Optimal Wavelength Research Articles

Super Broadband Emission Across NIR‐I and NIR‐II Under Blue Light Excitation of Cr3+, Ni2+ Co‐Doped Sr2GaTaO6 Phosphor Achieved by Two‐Site Occupation and Effective Energy Transfer

AbstractThe performance of the near‐infrared phosphor‐converted light‐emitting diodes (NIR pc‐LEDs) mainly depends on the NIR emitting phosphors used. Cr3+ doped materials can be excited by blue light chips, but their emission is located in the NIR‐I region (650–1000 nm). Ni2+ doped materials are mainly located in the NIR‐II region (1000–1700 nm), but they cannot be effectively excited by blue light chips. Herein, Cr3+, Ni2+ mono‐doped, and co‐doped Sr2GaTaO6 NIR emitting phosphors are prepared and investigated. Cr3+ and Ni2+ ions occupy two octahedral sites of Ga3+ and Ta5+. The co‐doping of Cr3+ ions has achieved two breakthroughs. One is to shift the optimal excitation wavelength from violet light to blue light due to the energy transfer (efficiency up to 70%) from Cr3+ to Ni2+. The other is to achieve the broadband and continuous emission across NIR‐I and NIR‐II regions (650–1700 nm, with a full width at half maximum (FWHM) of 410 nm (173 nm + 237 nm)). The prepared Sr2GaTaO6: 0.02Cr3+, 0.01Ni2+ phosphor is combined with a commercial 460 nm blue chip to realize its application in organic compounds identification, night vision, and biological imaging. This work points out a direction for the future development of efficient super broadband NIR‐emitting phosphors.

Dual-mode luminescence light intensity modulation characteristics and optical radiation dependence of stannate photochromic ceramics

Alkaline earth stannate is characterized by good physicochemical stability. It has been applied in the field of optical information storage by coupling photoluminescence intensity modulation and photochromic performance, which has attracted the attention of researchers. The development of alkaline earth stannate ceramics with high light intensity modulation properties and non-destructive reading of optical information is of great research value. In this study, Er3+-doped Ca2SnO4 photochromic ceramics were prepared by high-temperature solid-phase reaction method. Alternating UV light irradiation and thermal stimulation, the ceramics achieve a reversible transition between light and dark gray. Er3+ doping gives the ceramics dual-mode luminescence light intensity modulation performance. When the doping amount of Er3+ is 0.01 mol, there is a maximum down-conversion luminous intensity modulation ratio of 93%, which is higher than most of the same type of photochromic materials. The photochromic behavior is explained using the capture-release model of traps for carriers, and the dual-mode luminescence light-intensity modulation behavior is analyzed through the energy transfer mechanism. The optical radiation response properties were investigated and the optimum light response wavelength is found to be 290 nm, which is related to the optical band gap Eg. And the selection of the optimal light response wavelength can effectively improve the performance of photochromic and light intensity modulation. This study provides a promising strategy for performance enhancement of photochromic materials.

Construction of a sustainable model to predict the moisture content of porang powder (Amorphophallus oncophyllus) based on pointed-scan visible near-infrared spectroscopy

Abstract The moisture content of porang powder (PP) is an inherent quality parameter. Therefore, several analytical methods, such as oven drying and Karl–Fischer titration, were applied to determine the content. However, these techniques are noted to have various disadvantages, such as being time-consuming, requiring sample preparation, being labor-intensive, and producing chemical waste. This study aims to investigate the potential of visible near-infrared (Vis-NIR) spectroscopy as a nondestructive and sustainable analytical technology to predict moisture content in PP. In this study, we developed a traditional machine learning algorithm, a partial least squares regression (PLSR), in tandem with two spectral bands, which are Vis-NIR (400–1,000 nm) and NIR (954–1,700 nm). To upgrade the performance of PLSR, we applied seven preprocessing techniques: mean normalization, maximum normalization, range normalization, multiplicative scatter correction, standard normal variate (SNV), and Savitzky–Golay first and second derivatives. We found that PLSR using NIR spectral bands was more effective; the preprocessed mean normalization exhibited the best results with a coefficient of determination ( R p 2 ) \left({R}_{p}^{2}) of 0.96 and a standard error prediction (SEP) of 0.56 using five latent variables. Furthermore, we also extracted 39 optimum wavelengths using variable importance in projection and achieved better performance ( R p 2 {R}_{p}^{2} = 0.95, SEP = 0.56%wb, and 5 LVs) via SNV preprocessed NIR spectra.

Fluorescence spectroscopy detection of carbendazim residue in cucumber juice based on BC

Excessive residues of the carbendazim pesticide in food will cause food safety issues. Particularly, cucumber is one of the common vegetables with carbendazim residues. This study, using fluorescence spectroscopy technology, explored the residues of carbendazim in cucumbers. First, a fluorescence spectrophotometer was used to scan and obtain the three-dimensional fluorescence spectra of carbendazim standard and four carbendazim formulations. Analyzing and comparing their respective fluorescence characteristics, fluorescence peak 1: Ex/Em=245/300–320 nm and fluorescence peak 2: Ex/Em=280/300–320 nm have been identified as the fluorescence characteristic peaks of carbendazim, and the optimal excitation wavelengths Ex=245 nm and Ex=280 nm with carbendazim specificity was screened. Subsequently, two-dimensional fluorescence spectroscopy was performed on the carbendazim and cucumber-carbendazim mixed solutions using the optimal excitation wavelength. In order to obtain more effective two-dimensional spectral data, the original fluorescence spectrum of the cucumber-carbendazim mixed solution was subjected to Blank Correction (BC), significantly reducing the impact of cucumber's own fluorescent characteristics on the carbendazim fluorescent peak in the mixed solution. Polynomial models and linear prediction models were developed based on the concentration of carbendazim and the fluorescence peak intensity values obtained after BC. The detection limit value of carbendazim residues in the cucumber-carbendazim mixed system included the maximum pesticide residue limit specified by national food safety regulations. This research provides valuable data and technical support for efficient detection of pesticide residues in cucumbers.

Identification of optimal hyperspectral wavelength to discriminate maize and sorghum crops using AVIRIS-NG data in Guntur district, Andhra Pradesh, India

Identification of optimal hyperspectral wavelength to discriminate maize and sorghum crops using AVIRIS-NG data in Guntur district, Andhra Pradesh, India

Application of hyperspectral imaging and colorimetric sensor array coupled with multivariate analysis for quality detection during salted duck eggs processing

AbstractIn order to realize the evaluation of salted duck eggs quality, this study constructed salts‐sensitive colorimetric sensor array (CSA) based on silver nanoprisms (AgNPRs) etching principle and utilized hyperspectral imaging (HSI) system to capture the reflectance spectral of CSA and section of salted duck eggs. To minimize the noise in spectral signals, three preprocessing methods including Savitzky–Golay Smoothing (SG), standard normal variate (SNV) transformation, and multiplicative scatter correction were used. The competitive adaptive reweighted sampling and uninformative variables elimination were used to select the optimal wavelengths, and then partial least squares regression was used to predict moisture, lipid, and salt content (SC). Results demonstrated coefficients of determination of 0.8200, 0.8969, 0.8709, and 0.9239 for protein moisture, yolk moisture, yolk lipid, and protein SC. Visualization distribution maps successfully display the distribution of moisture and lipid content during salting periods. The results indicated that the CSA based on AgNPRs etching principle can be an effective tool in quantitative measurement of salt and HSI combining CSA can be applied to evaluate the quality of salted duck eggs comprehensively. The study offers a rapid detection method for the production and processing of salted duck eggs in the industry.Practical applicationA novel salts‐sensitive CSA was constructed to evaluate quality of salted duck eggs based on AgNPRs etching. This study designed and developed a portable sample collection device using 3D printing technology to acquire the information of samples and CSA at the same time. This study combined with HSI system and colorimetric sensor technology to evaluate the quality of salted duck eggs during the salting process.

The ideal wavelength for daylight free-space quantum key distribution

Quantum key distribution (QKD) has matured in recent years from laboratory proof-of-principle demonstrations to commercially available systems. One of the major bottlenecks is the limited communication distance in fiber networks due to the exponential signal damping. To bridge intercontinental distances, low Earth orbit satellites transmitting quantum signals over the atmosphere can be used. These free-space links, however, can only operate during the night, as the sunlight otherwise saturates the detectors used to measure the quantum states. For applying QKD in a global quantum internet with continuous availability and high data rates, operation during daylight is required. In this work, we model a satellite-to-ground quantum channel for different quantum light sources to identify the optimal wavelength for free-space QKD under ambient conditions. Daylight quantum communication is possible within the Fraunhofer lines or in the near-infrared spectrum, where the intrinsic background from the sun is comparably low. The highest annual secret key length considering the finite key effect is achievable at the Hα Fraunhofer line. More importantly, we provide the fundamental model that can be adapted, in general, to any other specific link scenario taking into account the required modifications. We also propose a true single-photon source based on a color center in hexagonal boron nitride coupled to a microresonator that can implement such a scheme. Our results can also be applied in roof-to-roof scenarios and are, therefore, relevant for near-future quantum networks.

Comparative Analysis of Feature Importance Algorithms for Grassland Aboveground Biomass and Nutrient Prediction Using Hyperspectral Data

Estimating forage yield and nutrient composition using hyperspectral remote sensing is a major challenge. However, there is still a lack of comprehensive research on the optimal wavelength for the analysis of various nutrients in pasture. In this research, conducted in Hailar District, Hulunber City, Inner Mongolia Autonomous Region, China, 126 sets of hyperspectral data were collected, covering a spectral range of 350 to 1800 nanometers. The primary objective was to identify key spectral bands for estimating forage dry matter yield (DMY), nitrogen content (NC), neutral detergent fiber (NDF), and acid detergent fiber (ADF) using principal component analysis (PCA), random forests (RF), and SHapley Additive exPlanations (SHAP) analysis methods, and then the RF and Extra-Trees algorithm (ERT) model was used to predict aboveground biomass (AGB) and nutrient parameters using the optimized spectral bands and vegetation indices. Our approach effectively minimizes redundancy in hyperspectral data by selectively employing crucial spectral bands, thus improving the accuracy of forage nutrient estimation. PCA identified the most variable bands at 400 nm, 520–550 nm, 670–720 nm, and 930–950 nm, reflecting their general spectral significance rather than a link to specific forage nutrients. Further analysis using RF feature importance pinpointed influential bands, predominantly within 930–940 nm and 700–730 nm. SHAP analysis confirmed critical bands for DMY (965 nm, 712 nm, and 1652 nm), NC (1390 nm and 713 nm), ADF (1390 nm and 715–725 nm), and NDF (400 nm, 983 nm, 1350 nm, and 1800 nm). The fitting accuracy for ADF estimated using RF was lower (R2 = 0.58), while the fitting accuracy for other indicators was higher (R2 ≥ 0.59). The performance and prediction accuracy of ERT (R2 = 0.63) were noticeably superior to those of RF. In conclusion, our method effectively identifies influential bands, optimizing forage yield and quality estimation.

Near-infrared spectral interval screening based on hierarchical variables clustering and group SCAD in multivariate calibration

Spectral interval screening is a critical step in multivariate calibration, which can improve the model predictive performance and data interpretation. In this study, a novel method for interval selection is proposed based on a hierarchical variables clustering and group smoothly clipped absolute deviation(group SCAD) in combination with partial least squares(VCG-PLS). The proposed method makes use of hierarchical variables clustering to yield a variables partitioning into groups at each level, and these groups of variables from different clustering levels are then used as input for group SCAD. The method is designed to select informative wavelength intervals for near-infrared(NIR) spectroscopic data analysis. The proposed method mainly consists of three steps. Firstly, an effective hierarchical clustering is employed to cluster wavelengths(variables), which generates a partition of variables into groups at each hierarchy level and obtains all possible wavelength intervals. Then, the series of group variables obtained from various hierarchy levels are given as input to group-SCAD, and group-SCAD can generate potential group variables corresponding to each regularization parameter value. Finally, a collection of PLS models is constructed recursively by employing all wavelength intervals except one, until the optimal wavelength intervals are obtained. The optimal intervals correspond to the lowest root mean square error of prediction. The VCG-PLS integrates the advantages of hierarchical variable clustering and group SCAD, which is an efficient technique to enhance the performance of PLS in interval selection. The performance of VCG-PLS was tested on three real NIR datasets. The results demonstrate that VCG-PLS can improve prediction performance with fewer variables and may be a good wavelength interval selection strategy.

Detection of different drinkable milk using photonic crystal fibre biosensor in IR regime

A simplified PCF sensor has been designed to detect the different drinkable milk that includes camel, cow and buffalo milk, and can also assess its quality. The sensor features a singular circular core design and two layers octagonal cladding air holes that was analysed using the Finite Element Method technique in COMSOL Multiphysics software and determine the sensing and optical performance parameters: power fraction, relative sensitivity, confinement loss, effective area, numerical aperture, V-Parameter, spot size, and beam divergence. At the optimum wavelength of 6.0 μm, the relative sensitivities are 96.58%, 96.78%, and 96.84%, and confinement losses of 3.51 × 10−8 dB/m, 1.47 × 10−8 dB m−1, and 8.59 × 10−9 dB/m, for camel, cow, and buffalo milk, respectively. The efficacy of the proposed PCF structure for sensing applications in the dairy industry in distinguishing between different types of milk is evidenced by these findings. Moreover, the results of confinement loss and chromatic dispersion suggest potential applications of this design in optical communication.

Modification of sensitive pyridine-pyrazolone method for determination of blood cyanide and its possible applications in fatal aircraft accidents

BackgroundFatal aviation accidents are a critical concern for armed forces, necessitating precise toxicological analysis of postmortem blood samples. This paper introduces a novel spectrophotometric method for quantifying cyanide in blood samples with an aim to aid in aircraft accident reconstruction in the future. MethodsBlood samples were collected from healthy non-smokers aged 20–45 years, excluding individuals with hepatic impairment, or those using drugs affecting blood cyanide levels. The spectrophotometric method involved cyanide adsorption in a sodium hydroxide solution using microdiffusion discs and chemical reactions resulting in a pinkish-purple end product. The optimal absorption wavelength (λmax) was determined, and the lower limits of detection and quantitation were established. The method underwent validation for precision, sensitivity, specificity, linearity, and accuracy. ResultsThe procedure yielded a pinkish-purple compound with an optimal absorption wavelength (λmax) of 531 nm. The established limits of detection (LoD) and quantitation (LoQ) were 0.0625 μg/ml and 0.125 μg/ml, respectively. The method demonstrated strong linearity up to cyanide concentrations of 4 μg/ml. It exhibited a sensitivity of 99.7% and accuracy of 85.92%. The intraday and inter-day precision were determined as 9.04% and 4.27%, respectively. The method was highly specific, showing no interference with blanks at the peak wavelength with a working range of 0.125–4 μg/ml. ConclusionThe study describes developing and validating a sensitive method for quantitatively estimating cyanide in blood samples. Incorporating this method into the existing postmortem toxicological sample collection and investigation protocol will enhance the analysis capabilities and improve aircraft accident investigation outcomes within the country.

Theoretical and experimental verification of wide-spectrum thermometry based on Taylor series de-integration method.

In response to the challenges encountered in solving the integral equations and the disadvantages of requiring additional calibration parameters in the existing three-channel wide-spectrum temperature measurement, a wavelength-based Taylor series de-integration method is proposed. By combining the coefficient of determination, which characterizes the approximation effect, the selection criterion of characteristic wavelength (optimal expansion wavelength, OEW) is constructed. In the influence analysis of spectral emissivity on the de-integration method, the insensitivity of OEW to spectral emissivity is revealed. The feasibility of using blackbody OEW for de-integration processing is proved when the spectral emissivity is unknown, which provides necessary theoretical support for the selection of characteristic wavelengths in practical application. Based on this integration method, algebraic temperature measurement equations in the forms of graybody, three-channel fusion, and two-color are derived, and the theoretical errors of each form are discussed from both horizontal and longitudinal perspectives. Furthermore, thermometry experiments with multiple acquisition parameters and diverse samples were conducted corresponding to three solution forms, the universality of acquisition parameters and sample applicability are proven.

Methods to maximize detector count rates on small-angle neutron scattering diffractometers at reactor sources: I. Optimizing wavelength selection

Methods to determine the optimal neutron wavelength to maximize detector count rates on small angle neutron scattering (SANS) diffractometers at reactor sources is presented. Three experimental methods are used to determine the choice of optimal wavelength and collimation combination that maximizes the detector count rate. The wavelength optimization methods are applied to two different SANS diffractometers at the NCNR, and all methods are found to confirm the optimal wavelength of approximately 9.5 Å ± 0.5 Å for optically thin samples. The optimum wavelength is shifted by the wavelength-dependence of the sample transmission to 8.5 Å ± 0.5 Å for thicker absorbing samples or 6.5 Å ± 0.5 Å if the amount of multiple scattering needs to be minimized to limit scattering curve distortions. The same optimization methods can be applied to SANS diffractometers at other reactor facilities.

Combination of spectral and textural features of hyperspectral imaging for the authentication of the diet supplied to fattening cattle

This study explored the potential of hyperspectral imaging in the near infrared region (NIR-HSI) as a non-destructive and rapid tool to discriminate among two beef fattening diets. For that purpose, a feeding trial was carried out with a total of 24 purebred Pirenaica calves. Twelve of them were fed barley and straw (BS) while 11 animals were finished on vegetable by-products (VBPR). When comparing the reference measurements of the meat coming from those animals, only the total collagen ratio expressed the feeding effect (p-value<0.05). To undertake the authentication procedure, two discrimination approaches were run: partial least squares discriminant analysis (PLS-DA) and radial basis function-support vector machine (RBF-SVM). To precisely extract spectral and textural information from the lean portion of the meat steaks, various techniques were executed, such as principal component (PC) images, competitive adaptive reweighted sampling (CARS) for selecting optimal wavelengths, and gray-level-co-occurrence matrix (GLCM). After hyperspectral imaging and the combination of their own texture features, samples were classified according to feeding diet with an overall accuracy of 72.92% for PLS-DA and 80.56% for RBF-SVM. So, the potential of using HSI technology to authenticate the meat obtained from beef supplied a diet based on circular economy techniques was made in evidence.

Porous hydrogel microspheres with excellent temperature-sensitive, magnetic and fluorescent properties for drug delivery.

Porous hydrogel microspheres with temperature-sensitive, magnetic and fluorescent properties have great potential for drug delivery. In this study, porous hydrogel microspheres with excellent temperature-sensitive, magnetic and fluorescent properties were prepared through droplet microfluidics and photoinitiated radical polymerization, which were characterized via scanning electron microscopy (SEM), vibrating sample magnetometry (VSM), fluorescence spectroscopy, ultraviolet spectrophotometry, and other techniques. The volumetric phase-transition temperature of porous hydrogel microspheres was in the range of 40-45 °C, and the volume swelling ratio reached 5.26 as the temperature decreased from 55 °C to 25 °C. Meanwhile, the saturation magnetization and optimal fluorescence emission wavelength of porous hydrogel microspheres were 1.79 emu g-1 and 616 nm, respectively, which can be an effective strategy to visually monitor and control the speed of drug release during magnetic heat therapy. Finally, bovine serum albumin (BSA) was employed as a model drug to investigate the drug loading and release of porous hydrogel microspheres. The maximal drug loading amount was 238 mg g-1, and the drug release speed and amount can be correspondingly promoted by altering the temperature.

Resonant Raman scattering on graphene: SERS and gap-mode TERS.

Nanoscale deformations and corrugations occur in graphene-like two-dimensional materials during their incorporation into hybrid structures and real devices, such as sensors based on surface-enhanced Raman scattering (SERS-based sensors). The structural features mentioned above are known to affect the electronic properties of graphene, thus highly sensitive and high-resolution techniques are required to reveal and characterize arising local defects, mechanical deformations, and phase transformations. In this study, we demonstrate that gap-mode tip-enhanced Raman Scattering (gm-TERS), which offers the benefits of structural and chemical analytical methods, allows variations in the structure and mechanical state of a two-dimensional material to be probed with nanoscale spatial resolution. In this work, we demonstrate locally enhanced gm-TERS on a monolayer graphene film placed on a plasmonic substrate with specific diameter gold nanodisks. SERS measurements are employed to determine the optimal disk diameter and excitation wavelength for further realization of gm-TERS. A significant local plasmonic enhancement of the main vibrational modes in graphene by a factor of 100 and a high spatial resolution of 10 nm are achieved in the gm-TERS experiment, making gm-TERS chemical mapping possible. By analyzing the gm-TERS spectra of the graphene film in the local area of a nanodisk, the local tensile mechanical strain in graphene was detected, resulting in a split of the G mode into two components, G+ and G-. Using the frequency split in the positions of G+ and G- modes in the TERS spectra, the stress was estimated to be up to 1.5%. The results demonstrate that gap-mode TERS mapping allows rapid and precise characterization of local structural defects in two-dimensional materials on the nanoscale.

Pedestal-cladding-pumped holmium fiber laser optimization using an analytical model

An analytical model of holmium-doped fiber laser is used to calculate optimal fiber length, pump wavelength and signal wavelength under in-band pumping conditions while considering fiber losses. The calculations show the advantages of a new type of pedestal-cladding-pumped fiber.

Pollution Monitoring: A Solution to Improve the Quality of Wastewater Treatment from Household Emissions

In the context of the growing environmental pressure on water resources caused by anthropogenic factors, the task of increasing the efficiency of wastewater treatment systems becomes urgent. The purpose of this work is to study and determine the optimal wavelength of the photoemitter for measuring the concentration of activated sludge by the optical method in biological wastewater treatment. The process of interaction of the emitted light with the measured medium is theoretically analyzed, the optical properties of the ultraviolet, visible, and near-infrared regions of the spectrum are considered. Based on these analyzes, an experimental study is carried out to find the optimal wavelength of the emitted light. To that end, under laboratory conditions, on the spectrophotometer model EMC-32PCS-UV, spectral measurements were performed on the absorption of emitted light by activated sludge microorganisms in the spectral range from 190 to 1100 nm wavelengths. Samples of activated sludge from the treatment plant in the city of Bukhara, Uzbekistan with different concentration values were utilized. When studying the absorption spectra of activated sludge microorganisms, it was experimentally established that the maximum absorption of light occurs in the infrared region of radiation, specifically at a wavelength of 940 nm. To select the optimal value of the radiation wavelength, the main criteria and requirements were theoretically determined. Based on these criteria, considering the scattering and absorption of light, the optical properties of the photodiodes used, it was concluded that the optimal value of the radiation wavelength is 940 nm. Using the results of the absorption spectra, the radiation wavelength was chosen. Graphical representations of the results of spectral studies with activated sludge microorganisms are given.

A review of quality assurance texture for highly pigmented iris recognition using an optimal wavelength band

The iris identification technology that is commercially available often uses segmentation to capture images of the eye within the 850-nm electromagnetic radiation spectrum. In this paper, the strongly pigmented iris image is taken with a camera at 12 different wavelengths, ranging from 420 to 940 nm. The goal is to identify the best wavelength band to expand the iris image wavelengths from 420 to 940 nm in NIR (near infrared) for the purpose of densely pigmented iris recognition. A system that obtains data, usually by digitizing analog channels and storing the data in digital form, is primarily anticipated for imaging the iris at narrow spectral bands in the range of 420–940 nm. This system takes pictures within particular wavelength ranges across the electromagnetic spectrum. Then, 200 human black iris that match the left and right eyes of 100 distinct people are obtained for the assessment. The most common wavelength for recognizing an iris with significant pigmentation is based on texture quality assurance, Equivalent Error Rate (EER), and False Rejection Rate (FRR) matching performance. The visual perception of heightened, detailed local iris texture information supports this effect.

Preclinical Study of Dual-Wavelength Light-Emitting Diode Therapy in an Osteoarthritis Rat Model.

To evaluate the efficacy of light-emitting diode (LED) and their dual-wavelengths as a treatment strategy for osteoarthritis. We induced osteoarthritis in male Sprague-Dawley rats by intra-articular injection of sodium iodoacetate into the right rear knee joint. The animals with lesions were divided into an untreated group and an LED-treated group (n=7 each). In the LED-treated group, the lesioned knee was irradiated with lasers (850 and 940 nm) and dose (3.15 J/cm2) for 20 minutes per session, twice a week for 4 weeks. Knee joint tissues were stained and scanned using an in vivo micro-computed tomography (CT) scanner. Serum interleukin (IL)-6 and IL-18 levels were determined using enzyme-linked immuno-sorbent assay. Several functional tests (lines crossed, rotational movement, rearing, and latency to remain rotating rod) were performed 24 hours before LED treatment and at 7, 14, 21, and 28 days after treatment. LED-treated rats showed improved locomotor function and suppressed matrix-degrading cytokines. Micro-CT images indicated that LED therapy had a preserving effect on cartilage and cortical bone. LED treatment using wavelengths of 850 and 940 nm resulted in significant functional, anatomical, and histologic improvements without adverse events in a rat model. Further research is required to determine the optimal wavelength, duration, and combination method, which will maximize treatment effectiveness.