This study innovatively employs functional near-infrared spectroscopy(fNIRS)technology to investigate passengers’brain responses to various external stimuli during high-speed train operations,assessing their impact o...This study innovatively employs functional near-infrared spectroscopy(fNIRS)technology to investigate passengers’brain responses to various external stimuli during high-speed train operations,assessing their impact on passenger comfort.Three stimuli are examined:passing through tunnels,sonic booms at tunnel exits,and two trains meeting within the tunnel.The analysis of environmental variables,including cabin noise,cabin-to-external pressure,and cabin-to-body acceleration,reveals that changes in auditory and pressure levels during the tunnel experience led to an 87%increase in oxygenated hemoglobin(HbO)levels in the temporal lobe(TL).This reflects a brief discomfort that subsides as passengers adapt,with HbO levels nearly returning to pre-tunnel levels upon exit.Among the stimuli,the sonic boom triggered the most significant neural response,with HbO fluctuations increased by 175%.In contrast,the impact of train meetings was minor,yielding an average HbO increase of only 14.21%.Connectivity analysis further shows significant enhancements in brain functional connectivity during tunnel entrance and sonic boom scenarios,with increases of 52%and 80%,respectively.Our findings contribute to passenger comfort assessment by establishing objective neurophysiological measures that quantify previously subjective experiences.The application of fNIRS in this dynamic environment creates new possibilities for evidence-based comfort optimization in railway design.展开更多
Background:Gossypol found in cottonseeds is toxic to human beings and monogastric animals and is a primary parameter for the integrated utilization of cottonseed products.It is usually determined by the techniques rel...Background:Gossypol found in cottonseeds is toxic to human beings and monogastric animals and is a primary parameter for the integrated utilization of cottonseed products.It is usually determined by the techniques relied on complex pretreatment procedures and the samples after determination cannot be used in the breeding program,so it is of great importance to predict the gossypol content in cottonseeds rapidly and nondestructively to substitute the traditional analytical method.Results:Gossypol content in cottonseeds was investigated by near-infrared spectroscopy(NIRS)and high-performance liquid chromatography(HPLC).Partial least squares regression,combined with spectral pretreatment methods including Savitzky-Golay smoothing,standard normal variate,multiplicative scatter correction,and first derivate were tested for optimizing the calibration models.NIRS technique was efficient in predicting gossypol content in intact cottonseeds,as revealed by the root-mean-square error of cross-validation(RMSECV),root-mean-square error of prediction(RMSEP),coefficient for determination of prediction(R_(p)^(2)),and residual predictive deviation(RPD)values for all models,being 0.05∼0.07,0.04∼0.06,0.82∼0.92,and 2.3∼3.4,respectively.The optimized model pretreated by Savitzky-Golay smoothing+standard normal variate+first derivate resulted in a good determination of gossypol content in intact cottonseeds.Conclusions:Near-infrared spectroscopy coupled with different spectral pretreatments and partial least squares(PLS)regression has exhibited the feasibility in predicting gossypol content in intact cottonseeds,rapidly and non destructively.It could be used as an alternative method to substitute for traditional one to determi ne the gossypol content in intact cottonseeds.展开更多
Noninvasive glucose detection is highly required for more convenient and less pain glycaemic monito-ring.Most of currently used methods are invasive.In this paper,a near-infrared reflectance spectroscopy(NIRS)is propo...Noninvasive glucose detection is highly required for more convenient and less pain glycaemic monito-ring.Most of currently used methods are invasive.In this paper,a near-infrared reflectance spectroscopy(NIRS)is proposed to detect blood glucose to protect patient absent of pain.NIRS is a safe,simple and effi-cient technology applied in many fields.Experiments,based on Oral Glucose Tolerance Test(OGTT),were conducted to collect data modeling with partial least squares(PLS)regression.42 samples of fingertip blood and palm were measured by commercially available blood glucose meter and NIRS separately at the same time.The glucose concentration range is between 5 and 12 mmol·L^-1.With leave-one-out cross-validation,we ob-tained a result of root mean square error of cross-validation(RMSECV)of 1.16 mmol·L^-1 for all the data.With the pre-processing methods of normalization and un-informative variables elimination reducing noise and eliminating some additional effects,we get a better result of 0.79 mmol·L^-1.A RMSECV of 0.41 mmol·L^-1 for individual modeling is much less than the total modeling.It has a broad application prospect in individ-ual customization.展开更多
Carbon dots(CDs)are fluorescent carbon-based nanomaterials with sizes smal-ler than 10 nm,that are renowned for their exceptional properties,including superior anti-photobleaching,excellent biocompatibility,and minima...Carbon dots(CDs)are fluorescent carbon-based nanomaterials with sizes smal-ler than 10 nm,that are renowned for their exceptional properties,including superior anti-photobleaching,excellent biocompatibility,and minimal toxicity,which have received sig-nificant interest.Near-infrared(NIR)light has emerged as an ideal light source in the biolo-gical field due to its advantages of minimal scattering and absorption,long wavelength emission,increased tissue penetration,and reduced interference from biological back-grounds.CDs with efficient absorption and/or emission characteristics in the NIR spectrum have shown remarkable promise in the biomedical uses.This study provides a comprehens-ive overview of the preparation methods and wavelength modulation strategies for near-in-frared CDs and reviews research progress in their use in the areas of biosensing,bioimaging,and therapy.It also discusses current challenges and clinical prospects,aimed at deepening our understanding of the subject and promoting further advances in this field.展开更多
A novel near-infrared all-fiber mode monitor based on a mini-two-path Mach-Zehnder interferometer(MTP-MZI)is proposed.The MTP-MZI mode monitor is created by fusing a section of(no-core fiber,NCF)and a(single-mode fibe...A novel near-infrared all-fiber mode monitor based on a mini-two-path Mach-Zehnder interferometer(MTP-MZI)is proposed.The MTP-MZI mode monitor is created by fusing a section of(no-core fiber,NCF)and a(single-mode fiber,SMF)together with an optical fiber fusion splicer,establishing two distinct centimeter-level optical transmission paths.Since the high-order modes in NCF transmit near-infrared light more sensitively to curvature-induced energy leakage than the fundamental mode in SMF,the near-infrared high-order mode light leaks out of NCF when the curvature changes,causing the MTP-MZI transmission spectrum to change.By ana⁃lyzing the relationship between the curvature,transmission spectrum,and spatial frequency spectrum,the modes involved in the interference can be studied,thereby revealing the mode transmission characteristics of near-infra⁃red light in optical fibers.In the verification experiments,higher-order modes were excited by inserting a novel hollow-core fiber(HCF)into the MTP-MZI.When the curvature of the MTP-MZI changes,the near-infrared light high-order mode introduced into the device leaks out,causing the transmission spectrum to return to its origi⁃nal state before bending and before the HCF was spliced.The experimental results demonstrate that the MTP-MZI mode monitor can monitor the fiber modes introduced from the external environment,providing both theoretical and experimental foundations for near-infrared all-fiber mode monitoring in optical information systems.展开更多
Tin-lead(Sn-Pb)mixed perovskites are extensively investigated in near-infrared(NIR)photodetectors(PDs)owing to their excellent photoelectric performance.However,achieving high-performance Sn-Pb mixed PDs remains chall...Tin-lead(Sn-Pb)mixed perovskites are extensively investigated in near-infrared(NIR)photodetectors(PDs)owing to their excellent photoelectric performance.However,achieving high-performance Sn-Pb mixed PDs remains challenging,primarily because of the rapid crystallization and the susceptibility of Sn^(2+) to oxidation.To ad⁃dress these issues,this study introduces the multifunctional molecules 2,3-difluorobenzenamine(DBM)to modulate the crystallization of Sn-Pb mixed perovskites and retard the oxidation of Sn^(2+),thereby significantly enhancing film quality.Compared with the pristine film,Sn-Pb mixed perovskite films modulated by DBM molecules exhibit a high⁃ly homogeneous morphology,reduced roughness and defect density.The self-powered NIR PDs fabricated with the improved films have a spectral response range from 300 nm to 1100 nm,a peak responsivity of 0.51 A·W^(-1),a spe⁃cific detectivity as high as 2.46×10^(11)Jones within the NIR region(780 nm to 1100 nm),a linear dynamic range ex⁃ceeding 152 dB,and ultrafast rise/fall time of 123/464 ns.Thanks to the outstanding performance of PDs,the fabri⁃cated 5×5 PDs array demonstrates superior imaging ability in the NIR region up to 980 nm.This work advances the development of Sn-Pb mixed perovskites for NIR detection and paves the way for their commercialization.展开更多
Broadband near-infrared(NIR)luminescent materials have shown great promise in applications such as optical communication,biomedicine,and optoelectronic devices.However,the current research is focused on phos⁃phors and...Broadband near-infrared(NIR)luminescent materials have shown great promise in applications such as optical communication,biomedicine,and optoelectronic devices.However,the current research is focused on phos⁃phors and glasses,and it is important to develop broadband NIR luminescent nanomaterials.Here,we report an erbi⁃um-sensitized core-shell nanocrystal design for broadband NIR emission.Based on the structural design with suitable dopings of Tm^(3+)and Ho^(3+),the broadband NIR emission covering 1.5-2.1μm region is achieved under 980 nm and 808 nm excitations.Moreover,the emission intensity is further enhanced by introducing Yb^(3+)and Nd^(3+)into the sam⁃ple,respectively,and the energy transfer processes between them are systematically discussed.Our results present a novel approach for developing broadband NIR luminescent materials and devices.展开更多
Doping perylene diimide(PDI)into a polymer matrix is a simple strategy to prepare near-infrared(NIR)reflective materials,but the mechanical properties and NIR reflectance properties are significantly compromised due t...Doping perylene diimide(PDI)into a polymer matrix is a simple strategy to prepare near-infrared(NIR)reflective materials,but the mechanical properties and NIR reflectance properties are significantly compromised due to macro-phase separation.In this study,a novel polymer(denoted as PU-PDI)with intrinsic NIR reflective proper⁃ties was synthesized by covalent incorporation of PDI units into polyurethane chains.Its photophysical characteris⁃tics,mechanical property and NIR reflectance property are investigated in detail.The results show that covalent in⁃corporation reduces the severe aggregation of PDI units,thereby endows PU-PDI with excellent mechanical property.The elongation at break of PU-PDI can reach more than 700%,and the breaking strength is 34.11 MPa.Moreover,compared to the blending system,PU-PDI possesses enhanced NIR reflection ability due to the better dispersion of PDI units.展开更多
Organic semiconductor materials have shown unique advantages in the development of optoelectronic devices due to their ease of preparation,low cost,lightweight,and flexibility.In this work,we explored the application ...Organic semiconductor materials have shown unique advantages in the development of optoelectronic devices due to their ease of preparation,low cost,lightweight,and flexibility.In this work,we explored the application of the organic semiconductor Y6-1O single crystal in photodetection devices.Firstly,Y6-1O single crystal material was prepared on a silicon substrate using solution droplet casting method.The optical properties of Y6-1O material were characterized by polarized optical microscopy,fluorescence spectroscopy,etc.,confirming its highly single crystalline performance and emission properties in the near-infrared region.Phototransistors based on Y6-1O materials with different thicknesses were then fabricated and tested.It was found that the devices exhibited good visible to near-infrared photoresponse,with the maximum photoresponse in the near-infrared region at 785 nm.The photocurrent on/off ratio reaches 10^(2),and photoresponsivity reaches 16 mA/W.It was also found that the spectral response of the device could be regulated by gate voltage as well as the material thickness,providing important conditions for optimizing the performance of near-infrared photodetectors.This study not only demonstrates the excellent performance of organic phototransistors based on Y6-1O single crystal material in near-infrared detection but also provides new ideas and directions for the future development of infrared detectors.展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
Exploring cost-effective and efficient catalysts for oxygen reduction reaction(ORR)poses a significant challenge,espe-cially in the pursuit of alternatives to precious metals like platinum.Significant advancements hav...Exploring cost-effective and efficient catalysts for oxygen reduction reaction(ORR)poses a significant challenge,espe-cially in the pursuit of alternatives to precious metals like platinum.Significant advancements have driven electrochem-ists to develop efficient ORR catalysts using abundant materials,particularly iron(Fe)-based,known for their exceptional performance in ORR.While the crucial function of Fe in boosting ORR catalytic activity is recognized,the connection between material attributes and catalytic performance remains enigmatic.Understanding the dynamic processes involved in oxygen electrocatalysis is paramount for designing precious-metals-free ORR electrocatalysts.Mössbauer spectroscopy stands out as a powerful technique for deciphering the structural characteristics of Fe species in catalysis,facilitating the identification of active sites and the clarification of catalytic mechanisms.By showcasing noteworthy case studies within this review,we demonstrate the application of in-situ/operando 57Fe Mössbauer spectroscopy across diverse Fe-involved materials in ORR catalysis.This sheds light on various aspects of ORR catalysis,such as identifying active sites,assessing stability,and understanding the reaction mechanism.Our inquiry drives towards the opportunities and hurdles associ-ated with Mössbauer spectroscopy,unveiling potential breakthroughs and avenues for enhancement within this pivotal research realm.展开更多
In the near-infrared(NIR)spectroscopic data of complex sample systems,such as tobacco leaves,nonlinearity is fairly significant between the absorbance and concentration.This nonlinearity severely degrades the quantita...In the near-infrared(NIR)spectroscopic data of complex sample systems,such as tobacco leaves,nonlinearity is fairly significant between the absorbance and concentration.This nonlinearity severely degrades the quantitative results of traditional methods,such as partial least squares regression(PLS),which can be used to construct linear models.The problem was addressed in this study by using deep learning(DL).We employed three different DL models:a one-dimensional convolutional neural network(1D CNN),a deep neural network(DNN),and a stacked autoencoder with feedforward neural networks(SAE-FNNs).By carefully selecting and tuning the architectures and parameters of these models,we were able to find the most suitable model for dealing with such nonlinear relationships.Our experimental findings reveal that both the DNN and the SAE-FNN models excel in addressing the nonlinear issues of pectin concentration in tobacco,surpassing the performance of the classic linear model(PLS).Specifically,the DNN model stands out for its low average root mean squared error of prediction(RMSEP)value and small standard deviation(SD)of RMSEPs,leading to a tighter and more centered distribution of residuals in the prediction set.These DL models not only proficiently identify complex patterns within NIR data but also boast high prediction accuracy and fast implementation,demonstrating their effectiveness in analytical applications.展开更多
This review paper reports near-infrared(NIR)imaging studies using a newly-developed NIR camera,Compovision.Compovision can measure a significantly wide area of 150mm×250mm at high speed of between 2and 5s.It enab...This review paper reports near-infrared(NIR)imaging studies using a newly-developed NIR camera,Compovision.Compovision can measure a significantly wide area of 150mm×250mm at high speed of between 2and 5s.It enables a wide spectral region measurement in the 1 000~2 350nm range at 6nm intervals.We investigated the potential of Compovision in the applications to industrial problems such as the evaluation of pharmaceutical tablets and polymers.Our studies have demonstrated that NIR imaging based on Compovision can solve several issues such as long acquisition times and relatively low sensitivity of detection.NIR imaging with Compovision is strongly expected to be applied not only to pharmaceutical tablet monitoring and polymer characterization but also to various applications such as those to food products,biomedical substances and organic and inorganic materials.展开更多
Background:Manga nese(Mn)is an essential microelement in cotton seeds,which is usually determined by the techniques relied on hazardous reagents and complex pretreatment procedures.Therefore a rapid,low-cost,and reage...Background:Manga nese(Mn)is an essential microelement in cotton seeds,which is usually determined by the techniques relied on hazardous reagents and complex pretreatment procedures.Therefore a rapid,low-cost,and reagent-free analytical way is demanded to substitute the traditional analytical method.Results:The Mn content in cottonseed meal was investigated by near-infrared spectroscopy(NIRS)and chemometrics techniques.Standard normal variate(SNV)combined with first derivatives(FD)was the optimal spectra pre-treatment method.Monte Carlo uninformative variable elimination(MCUVE)and successive projections algorithm method(SPA)were employed to extract the informative variables from the full NIR spectra.The lin ear and non linear calibration models for cott on seed Mn content were developed.Finally,the optimal model for cottonseed Mn content was obtained by MCUVE-SPA-LSSVM,with root mean squares error of prediction(RMSEP)of 1.994 6,coefficient of determination(R^2)of 0.949 3,and the residual predictive deviation(RPD)of 4.370 5,respectively.Conclusions:The MCUVE-SPA-LSSVM model is accuracy enough to measure the Mn content in cottonseed meal,which can be used as an alter native way to substitute for traditional analytical method.展开更多
Dual-comb spectroscopy(DCS)is one of the most promising technologies for ultra-long open-path multiplegreenhouse gas detection.Ultra-long open-path DCS has the potential to realize horizontal open-path links over hund...Dual-comb spectroscopy(DCS)is one of the most promising technologies for ultra-long open-path multiplegreenhouse gas detection.Ultra-long open-path DCS has the potential to realize horizontal open-path links over hundredsof kilometers and vertical open-path links between satellites and the ground base.Under these extreme detection conditions,identifying an appropriate wavelength band that ensures both technical feasibility and a reasonable absorbance fortarget components is critical but currently lacks studies.In this work,we simulate transmission spectra under different detectionconfigurations to identify optimal wavelength bands for carbon dioxide(CO_(2))and methane(CH_(4))measurement.The simulation results show that the 1540 nm Watt-level high-power frequency combs developed are suitable for CO_(2)measurement in both horizontal and vertical ultra-long detection configurations.The results also suggest that developinghigh-power fiber amplifiers for 1630 nm and 1636 nm will facilitate CH_(4)measurement in horizontal and vertical ultra-longdetection configurations,respectively.The amplification at 1636 nm will be a future research focus,as it is expected to enablesimultaneous measurements of CH_(4),CO_(2),and water vapor in the vertical detection configuration.展开更多
In sub nanometer carbon nanotubes,water exhibits unique dynamic characteristics,and in the high-frequency region of the infrared spectrum,where the stretching vibrations of the internal oxygen-hydrogen(O-H)bonds are c...In sub nanometer carbon nanotubes,water exhibits unique dynamic characteristics,and in the high-frequency region of the infrared spectrum,where the stretching vibrations of the internal oxygen-hydrogen(O-H)bonds are closely related to the hydrogen bonds(H-bonds)network between water molecules.Therefore,it is crucial to analyze the relationship between these two aspects.In this paper,the infrared spectrum and motion characteristics of the stretching vibrations of the O-H bonds in one-dimensional confined water(1DCW)and bulk water(BW)in(6,6)single-walled carbon nanotubes(SWNT)are studied by molecular dynamics simulations.The results show that the stretching vibrations of the two O-H bonds in 1DCW exhibit different frequencies in the infrared spectrum,while the O-H bonds in BW display two identical main frequency peaks.Further analysis using the spring oscillator model reveals that the difference in the stretching amplitude of the O-H bonds is the main factor causing the change in vibration frequency,where an increase in stretching amplitude leads to a decrease in spring stiffness and,consequently,a lower vibration frequency.A more in-depth study found that the interaction of H-bonds between water molecules is the fundamental cause of the increased stretching amplitude and decreased vibration frequency of the O-H bonds.Finally,by analyzing the motion trajectory of the H atoms,the dynamic differences between 1DCW and BW are clearly revealed.These findings provide a new perspective for understanding the behavior of water molecules at the nanoscale and are of significant importance in advancing the development of infrared spectroscopy detection technology.展开更多
Although there are numerous optical spectroscopy techniques and methods that have been used to extract the fundamental bandgap of a semiconductor,most of them belong to one of these three approaches:(1)the excitonic a...Although there are numerous optical spectroscopy techniques and methods that have been used to extract the fundamental bandgap of a semiconductor,most of them belong to one of these three approaches:(1)the excitonic absorption,(2)modulation spectroscopy,and(3)the most widely used Tauc-plot.The excitonic absorption is based on a many-particle theory,which is physically the most correct approach,but requires more stringent crystalline quality and appropriate sample preparation and experimental implementation.The Tauc-plot is based on a single-particle theo⁃ry that neglects the many-electron effects.Modulation spectroscopy analyzes the spectroscopy features in the derivative spectrum,typically,of the reflectance and transmission under an external perturbation.Empirically,the bandgap ener⁃gy derived from the three approaches follow the order of E_(ex)>E_(MS)>E_(TP),where three transition energies are from exci⁃tonic absorption,modulation spectroscopy,and Tauc-plot,respectively.In principle,defining E_(g) as the single-elec⁃tron bandgap,we expect E_(g)>E_(ex),thus,E_(g)>E_(TP).In the literature,E_(TP) is often interpreted as E_(g),which is conceptual⁃ly problematic.However,in many cases,because the excitonic peaks are not readily identifiable,the inconsistency be⁃tween E_(g) and E_(TP) becomes invisible.In this brief review,real world examples are used(1)to illustrate how excitonic absorption features depend sensitively on the sample and measurement conditions;(2)to demonstrate the differences between E_(ex),E_(MS),and E_(TP) when they can be extracted simultaneously for one sample;and(3)to show how the popular⁃ly adopted Tauc-plot could lead to misleading results.Finally,it is pointed out that if the excitonic absorption is not ob⁃servable,the modulation spectroscopy can often yield a more useful and reasonable bandgap than Tauc-plot.展开更多
To address the issues of peak overlap caused by complex matrices in agricultural product terahertz(THz)spectral signals and the dynamic,nonlinear interference induced by environmental and system noise,this study explo...To address the issues of peak overlap caused by complex matrices in agricultural product terahertz(THz)spectral signals and the dynamic,nonlinear interference induced by environmental and system noise,this study explores the feasibility of adaptive-signal-decomposition-based denoising methods to improve THz spectral quality.THz time-domain spectroscopy(THz-TDS)combined with an attenuated total reflection(ATR)accessory was used to collect THz absorbance spectra from 48 peanut samples.Taking the quantitative prediction model of peanut moisture content based on THz-ATR as an example,wavelet transform(WT),empirical mode decomposition(EMD),local mean decomposition(LMD),and its improved methods-segmented local mean decomposition(SLMD)and piecewise mirror extension local mean decomposition(PME-LMD)-were employed for spectral denoising.The applicability of different denoising methods was evaluated using a support vector regression(SVR)model.Experimental results show that the peanut moisture content prediction model constructed after PME-LMD denoising achieved the best performance,with a root mean square error(RMSE),coefficient of determination(R^(2)),and mean absolute percentage error(MAPE)of 0.010,0.912,and 0.040,respectively.Compared with traditional methods,PME-LMD significantly improved spectral quality and model prediction performance.The PME-LMD denoising strategy proposed in this study effectively suppresses non-uniform noise interference in THz spectral signals,providing an efficient and accurate preprocessing method for THz spectral analysis of agricultural products.This research provides theoretical support and technical guidance for the application of THz technology for detecting agricultural product quality.展开更多
3-Nitro-1,2,4-triazol-5-one(NTO)is a typical high-energy,low-sensitivity explosive,and accurate concentration monitoring is critical for crystallization process control.In this study,a high-precision quantitative anal...3-Nitro-1,2,4-triazol-5-one(NTO)is a typical high-energy,low-sensitivity explosive,and accurate concentration monitoring is critical for crystallization process control.In this study,a high-precision quantitative analytical model for NTO concentration in ethanol solutions was developed by integrating real-time ATR-FTIR spectroscopy with chemometric and machine learning techniques.Dynamic spectral data were obtained by designing multi-concentration gradient heating-cooling cycle experiments,abnormal samples were eliminated using the isolation forest algorithm,and the effects of various preprocessing methods on model performance were systematically evaluated.The results show that partial least squares regression(PLSR)exhibits superior generalization ability compared to other models.Vibrational bands corresponding to C=O and–NO_(2)were identified as key predictors for concentration estimation.This work provides an efficient and reliable solution for real-time concentration monitoring during NTO crystallization and holds significant potential for process analytical applications in energetic material manufacturing.展开更多
基金Project(52202426)supported by the National Natural Science Foundation of ChinaProjects(15205723,15226424)supported by the Research Grants Council(RGC)of the Hong Kong Special Administrative Region,ChinaProject(KBBY1)supported by the Innovation and Technology Commission of the Hong Kong Special Administrative Region。
文摘This study innovatively employs functional near-infrared spectroscopy(fNIRS)technology to investigate passengers’brain responses to various external stimuli during high-speed train operations,assessing their impact on passenger comfort.Three stimuli are examined:passing through tunnels,sonic booms at tunnel exits,and two trains meeting within the tunnel.The analysis of environmental variables,including cabin noise,cabin-to-external pressure,and cabin-to-body acceleration,reveals that changes in auditory and pressure levels during the tunnel experience led to an 87%increase in oxygenated hemoglobin(HbO)levels in the temporal lobe(TL).This reflects a brief discomfort that subsides as passengers adapt,with HbO levels nearly returning to pre-tunnel levels upon exit.Among the stimuli,the sonic boom triggered the most significant neural response,with HbO fluctuations increased by 175%.In contrast,the impact of train meetings was minor,yielding an average HbO increase of only 14.21%.Connectivity analysis further shows significant enhancements in brain functional connectivity during tunnel entrance and sonic boom scenarios,with increases of 52%and 80%,respectively.Our findings contribute to passenger comfort assessment by establishing objective neurophysiological measures that quantify previously subjective experiences.The application of fNIRS in this dynamic environment creates new possibilities for evidence-based comfort optimization in railway design.
基金The research work was funded by The National Key Technology R&D Program of China(2016YFD0101404)China Agriculture Research System(CARS-18-25)Jiangsu Collaborative Innovation Center for Modern Crop Production.
文摘Background:Gossypol found in cottonseeds is toxic to human beings and monogastric animals and is a primary parameter for the integrated utilization of cottonseed products.It is usually determined by the techniques relied on complex pretreatment procedures and the samples after determination cannot be used in the breeding program,so it is of great importance to predict the gossypol content in cottonseeds rapidly and nondestructively to substitute the traditional analytical method.Results:Gossypol content in cottonseeds was investigated by near-infrared spectroscopy(NIRS)and high-performance liquid chromatography(HPLC).Partial least squares regression,combined with spectral pretreatment methods including Savitzky-Golay smoothing,standard normal variate,multiplicative scatter correction,and first derivate were tested for optimizing the calibration models.NIRS technique was efficient in predicting gossypol content in intact cottonseeds,as revealed by the root-mean-square error of cross-validation(RMSECV),root-mean-square error of prediction(RMSEP),coefficient for determination of prediction(R_(p)^(2)),and residual predictive deviation(RPD)values for all models,being 0.05∼0.07,0.04∼0.06,0.82∼0.92,and 2.3∼3.4,respectively.The optimized model pretreated by Savitzky-Golay smoothing+standard normal variate+first derivate resulted in a good determination of gossypol content in intact cottonseeds.Conclusions:Near-infrared spectroscopy coupled with different spectral pretreatments and partial least squares(PLS)regression has exhibited the feasibility in predicting gossypol content in intact cottonseeds,rapidly and non destructively.It could be used as an alternative method to substitute for traditional one to determi ne the gossypol content in intact cottonseeds.
基金the National High Technology Research and Development Program of China(2013AA041201)Zhejiang Province Scientific and Technological Project(2015C37062)
文摘Noninvasive glucose detection is highly required for more convenient and less pain glycaemic monito-ring.Most of currently used methods are invasive.In this paper,a near-infrared reflectance spectroscopy(NIRS)is proposed to detect blood glucose to protect patient absent of pain.NIRS is a safe,simple and effi-cient technology applied in many fields.Experiments,based on Oral Glucose Tolerance Test(OGTT),were conducted to collect data modeling with partial least squares(PLS)regression.42 samples of fingertip blood and palm were measured by commercially available blood glucose meter and NIRS separately at the same time.The glucose concentration range is between 5 and 12 mmol·L^-1.With leave-one-out cross-validation,we ob-tained a result of root mean square error of cross-validation(RMSECV)of 1.16 mmol·L^-1 for all the data.With the pre-processing methods of normalization and un-informative variables elimination reducing noise and eliminating some additional effects,we get a better result of 0.79 mmol·L^-1.A RMSECV of 0.41 mmol·L^-1 for individual modeling is much less than the total modeling.It has a broad application prospect in individ-ual customization.
基金financial support by Talent Introduction Research Initiation Fund of Shanxi Bethune Hospital(2022RC04)Basic Research Program Youth Science Research Project of Shanxi province(202203021212096)+1 种基金Shanxi Province Clinical Theranostics Technology Innovation Center for Immunologic and Rheumatic Diseases(CXZX-202302)Research Project Plan of Shanxi Provincial Administration of Traditional Chinese Medicine(2023ZYYB2021)。
文摘Carbon dots(CDs)are fluorescent carbon-based nanomaterials with sizes smal-ler than 10 nm,that are renowned for their exceptional properties,including superior anti-photobleaching,excellent biocompatibility,and minimal toxicity,which have received sig-nificant interest.Near-infrared(NIR)light has emerged as an ideal light source in the biolo-gical field due to its advantages of minimal scattering and absorption,long wavelength emission,increased tissue penetration,and reduced interference from biological back-grounds.CDs with efficient absorption and/or emission characteristics in the NIR spectrum have shown remarkable promise in the biomedical uses.This study provides a comprehens-ive overview of the preparation methods and wavelength modulation strategies for near-in-frared CDs and reviews research progress in their use in the areas of biosensing,bioimaging,and therapy.It also discusses current challenges and clinical prospects,aimed at deepening our understanding of the subject and promoting further advances in this field.
基金Supported by the Central Government Guidance on Local Science and Technology Development Funds(2023ZY1023)the Six Talent Peaks Project in Jiangsu Province(KTHY-052).
文摘A novel near-infrared all-fiber mode monitor based on a mini-two-path Mach-Zehnder interferometer(MTP-MZI)is proposed.The MTP-MZI mode monitor is created by fusing a section of(no-core fiber,NCF)and a(single-mode fiber,SMF)together with an optical fiber fusion splicer,establishing two distinct centimeter-level optical transmission paths.Since the high-order modes in NCF transmit near-infrared light more sensitively to curvature-induced energy leakage than the fundamental mode in SMF,the near-infrared high-order mode light leaks out of NCF when the curvature changes,causing the MTP-MZI transmission spectrum to change.By ana⁃lyzing the relationship between the curvature,transmission spectrum,and spatial frequency spectrum,the modes involved in the interference can be studied,thereby revealing the mode transmission characteristics of near-infra⁃red light in optical fibers.In the verification experiments,higher-order modes were excited by inserting a novel hollow-core fiber(HCF)into the MTP-MZI.When the curvature of the MTP-MZI changes,the near-infrared light high-order mode introduced into the device leaks out,causing the transmission spectrum to return to its origi⁃nal state before bending and before the HCF was spliced.The experimental results demonstrate that the MTP-MZI mode monitor can monitor the fiber modes introduced from the external environment,providing both theoretical and experimental foundations for near-infrared all-fiber mode monitoring in optical information systems.
基金Supported by National Key Research and Development Program of China(2022YFA1404201)National Natural Science Foundation of China(62205187,U23A20380,U22A2091,62222509,62127817,62075120)+3 种基金Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China(IRT_17R70)Fundamental Research Program of Shanxi Province(202103021223032,202303021222031)Project Funded by China Postdoctoral Science Foundation(2022M722006)Fund for Shanxi“1331 Project”Key Subjects Construction。
文摘Tin-lead(Sn-Pb)mixed perovskites are extensively investigated in near-infrared(NIR)photodetectors(PDs)owing to their excellent photoelectric performance.However,achieving high-performance Sn-Pb mixed PDs remains challenging,primarily because of the rapid crystallization and the susceptibility of Sn^(2+) to oxidation.To ad⁃dress these issues,this study introduces the multifunctional molecules 2,3-difluorobenzenamine(DBM)to modulate the crystallization of Sn-Pb mixed perovskites and retard the oxidation of Sn^(2+),thereby significantly enhancing film quality.Compared with the pristine film,Sn-Pb mixed perovskite films modulated by DBM molecules exhibit a high⁃ly homogeneous morphology,reduced roughness and defect density.The self-powered NIR PDs fabricated with the improved films have a spectral response range from 300 nm to 1100 nm,a peak responsivity of 0.51 A·W^(-1),a spe⁃cific detectivity as high as 2.46×10^(11)Jones within the NIR region(780 nm to 1100 nm),a linear dynamic range ex⁃ceeding 152 dB,and ultrafast rise/fall time of 123/464 ns.Thanks to the outstanding performance of PDs,the fabri⁃cated 5×5 PDs array demonstrates superior imaging ability in the NIR region up to 980 nm.This work advances the development of Sn-Pb mixed perovskites for NIR detection and paves the way for their commercialization.
文摘Broadband near-infrared(NIR)luminescent materials have shown great promise in applications such as optical communication,biomedicine,and optoelectronic devices.However,the current research is focused on phos⁃phors and glasses,and it is important to develop broadband NIR luminescent nanomaterials.Here,we report an erbi⁃um-sensitized core-shell nanocrystal design for broadband NIR emission.Based on the structural design with suitable dopings of Tm^(3+)and Ho^(3+),the broadband NIR emission covering 1.5-2.1μm region is achieved under 980 nm and 808 nm excitations.Moreover,the emission intensity is further enhanced by introducing Yb^(3+)and Nd^(3+)into the sam⁃ple,respectively,and the energy transfer processes between them are systematically discussed.Our results present a novel approach for developing broadband NIR luminescent materials and devices.
文摘Doping perylene diimide(PDI)into a polymer matrix is a simple strategy to prepare near-infrared(NIR)reflective materials,but the mechanical properties and NIR reflectance properties are significantly compromised due to macro-phase separation.In this study,a novel polymer(denoted as PU-PDI)with intrinsic NIR reflective proper⁃ties was synthesized by covalent incorporation of PDI units into polyurethane chains.Its photophysical characteris⁃tics,mechanical property and NIR reflectance property are investigated in detail.The results show that covalent in⁃corporation reduces the severe aggregation of PDI units,thereby endows PU-PDI with excellent mechanical property.The elongation at break of PU-PDI can reach more than 700%,and the breaking strength is 34.11 MPa.Moreover,compared to the blending system,PU-PDI possesses enhanced NIR reflection ability due to the better dispersion of PDI units.
基金Supported by the National Key Research and Development Program of China(2021YFB2012601)National Natural Science Foundation of China(12204109)+1 种基金Science and Technology Innovation Plan of Shanghai Science and Technology Commission(21JC1400200)Higher Education Indus⁃try Support Program of Gansu Province(2022CYZC-06)。
文摘Organic semiconductor materials have shown unique advantages in the development of optoelectronic devices due to their ease of preparation,low cost,lightweight,and flexibility.In this work,we explored the application of the organic semiconductor Y6-1O single crystal in photodetection devices.Firstly,Y6-1O single crystal material was prepared on a silicon substrate using solution droplet casting method.The optical properties of Y6-1O material were characterized by polarized optical microscopy,fluorescence spectroscopy,etc.,confirming its highly single crystalline performance and emission properties in the near-infrared region.Phototransistors based on Y6-1O materials with different thicknesses were then fabricated and tested.It was found that the devices exhibited good visible to near-infrared photoresponse,with the maximum photoresponse in the near-infrared region at 785 nm.The photocurrent on/off ratio reaches 10^(2),and photoresponsivity reaches 16 mA/W.It was also found that the spectral response of the device could be regulated by gate voltage as well as the material thickness,providing important conditions for optimizing the performance of near-infrared photodetectors.This study not only demonstrates the excellent performance of organic phototransistors based on Y6-1O single crystal material in near-infrared detection but also provides new ideas and directions for the future development of infrared detectors.
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
基金financially supported by the National Natural Science Foundation of China (22350410386,W2412116,22375200,U22A202175,21961142006)。
文摘Exploring cost-effective and efficient catalysts for oxygen reduction reaction(ORR)poses a significant challenge,espe-cially in the pursuit of alternatives to precious metals like platinum.Significant advancements have driven electrochem-ists to develop efficient ORR catalysts using abundant materials,particularly iron(Fe)-based,known for their exceptional performance in ORR.While the crucial function of Fe in boosting ORR catalytic activity is recognized,the connection between material attributes and catalytic performance remains enigmatic.Understanding the dynamic processes involved in oxygen electrocatalysis is paramount for designing precious-metals-free ORR electrocatalysts.Mössbauer spectroscopy stands out as a powerful technique for deciphering the structural characteristics of Fe species in catalysis,facilitating the identification of active sites and the clarification of catalytic mechanisms.By showcasing noteworthy case studies within this review,we demonstrate the application of in-situ/operando 57Fe Mössbauer spectroscopy across diverse Fe-involved materials in ORR catalysis.This sheds light on various aspects of ORR catalysis,such as identifying active sites,assessing stability,and understanding the reaction mechanism.Our inquiry drives towards the opportunities and hurdles associ-ated with Mössbauer spectroscopy,unveiling potential breakthroughs and avenues for enhancement within this pivotal research realm.
基金supported by a joint project with SINOPEC(Dalian)Research Institute of Petroleum and Petrochemicals Co.,Ltd.(Contract No.323061).
文摘In the near-infrared(NIR)spectroscopic data of complex sample systems,such as tobacco leaves,nonlinearity is fairly significant between the absorbance and concentration.This nonlinearity severely degrades the quantitative results of traditional methods,such as partial least squares regression(PLS),which can be used to construct linear models.The problem was addressed in this study by using deep learning(DL).We employed three different DL models:a one-dimensional convolutional neural network(1D CNN),a deep neural network(DNN),and a stacked autoencoder with feedforward neural networks(SAE-FNNs).By carefully selecting and tuning the architectures and parameters of these models,we were able to find the most suitable model for dealing with such nonlinear relationships.Our experimental findings reveal that both the DNN and the SAE-FNN models excel in addressing the nonlinear issues of pectin concentration in tobacco,surpassing the performance of the classic linear model(PLS).Specifically,the DNN model stands out for its low average root mean squared error of prediction(RMSEP)value and small standard deviation(SD)of RMSEPs,leading to a tighter and more centered distribution of residuals in the prediction set.These DL models not only proficiently identify complex patterns within NIR data but also boast high prediction accuracy and fast implementation,demonstrating their effectiveness in analytical applications.
文摘This review paper reports near-infrared(NIR)imaging studies using a newly-developed NIR camera,Compovision.Compovision can measure a significantly wide area of 150mm×250mm at high speed of between 2and 5s.It enables a wide spectral region measurement in the 1 000~2 350nm range at 6nm intervals.We investigated the potential of Compovision in the applications to industrial problems such as the evaluation of pharmaceutical tablets and polymers.Our studies have demonstrated that NIR imaging based on Compovision can solve several issues such as long acquisition times and relatively low sensitivity of detection.NIR imaging with Compovision is strongly expected to be applied not only to pharmaceutical tablet monitoring and polymer characterization but also to various applications such as those to food products,biomedical substances and organic and inorganic materials.
基金funded by The National Key Technology R&D program of China(2016YFD0101404)China Agriculture Research System(CARS-18-25)Jiangsu Collaborative Innovation Center for Modern Crop Production
文摘Background:Manga nese(Mn)is an essential microelement in cotton seeds,which is usually determined by the techniques relied on hazardous reagents and complex pretreatment procedures.Therefore a rapid,low-cost,and reagent-free analytical way is demanded to substitute the traditional analytical method.Results:The Mn content in cottonseed meal was investigated by near-infrared spectroscopy(NIRS)and chemometrics techniques.Standard normal variate(SNV)combined with first derivatives(FD)was the optimal spectra pre-treatment method.Monte Carlo uninformative variable elimination(MCUVE)and successive projections algorithm method(SPA)were employed to extract the informative variables from the full NIR spectra.The lin ear and non linear calibration models for cott on seed Mn content were developed.Finally,the optimal model for cottonseed Mn content was obtained by MCUVE-SPA-LSSVM,with root mean squares error of prediction(RMSEP)of 1.994 6,coefficient of determination(R^2)of 0.949 3,and the residual predictive deviation(RPD)of 4.370 5,respectively.Conclusions:The MCUVE-SPA-LSSVM model is accuracy enough to measure the Mn content in cottonseed meal,which can be used as an alter native way to substitute for traditional analytical method.
基金supported by the Fundamental Research Funds for the Central Universities(WK3420000020)the National Natural Science Foundation of China(42125402 and 42188101).
文摘Dual-comb spectroscopy(DCS)is one of the most promising technologies for ultra-long open-path multiplegreenhouse gas detection.Ultra-long open-path DCS has the potential to realize horizontal open-path links over hundredsof kilometers and vertical open-path links between satellites and the ground base.Under these extreme detection conditions,identifying an appropriate wavelength band that ensures both technical feasibility and a reasonable absorbance fortarget components is critical but currently lacks studies.In this work,we simulate transmission spectra under different detectionconfigurations to identify optimal wavelength bands for carbon dioxide(CO_(2))and methane(CH_(4))measurement.The simulation results show that the 1540 nm Watt-level high-power frequency combs developed are suitable for CO_(2)measurement in both horizontal and vertical ultra-long detection configurations.The results also suggest that developinghigh-power fiber amplifiers for 1630 nm and 1636 nm will facilitate CH_(4)measurement in horizontal and vertical ultra-longdetection configurations,respectively.The amplification at 1636 nm will be a future research focus,as it is expected to enablesimultaneous measurements of CH_(4),CO_(2),and water vapor in the vertical detection configuration.
基金Supported by the Natural Science Foundation of China(51705326,52075339)。
文摘In sub nanometer carbon nanotubes,water exhibits unique dynamic characteristics,and in the high-frequency region of the infrared spectrum,where the stretching vibrations of the internal oxygen-hydrogen(O-H)bonds are closely related to the hydrogen bonds(H-bonds)network between water molecules.Therefore,it is crucial to analyze the relationship between these two aspects.In this paper,the infrared spectrum and motion characteristics of the stretching vibrations of the O-H bonds in one-dimensional confined water(1DCW)and bulk water(BW)in(6,6)single-walled carbon nanotubes(SWNT)are studied by molecular dynamics simulations.The results show that the stretching vibrations of the two O-H bonds in 1DCW exhibit different frequencies in the infrared spectrum,while the O-H bonds in BW display two identical main frequency peaks.Further analysis using the spring oscillator model reveals that the difference in the stretching amplitude of the O-H bonds is the main factor causing the change in vibration frequency,where an increase in stretching amplitude leads to a decrease in spring stiffness and,consequently,a lower vibration frequency.A more in-depth study found that the interaction of H-bonds between water molecules is the fundamental cause of the increased stretching amplitude and decreased vibration frequency of the O-H bonds.Finally,by analyzing the motion trajectory of the H atoms,the dynamic differences between 1DCW and BW are clearly revealed.These findings provide a new perspective for understanding the behavior of water molecules at the nanoscale and are of significant importance in advancing the development of infrared spectroscopy detection technology.
基金Supported by Bissell Distinguished Professor Endowment Fund at UNC-Charlotte。
文摘Although there are numerous optical spectroscopy techniques and methods that have been used to extract the fundamental bandgap of a semiconductor,most of them belong to one of these three approaches:(1)the excitonic absorption,(2)modulation spectroscopy,and(3)the most widely used Tauc-plot.The excitonic absorption is based on a many-particle theory,which is physically the most correct approach,but requires more stringent crystalline quality and appropriate sample preparation and experimental implementation.The Tauc-plot is based on a single-particle theo⁃ry that neglects the many-electron effects.Modulation spectroscopy analyzes the spectroscopy features in the derivative spectrum,typically,of the reflectance and transmission under an external perturbation.Empirically,the bandgap ener⁃gy derived from the three approaches follow the order of E_(ex)>E_(MS)>E_(TP),where three transition energies are from exci⁃tonic absorption,modulation spectroscopy,and Tauc-plot,respectively.In principle,defining E_(g) as the single-elec⁃tron bandgap,we expect E_(g)>E_(ex),thus,E_(g)>E_(TP).In the literature,E_(TP) is often interpreted as E_(g),which is conceptual⁃ly problematic.However,in many cases,because the excitonic peaks are not readily identifiable,the inconsistency be⁃tween E_(g) and E_(TP) becomes invisible.In this brief review,real world examples are used(1)to illustrate how excitonic absorption features depend sensitively on the sample and measurement conditions;(2)to demonstrate the differences between E_(ex),E_(MS),and E_(TP) when they can be extracted simultaneously for one sample;and(3)to show how the popular⁃ly adopted Tauc-plot could lead to misleading results.Finally,it is pointed out that if the excitonic absorption is not ob⁃servable,the modulation spectroscopy can often yield a more useful and reasonable bandgap than Tauc-plot.
基金Supported by the National Key R&D Program of China(2023YFD2101001)National Natural Science Foundation of China(32202144,61807001)。
文摘To address the issues of peak overlap caused by complex matrices in agricultural product terahertz(THz)spectral signals and the dynamic,nonlinear interference induced by environmental and system noise,this study explores the feasibility of adaptive-signal-decomposition-based denoising methods to improve THz spectral quality.THz time-domain spectroscopy(THz-TDS)combined with an attenuated total reflection(ATR)accessory was used to collect THz absorbance spectra from 48 peanut samples.Taking the quantitative prediction model of peanut moisture content based on THz-ATR as an example,wavelet transform(WT),empirical mode decomposition(EMD),local mean decomposition(LMD),and its improved methods-segmented local mean decomposition(SLMD)and piecewise mirror extension local mean decomposition(PME-LMD)-were employed for spectral denoising.The applicability of different denoising methods was evaluated using a support vector regression(SVR)model.Experimental results show that the peanut moisture content prediction model constructed after PME-LMD denoising achieved the best performance,with a root mean square error(RMSE),coefficient of determination(R^(2)),and mean absolute percentage error(MAPE)of 0.010,0.912,and 0.040,respectively.Compared with traditional methods,PME-LMD significantly improved spectral quality and model prediction performance.The PME-LMD denoising strategy proposed in this study effectively suppresses non-uniform noise interference in THz spectral signals,providing an efficient and accurate preprocessing method for THz spectral analysis of agricultural products.This research provides theoretical support and technical guidance for the application of THz technology for detecting agricultural product quality.
基金supported by the Aeronautical Science Foundation of China(Grant No.20230018072011)。
文摘3-Nitro-1,2,4-triazol-5-one(NTO)is a typical high-energy,low-sensitivity explosive,and accurate concentration monitoring is critical for crystallization process control.In this study,a high-precision quantitative analytical model for NTO concentration in ethanol solutions was developed by integrating real-time ATR-FTIR spectroscopy with chemometric and machine learning techniques.Dynamic spectral data were obtained by designing multi-concentration gradient heating-cooling cycle experiments,abnormal samples were eliminated using the isolation forest algorithm,and the effects of various preprocessing methods on model performance were systematically evaluated.The results show that partial least squares regression(PLSR)exhibits superior generalization ability compared to other models.Vibrational bands corresponding to C=O and–NO_(2)were identified as key predictors for concentration estimation.This work provides an efficient and reliable solution for real-time concentration monitoring during NTO crystallization and holds significant potential for process analytical applications in energetic material manufacturing.
