanostructured ${\mathrm{I}\mathrm{n}}_{\mathrm{x}}{\mathrm{G}\mathrm{a}}_{1-\mathrm{x}}\mathrm{N}/\mathrm{S}\mathrm{a}\mathrm{p}\mathrm{p}\mathrm{h}\mathrm{i}\mathrm{r}\mathrm{e}$ epifilms. Analyses of $\mathrm{R}\left(\mathrm{E}\right)$ and $\mathrm{T}\left(\mathrm{E}\right)$ have offered accurate x-dependent shifts of energy gaps for ${\mathrm{I}\mathrm{n}}_{\mathrm{x}}{\mathrm{G}\mathrm{a}}_{1-\mathrm{x}}\mathrm{N}$ (x = 0.5, 0.7) in excellent agreement with the experimental data. Full article

Near-infrared imaging devices are extensively used in medical diagnosis, night vision, and security monitoring. However, existing traditional imaging devices rely on a bunch of refracting lenses, resulting in large, bulky imaging systems that restrict their broader utility. The emergence of flat meta-optics offers a potential solution to these limitations, but existing research on compact integrated devices based on near-infrared meta-optics is insufficient. In this study, we propose an integrated NIR imaging camera that utilizes large-size metalens with a silicon nanostructure with high transmission efficiency. Through the detection of target and animal and plant tissue samples, the ability to capture biological structures and their imaging performance was verified. Through further integration of the NIR imaging device, the device significantly reduces the size and weight of the system and optimizes the aperture to achieve excellent image brightness and contrast. Additionally, venous imaging of human skin shows the potential of the device for biomedical applications. This research has an important role in promoting the miniaturization and lightweight of near-infrared optical imaging devices, which is expected to be applied to medical testing and night vision imaging. Full article

Lossless image compression is vital for missions with limited data transmission bandwidth. Reducing file sizes enables faster transmission and increased scientific gains from transient events. This study compares two wavelet-based image compression algorithms, CCSDS 122.0 and JPEG 2000, used in the European Space Agency Comet Interceptor and Hera missions, respectively, in varying scenarios. The JPEG 2000 implementation is sourced from the JasPer library, whereas a custom implementation was written for CCSDS 122.0. The performance analysis for both algorithms consists of compressing simulated asteroid images in the visible and near-infrared spectral ranges. In addition, all test images were noise-filtered to study the effect of the amount of noise on both compression ratio and speed. The study finds that JPEG 2000 achieves consistently higher compression ratios and benefits from decreased noise more than CCSDS 122.0. However, CCSDS 122.0 produces comparable results faster than JPEG 2000 and is substantially less computationally complex. On the contrary, JPEG 2000 allows dynamic (entropy-permitting) reduction in the bit depth of internal data structures to 8 bits, halving the memory allocation, while CCSDS 122.0 always works in 16-bit mode. These results contribute valuable knowledge to the behavioral characteristics of both algorithms and provide insight for entities planning on using either algorithm on board planetary missions. Full article