Optimization and simplification of optical systems represent a milestone in advancing the development of handheld and portable laser-induced breakdown spectroscopy(LIBS)systems towards smaller,more integrated forms.Th...Optimization and simplification of optical systems represent a milestone in advancing the development of handheld and portable laser-induced breakdown spectroscopy(LIBS)systems towards smaller,more integrated forms.This research,for the first time,conducted a comprehensive optimization design and comparative analysis of three compact LIBS system optical paths:the paraxial optical path(OP),the off-axis OP,and the reflective OP.The differences in spectral intensity and stability among these paths were revealed,providing a scientific basis for selecting the optimal OP for LIBS systems.The research found that the paraxial OP excels in spectral performance and quantitative analysis accuracy,making it the preferred choice for compact LIBS systems.Specifically,the paraxial OP significantly enhances spectral intensity,achieving a 6 times improvement over the off-axis OP and an even more remarkable 150 times increase compared to the reflective OP,greatly enhancing detection sensitivity.Additionally,the relative standard deviation,spectral stability index,maintains a consistently low level,ranging from 10.9%to 13.4%,significantly outperforming the other two OPs and ensuring the reliability of analytical results.In the field of quantitative analysis,the paraxial OP also demonstrates higher accuracy,precision,and sensitivity,comparing to other OPs.The quantitative analysis models for Si,Cu,and Ti elements exhibit excellent fitting,providing users with high-quality quantitative analysis results that are of great significance for applications in material science,environmental monitoring,industrial inspection,and other fields.In summary,this study not only confirms the enormous application potential of the paraxial OP in compact LIBS systems but also provides valuable practical experience and theoretical support for the miniaturization and integration of LIBS systems.Looking ahead,with continuous technological advancements,the design of the paraxial OP is expected to further propel the widespread adoption of LIBS technology in portable,on-site detection applications.展开更多
Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can a...Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.展开更多
This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve(SC)and calibration-free laser-induced breakdown spectroscopy(CF-LIBS)technology to ach...This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve(SC)and calibration-free laser-induced breakdown spectroscopy(CF-LIBS)technology to achieve synchronous,rapid,and accurate measurement of elements in a large number of samples,namely,SC-assisted CF-LIBS.Al alloy standard samples,divided into calibration and test samples,were applied to validate the proposed method.SC was built based on the characteristic line of Pb and Cr in the calibration sample,and the contents of Pb and Cr in the test sample were calculated with relative errors of 6%and 4%,respectively.SC built using Cr with multiple characteristic lines yielded better calculation results.The relative contents of ten elements in the test sample were calculated using CF-LIBS.Subsequently,the SC-assisted CF-LIBS was executed,with the majority of the calculation relative errors falling within the range of 2%-5%.Finally,the Al and Na contents of the Al alloy were predicted.The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multiple elements after a single-element SC analysis of the tested samples.Furthermore,this quantitative analysis method was successfully applied to soil and Astragalus samples,realizing an accurate calculation of the contents of multiple elements.Thus,it is important to advance the LIBS quantitative analysis and its related applications.展开更多
The stable sub-angstrom resolution of the aberration-corrected scanning transmission electron microscope(ACSTEM)makes it an advanced and practical characterization technique for all materials.Owing to the prosperous a...The stable sub-angstrom resolution of the aberration-corrected scanning transmission electron microscope(ACSTEM)makes it an advanced and practical characterization technique for all materials.Owing to the prosperous advancement in computational technology,specialized software and programs have emerged as potent facilitators across the entirety of electron microscopy characterization process.Utilizing advanced image processing algorithms promotes the rectification of image distortions,concurrently elevating the overall image quality to superior standards.Extracting high-resolution,pixel-level discrete information and converting it into atomic-scale,followed by performing statistical calculations on the physical matters of interest through quantitative analysis,represent an effective strategy to maximize the value of electron microscope images.The efficacious utilization of quantitative analysis of electron microscope images has become a progressively prominent consideration for materials scientists and electron microscopy researchers.This article offers a concise overview of the pivotal procedures in quantitative analysis and summarizes the computational methodologies involved from three perspectives:contrast,lattice and strain,as well as atomic displacements and polarization.It further elaborates on practical applications of these methods in electronic functional materials,notably in piezoelectrics/ferroelectrics and thermoelectrics.It emphasizes the indispensable role of quantitative analysis in fundamental theoretical research,elucidating the structure–property correlations in high-performance systems,and guiding synthesis strategies.展开更多
To obtain more stable spectral data for accurate quantitative analysis of multi-element,especially for the large-area in-situ elements detection of soils, we propose a method for a multielement quantitative analysis o...To obtain more stable spectral data for accurate quantitative analysis of multi-element,especially for the large-area in-situ elements detection of soils, we propose a method for a multielement quantitative analysis of soils using calibration-free laser-induced breakdown spectroscopy(CF-LIBS) based on data filtering. In this study, we analyze a standard soil sample doped with two heavy metal elements, Cu and Cd, with a specific focus on the line of Cu I324.75 nm for filtering the experimental data of multiple sample sets. Pre-and post-data filtering,the relative standard deviation for Cu decreased from 30% to 10%, The limits of detection(LOD)values for Cu and Cd decreased by 5% and 4%, respectively. Through CF-LIBS, a quantitative analysis was conducted to determine the relative content of elements in soils. Using Cu as a reference, the concentration of Cd was accurately calculated. The results show that post-data filtering, the average relative error of the Cd decreases from 11% to 5%, indicating the effectiveness of data filtering in improving the accuracy of quantitative analysis. Moreover, the content of Si, Fe and other elements can be accurately calculated using this method. To further correct the calculation, the results for Cd was used to provide a more precise calculation. This approach is of great importance for the large-area in-situ heavy metals and trace elements detection in soil, as well as for rapid and accurate quantitative analysis.展开更多
Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ ...Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.展开更多
The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and co...The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and convergence zone(CZ)characteristics.Based on the Gaussian vortex model,we construct various sound propagation scenarios under different eddy conditions,and carry out sound propagation experiments to obtain simulation samples.With a large number of samples,we first adopt the unified regression to set up analytic relationships between eddy conditions and CZ parameters.The sensitivity of eddy indicators to the CZ is quantitatively analyzed.Then,we adopt the machine learning(ML)algorithms to establish prediction models of CZ parameters by exploring the nonlinear relationships between multiple ME indicators and CZ parameters.Through the research,we can express the influence of ME on the CZ quantitatively,and achieve the rapid prediction of CZ parameters in ocean eddies.The prediction accuracy(R)of the CZ distance(mean R:0.9815)is obviously better than that of the CZ width(mean R:0.8728).Among the three ML algorithms,Gradient Boosting Decision Tree has the best prediction ability(root mean square error(RMSE):0.136),followed by Random Forest(RMSE:0.441)and Extreme Learning Machine(RMSE:0.518).展开更多
Liquid chromatography-electrospray ionization tandem mass spectrometry(LC-ESI-MS)is a widely utilized technique for in vivo pharmaceutical analysis.Ionization interference within electrospray ion source,occurring betw...Liquid chromatography-electrospray ionization tandem mass spectrometry(LC-ESI-MS)is a widely utilized technique for in vivo pharmaceutical analysis.Ionization interference within electrospray ion source,occurring between drugs and metabolites,can lead to signal variations,potentially compromising quantitative accuracy.Currently,method validation often overlooks this type of signal interference,which may result in systematic errors in quantitative results without matrix-matched calibration.In this study,we conducted an investigation using ten different groups of drugs and their corresponding metabolites across three LC-ESI-MS systems to assess the prevalence of signal interference.Such interferences can potentially cause or enhance nonlinearity in the calibration curves of drugs and metabolites,thereby altering the relationship between analyte response and concentration for quantification.Finally,we established an evaluation scheme through a step-by-step dilution assay and employed three resolution methods:chromatographic separation,dilution,and stable labeled isotope internal standards correction.The above strategies were integrated into the method establishment process to improve quantitative accuracy.展开更多
In this paper, a double artificial neural network （DANN） algorithm was used to parse near infrared （NIR） reflectance spectrum of Cofrel medicines. The contents of benproperine phosphate, which is the effective ing...In this paper, a double artificial neural network （DANN） algorithm was used to parse near infrared （NIR） reflectance spectrum of Cofrel medicines. The contents of benproperine phosphate, which is the effective ingredient in Cofrel medicines, were accurately nondestructive quantitatively predicted. Compared the results with those of HPLC, the relative errors （RE %） were less than 0.18%. The analytical results could be applied to qualitative control of Cofrel medicines.展开更多
An experimental setup has been designed and realized in order to optimize the characteristics of laser-induced breakdown spectroscopy system working in various pressure environments. An approach combined the normaliza...An experimental setup has been designed and realized in order to optimize the characteristics of laser-induced breakdown spectroscopy system working in various pressure environments. An approach combined the normalization methods with the partial least squares(PLS) method are developed for quantitative analysis of molybdenum(Mo) element in the multi-component alloy,which is the first wall material in the Experimental Advanced Superconducting Tokamak. In this study, the different spectral normalization methods(total spectral area normalization,background normalization, and reference line normalization) are investigated for reducing the uncertainty and improving the accuracy of spectral measurement. The results indicates that the approach of PLS based on inter-element interference is significantly better than the conventional PLS methods as well as the univariate linear methods in the various pressure for molybdenum element analysis.展开更多
AIM: To study liver cell apoptosis caused by the toxicity of selenium and observe the alteration of choline compounds using in vitro 9.4T high resolution magnetic resonance spectroscopy. METHODS: Twenty male Wistar ra...AIM: To study liver cell apoptosis caused by the toxicity of selenium and observe the alteration of choline compounds using in vitro 9.4T high resolution magnetic resonance spectroscopy. METHODS: Twenty male Wistar rats were randomly divided into two groups. The rats in the treatment group were intraperitoneally injected with sodium selenite and the control group with distilled water. All rats were sacrifi ced and the livers were dissected. 1H-MRS data were collected using in vitro 9.4T high resolution magnetic resonance spectrometer. Spectra were processed using XWINNMR and MestRe-c 4.3. HE and TUNEL staining was employed to detect and confi rm the change of liver cells. RESULTS: Good 1H-MR spectra of perchloric acid extract from liver tissue of rats were obtained. The conventional metabolites were detected and assigned. Concentrations of different ingredient choline compounds in treatment group vs control group were as follows: total choline compounds,5.08 ± 0.97 mmol/L vs 3.81 ± 1.16 mmol/L (P = 0.05); and free choline,1.07 ± 0.23 mmol/L vs 0.65 ± 0.20 mmol/L (P = 0.00). However,there was no statistical signif icance between the two groups. The hepatic sinus and cellular structure of hepatic cells in treatmentgroup were abnormal. Apoptosis of hepatic cells was confi rmed by TUNEL assay. CONCLUSION: High dose selenium compounds can cause the rat liver lesion and induce cell apoptosis in vivo. High resolution 1H-MRS in vitro can detect diversified metabolism. The changing trend for different ingredient of choline compounds is not completely the same at early period of apoptosis.展开更多
The multi-element components of low alloy steel were quantified by using laser-induced breakdown spectroscopy (LIBS) in deep UV. The Nd:YAG pulsed laser was used to produce plasma. The spectrum was simultaneously obta...The multi-element components of low alloy steel were quantified by using laser-induced breakdown spectroscopy (LIBS) in deep UV. The Nd:YAG pulsed laser was used to produce plasma. The spectrum was simultaneously obtained by deep UV spectrometer. This paper studied the influence of experiment parameters on LIBS spectral intensity, such as delay, energy of laser, and the distance between the focusing lens and the surface of the sample. With the optimal expe- riment parameters, the characteristic lines of C, Ni, Si, Cr and Cu contained in low alloy steel were selected for quantit- ative analysis and the calibration curves of these elements were obtained. The linear correlation coefficient was good. Using the calibration curves to quantitative analysis for the sample 05-d, and the relative error of analytical results is less than 10% for most elements.展开更多
In the spectral analysis of laser-induced breakdown spectroscopy,abundant characteristic spectral lines and severe interference information exist simultaneously in the original spectral data.Here,a feature selection m...In the spectral analysis of laser-induced breakdown spectroscopy,abundant characteristic spectral lines and severe interference information exist simultaneously in the original spectral data.Here,a feature selection method called recursive feature elimination based on ridge regression(Ridge-RFE)for the original spectral data is recommended to make full use of the valid information of spectra.In the Ridge-RFE method,the absolute value of the ridge regression coefficient was used as a criterion to screen spectral characteristic,the feature with the absolute value of minimum weight in the input subset features was removed by recursive feature elimination(RFE),and the selected features were used as inputs of the partial least squares regression(PLS)model.The Ridge-RFE method based PLS model was used to measure the Fe,Si,Mg,Cu,Zn and Mn for 51 aluminum alloy samples,and the results showed that the root mean square error of prediction decreased greatly compared to the PLS model with full spectrum as input.The overall results demonstrate that the Ridge-RFE method is more efficient to extract the redundant features,make PLS model for better quantitative analysis results and improve model generalization ability.展开更多
Laser-induced breakdown spectroscopy(LIBS) is a sensitive optical technique that is capable of rapid multi-elemental analysis. The development of this technique for elemental analysis of pharmaceutical products may ev...Laser-induced breakdown spectroscopy(LIBS) is a sensitive optical technique that is capable of rapid multi-elemental analysis. The development of this technique for elemental analysis of pharmaceutical products may eventually revolutionize the field of human health. Under normal circumstances, the elemental analysis of pharmaceutical products based on chemical methods is time-consuming and complicated. In this investigation, the principal aim is to develop an LIBS-based methodology for elemental analysis of pharmaceutical products. This LIBS technique was utilized for qualitative as well as quantitative analysis of the elements present in Ca-based tablets. All the elements present in the tablets were detected and their percentage compositions were verified in a single shot, using the proposed instrument. These elements(e.g., Ca, Mg, Fe, Zn, and others) were identified by the wavelengths of their spectral lines, which were verified using the NIST database. The approximate amount of each element was determined based on their observed peaks and the result was in exact agreement with the content specification. The determination of the composition of prescription drug for patients is highly important in numerous circumstances. For example, the exploitation of LIBS may facilitate elemental decomposition of medicines to determine the accuracy of the stated composition information. Moreover, the approach can provide element-specific, meaningful, and accurate information related to pharmaceutical products.展开更多
Tokamak exhaust is an important part of the deuterium-tritium fuel cycle system in fusion reactions.In this work,we present a laser-induced breakdown spectroscopy(LIBS)-based method to monitor the gas compositions fro...Tokamak exhaust is an important part of the deuterium-tritium fuel cycle system in fusion reactions.In this work,we present a laser-induced breakdown spectroscopy(LIBS)-based method to monitor the gas compositions from the exhaust system in the tokamak device.Helium(He),a main impurity in the exhaust gas,was mixed with hydrogen(H_(2))in different ratios through a self-designed gas distribution system,and sealed into a measurement chamber as a standard specimen.A 532 nm wavelength laser pulse with an output power of 100 mJ was used for plasma excitation.The time-resolved LIBS is used to study the time evolution characteristics of the signal strength,signal-to-background ratio(SBR),signal-to-noise ratio(SNR)and relative standard deviation(RSD)of the helium and hydrogen characteristic lines.The Boltzmann twoline method was employed to estimate the plasma temperature of laser-induced plasma(LIP).The Stark-broadened profile of He I 587.56 nm was exploited to measure the electron density.From these studies,an appropriate time was determined in which the low RSD%was consistent with the high signal-to-noise ratio.The He I 587.56 nm and Hαemission lines with good signalto-noise ratio were extracted from the spectrum and used in the external standard method and internal standard method for quantitative analysis.The test results for mixed gas showed that the average relative error of prediction was less than 11.15%,demonstrating the great potential of LIBS in detecting impurities in plasma exhaust gas.展开更多
Hyperspectral data fusion technique is the key to hyperspectral data processing in recent years. Many fusion methods have been proposed, but little research has been done to evaluate the performances of different data...Hyperspectral data fusion technique is the key to hyperspectral data processing in recent years. Many fusion methods have been proposed, but little research has been done to evaluate the performances of different data fusion methods. In order to meet the urgent need, quantitative correlation analysis(QCA) is proposed to analyse and compare the performances of different fusion methods directly from data before and after fusion. Experiment results show that the new method is effective and the results of comparison are in agreement with the results of application.展开更多
BAIRD SPECTROVAC 2000(DV 5) consisting of new type of HR-400 high repeat rate spark spectrosource, air cooled sample stand and an annular purged tungsten counter electrode has been used continuously in the la...BAIRD SPECTROVAC 2000(DV 5) consisting of new type of HR-400 high repeat rate spark spectrosource, air cooled sample stand and an annular purged tungsten counter electrode has been used continuously in the lab for many years and resulted in good economic benefits. The paper describes the application of the spectrometer in quantitative analysis of cast iron and steel products, and the experience and technique may be helpful to those who are using the same kind of instrument.展开更多
The Laser Induced Breakdown Spectroscopy (LIBS) is a fast, non-contact, no sample preparation analytic technology;it is very suitable for on-line analysis of alloy composition. In the copper smelting industry, analysi...The Laser Induced Breakdown Spectroscopy (LIBS) is a fast, non-contact, no sample preparation analytic technology;it is very suitable for on-line analysis of alloy composition. In the copper smelting industry, analysis and control of the copper alloy concentration affect the quality of the products greatly, so LIBS is an efficient quantitative analysis tech- nology in the copper smelting industry. But for the lead brass, the components of Pb, Al and Ni elements are very low and the atomic emission lines are easily submerged under copper complex characteristic spectral lines because of the matrix effects. So it is difficult to get the online quantitative result of these important elements. In this paper, both the partial least squares (PLS) method and the calibration curve (CC) method are used to quantitatively analyze the laser induced breakdown spectroscopy data which is obtained from the standard lead brass alloy samples. Both the major and trace elements were quantitatively analyzed. By comparing the two results of the different calibration method, some useful results were obtained: both for major and trace elements, the PLS method was better than the CC method in quantitative analysis. And the regression coefficient of PLS method is compared with the original spectral data with background interference to explain the advantage of the PLS method in the LIBS quantitative analysis. Results proved that the PLS method used in laser induced breakdown spectroscopy was suitable for simultaneous quantitative analysis of different content elements in copper smelting industry.展开更多
Laser-induced breakdown spectroscopy(LIBS)has been applied to many fields for the quantitative analysis of diverse materials.Improving the prediction accuracy of LIBS regression models is still of great significance f...Laser-induced breakdown spectroscopy(LIBS)has been applied to many fields for the quantitative analysis of diverse materials.Improving the prediction accuracy of LIBS regression models is still of great significance for the Mars exploration in the near future.In this study,we explored the quantitative analysis of LIBS for the one-dimensional Chem Cam(an instrument containing a LIBS spectrometer and a Remote Micro-Imager)spectral data whose spectra are produced by the Chem Cam team using LIBS under the Mars-like atmospheric conditions.We constructed a convolutional neural network(CNN)regression model with unified parameters for all oxides,which is efficient and concise.CNN that has the excellent capability of feature extraction can effectively overcome the chemical matrix effects that impede the prediction accuracy of regression models.Firstly,we explored the effects of four activation functions on the performance of the CNN model.The results show that the CNN model with the hyperbolic tangent(tanh)function outperforms the CNN models with the other activation functions(the rectified linear unit function,the linear function and the Sigmoid function).Secondly,we compared the performance among the CNN models using different optimization methods.The CNN model with the stochastic gradient descent optimization and the initial learning rate?=?0.0005 achieves satisfactory performance compared to the other CNN models.Finally,we compared the performance of the CNN model,the model based on support vector regression(SVR)and the model based on partial least square regression(PLSR).The results exhibit the CNN model is superior to the SVR model and the PLSR model for all oxides.Based on the above analysis,we conclude the CNN regression model can effectively improve the prediction accuracy of LIBS.展开更多
pH is one of the significant properties of soil,and is closely related to the decomposition of soil organic matter,anion-cation balance,growth of plants and many other soil processes.In the present work,laser-induced ...pH is one of the significant properties of soil,and is closely related to the decomposition of soil organic matter,anion-cation balance,growth of plants and many other soil processes.In the present work,laser-induced breakdown spectroscopy(LIBS) technique coupled with random forest(RF) was proposed to quantify the pH of soil.First,LIBS spectra of soil was collected,and some common elements in soil were identified based on the National Institute of Science and Technology database.Then,in order to obtain a better predictive result,the influence of different input variables(full spectrum,different spectral ranges,the intensity of characteristic bands and characteristic lines) on the predictive performance of RF calibration model was explored with the evaluation indicators of root mean square error(RMSE) and coefficient of determination(R2),the characteristic bands of four elements(AI,Ca,Mg and Si) were determined as the optimal input variables.Finally,the predictive performance of RF calibration model was compared with partial least squares calibration model with the optimal input variables and model parameters,and RF calibration model showed a better predictive performance,and the four evaluation indicators of R_p^2,RMSEP,mean absolute error and mean relative error were 0.9687,0.1285,0.1114 and 0.0136,respectively.It indicates that LIBS technique coupled with RF algorithm is an effective method for pH determination of soil.展开更多
基金financially supported by National Natural Science Foundation of China (Nos.62305392 and 62305123)Independent Research and Development Project of Naval Engineering University (No.2023504050)the Nursery Plan Project of Navel University of Engineering (2022)。
文摘Optimization and simplification of optical systems represent a milestone in advancing the development of handheld and portable laser-induced breakdown spectroscopy(LIBS)systems towards smaller,more integrated forms.This research,for the first time,conducted a comprehensive optimization design and comparative analysis of three compact LIBS system optical paths:the paraxial optical path(OP),the off-axis OP,and the reflective OP.The differences in spectral intensity and stability among these paths were revealed,providing a scientific basis for selecting the optimal OP for LIBS systems.The research found that the paraxial OP excels in spectral performance and quantitative analysis accuracy,making it the preferred choice for compact LIBS systems.Specifically,the paraxial OP significantly enhances spectral intensity,achieving a 6 times improvement over the off-axis OP and an even more remarkable 150 times increase compared to the reflective OP,greatly enhancing detection sensitivity.Additionally,the relative standard deviation,spectral stability index,maintains a consistently low level,ranging from 10.9%to 13.4%,significantly outperforming the other two OPs and ensuring the reliability of analytical results.In the field of quantitative analysis,the paraxial OP also demonstrates higher accuracy,precision,and sensitivity,comparing to other OPs.The quantitative analysis models for Si,Cu,and Ti elements exhibit excellent fitting,providing users with high-quality quantitative analysis results that are of great significance for applications in material science,environmental monitoring,industrial inspection,and other fields.In summary,this study not only confirms the enormous application potential of the paraxial OP in compact LIBS systems but also provides valuable practical experience and theoretical support for the miniaturization and integration of LIBS systems.Looking ahead,with continuous technological advancements,the design of the paraxial OP is expected to further propel the widespread adoption of LIBS technology in portable,on-site detection applications.
基金financial supports from National Natural Science Foundation of China(No.62205172)Huaneng Group Science and Technology Research Project(No.HNKJ22-H105)Tsinghua University Initiative Scientific Research Program and the International Joint Mission on Climate Change and Carbon Neutrality。
文摘Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.
基金supported by the Major Science and TechnologyTechnol-ogy Projects in Gansu Province(No.22ZD6FA021-5)Industrial Support Project of Gansu Province(Nos.2023CYZC-19 and 2021CYZC-22)+1 种基金Science and Technol-ogy Project of Gansu Province(Nos.23YFFA0074,22JR5RA137,and 22JR5RA151)Central Leading Local Science and Technology Development Fund Projects(No.23ZYQA293).
文摘This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve(SC)and calibration-free laser-induced breakdown spectroscopy(CF-LIBS)technology to achieve synchronous,rapid,and accurate measurement of elements in a large number of samples,namely,SC-assisted CF-LIBS.Al alloy standard samples,divided into calibration and test samples,were applied to validate the proposed method.SC was built based on the characteristic line of Pb and Cr in the calibration sample,and the contents of Pb and Cr in the test sample were calculated with relative errors of 6%and 4%,respectively.SC built using Cr with multiple characteristic lines yielded better calculation results.The relative contents of ten elements in the test sample were calculated using CF-LIBS.Subsequently,the SC-assisted CF-LIBS was executed,with the majority of the calculation relative errors falling within the range of 2%-5%.Finally,the Al and Na contents of the Al alloy were predicted.The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multiple elements after a single-element SC analysis of the tested samples.Furthermore,this quantitative analysis method was successfully applied to soil and Astragalus samples,realizing an accurate calculation of the contents of multiple elements.Thus,it is important to advance the LIBS quantitative analysis and its related applications.
基金Project supported by the financial support from the National Key R&D Program of China(Grant No.2021YFB3201100)the National Natural Science Foundation of China(Grant No.52172128)the Top Young Talents Programme of Xi’an Jiaotong University.
文摘The stable sub-angstrom resolution of the aberration-corrected scanning transmission electron microscope(ACSTEM)makes it an advanced and practical characterization technique for all materials.Owing to the prosperous advancement in computational technology,specialized software and programs have emerged as potent facilitators across the entirety of electron microscopy characterization process.Utilizing advanced image processing algorithms promotes the rectification of image distortions,concurrently elevating the overall image quality to superior standards.Extracting high-resolution,pixel-level discrete information and converting it into atomic-scale,followed by performing statistical calculations on the physical matters of interest through quantitative analysis,represent an effective strategy to maximize the value of electron microscope images.The efficacious utilization of quantitative analysis of electron microscope images has become a progressively prominent consideration for materials scientists and electron microscopy researchers.This article offers a concise overview of the pivotal procedures in quantitative analysis and summarizes the computational methodologies involved from three perspectives:contrast,lattice and strain,as well as atomic displacements and polarization.It further elaborates on practical applications of these methods in electronic functional materials,notably in piezoelectrics/ferroelectrics and thermoelectrics.It emphasizes the indispensable role of quantitative analysis in fundamental theoretical research,elucidating the structure–property correlations in high-performance systems,and guiding synthesis strategies.
基金supported by the Major Science and Technology Project of Gansu Province(No.22ZD6FA021-5)the Industrial Support Project of Gansu Province(Nos.2023CYZC-19 and 2021CYZC-22)the Science and Technology Project of Gansu Province(Nos.23YFFA0074,22JR5RA137 and 22JR5RA151).
文摘To obtain more stable spectral data for accurate quantitative analysis of multi-element,especially for the large-area in-situ elements detection of soils, we propose a method for a multielement quantitative analysis of soils using calibration-free laser-induced breakdown spectroscopy(CF-LIBS) based on data filtering. In this study, we analyze a standard soil sample doped with two heavy metal elements, Cu and Cd, with a specific focus on the line of Cu I324.75 nm for filtering the experimental data of multiple sample sets. Pre-and post-data filtering,the relative standard deviation for Cu decreased from 30% to 10%, The limits of detection(LOD)values for Cu and Cd decreased by 5% and 4%, respectively. Through CF-LIBS, a quantitative analysis was conducted to determine the relative content of elements in soils. Using Cu as a reference, the concentration of Cd was accurately calculated. The results show that post-data filtering, the average relative error of the Cd decreases from 11% to 5%, indicating the effectiveness of data filtering in improving the accuracy of quantitative analysis. Moreover, the content of Si, Fe and other elements can be accurately calculated using this method. To further correct the calculation, the results for Cd was used to provide a more precise calculation. This approach is of great importance for the large-area in-situ heavy metals and trace elements detection in soil, as well as for rapid and accurate quantitative analysis.
基金the financial support provided by the National Natural Science Foundation of China(Grant No.11872013).
文摘Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.
基金The National Natural Science Foundation of China under contract Nos 41875061 and 41775165.
文摘The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and convergence zone(CZ)characteristics.Based on the Gaussian vortex model,we construct various sound propagation scenarios under different eddy conditions,and carry out sound propagation experiments to obtain simulation samples.With a large number of samples,we first adopt the unified regression to set up analytic relationships between eddy conditions and CZ parameters.The sensitivity of eddy indicators to the CZ is quantitatively analyzed.Then,we adopt the machine learning(ML)algorithms to establish prediction models of CZ parameters by exploring the nonlinear relationships between multiple ME indicators and CZ parameters.Through the research,we can express the influence of ME on the CZ quantitatively,and achieve the rapid prediction of CZ parameters in ocean eddies.The prediction accuracy(R)of the CZ distance(mean R:0.9815)is obviously better than that of the CZ width(mean R:0.8728).Among the three ML algorithms,Gradient Boosting Decision Tree has the best prediction ability(root mean square error(RMSE):0.136),followed by Random Forest(RMSE:0.441)and Extreme Learning Machine(RMSE:0.518).
基金support provided by the National Natural Science Foundation of China(Grant No.:82173776)Natural Science Foundation of Guangdong Province,China(Grant No.:2021A1515010574)Guangdong Basic and Applied Basic Research Foundation,China(Grant No.:2021A1515110346).
文摘Liquid chromatography-electrospray ionization tandem mass spectrometry(LC-ESI-MS)is a widely utilized technique for in vivo pharmaceutical analysis.Ionization interference within electrospray ion source,occurring between drugs and metabolites,can lead to signal variations,potentially compromising quantitative accuracy.Currently,method validation often overlooks this type of signal interference,which may result in systematic errors in quantitative results without matrix-matched calibration.In this study,we conducted an investigation using ten different groups of drugs and their corresponding metabolites across three LC-ESI-MS systems to assess the prevalence of signal interference.Such interferences can potentially cause or enhance nonlinearity in the calibration curves of drugs and metabolites,thereby altering the relationship between analyte response and concentration for quantification.Finally,we established an evaluation scheme through a step-by-step dilution assay and employed three resolution methods:chromatographic separation,dilution,and stable labeled isotope internal standards correction.The above strategies were integrated into the method establishment process to improve quantitative accuracy.
文摘In this paper, a double artificial neural network （DANN） algorithm was used to parse near infrared （NIR） reflectance spectrum of Cofrel medicines. The contents of benproperine phosphate, which is the effective ingredient in Cofrel medicines, were accurately nondestructive quantitatively predicted. Compared the results with those of HPLC, the relative errors （RE %） were less than 0.18%. The analytical results could be applied to qualitative control of Cofrel medicines.
基金supported by the National Magnetic Confinement Fusion Science Program of China (No. 2017YFE0301304)National Natural Science Foundation of China (Nos. 11 475 039, 11 605 023, 11 705 020)+2 种基金China Postdoctoral Science Foundation (Nos. 2016M591423, 2017T100172, 2018M630285)the Fundamental Research Funds for the Central Universities (Nos. DUT15RC(3)072, DUT17RC(4)53, DUT18LK38)Liaoning Provincial Natural Science Foundation of China (No. 20 170 540 153)
文摘An experimental setup has been designed and realized in order to optimize the characteristics of laser-induced breakdown spectroscopy system working in various pressure environments. An approach combined the normalization methods with the partial least squares(PLS) method are developed for quantitative analysis of molybdenum(Mo) element in the multi-component alloy,which is the first wall material in the Experimental Advanced Superconducting Tokamak. In this study, the different spectral normalization methods(total spectral area normalization,background normalization, and reference line normalization) are investigated for reducing the uncertainty and improving the accuracy of spectral measurement. The results indicates that the approach of PLS based on inter-element interference is significantly better than the conventional PLS methods as well as the univariate linear methods in the various pressure for molybdenum element analysis.
基金The National Natural Science Foundation of China,No.30570480
文摘AIM: To study liver cell apoptosis caused by the toxicity of selenium and observe the alteration of choline compounds using in vitro 9.4T high resolution magnetic resonance spectroscopy. METHODS: Twenty male Wistar rats were randomly divided into two groups. The rats in the treatment group were intraperitoneally injected with sodium selenite and the control group with distilled water. All rats were sacrifi ced and the livers were dissected. 1H-MRS data were collected using in vitro 9.4T high resolution magnetic resonance spectrometer. Spectra were processed using XWINNMR and MestRe-c 4.3. HE and TUNEL staining was employed to detect and confi rm the change of liver cells. RESULTS: Good 1H-MR spectra of perchloric acid extract from liver tissue of rats were obtained. The conventional metabolites were detected and assigned. Concentrations of different ingredient choline compounds in treatment group vs control group were as follows: total choline compounds,5.08 ± 0.97 mmol/L vs 3.81 ± 1.16 mmol/L (P = 0.05); and free choline,1.07 ± 0.23 mmol/L vs 0.65 ± 0.20 mmol/L (P = 0.00). However,there was no statistical signif icance between the two groups. The hepatic sinus and cellular structure of hepatic cells in treatmentgroup were abnormal. Apoptosis of hepatic cells was confi rmed by TUNEL assay. CONCLUSION: High dose selenium compounds can cause the rat liver lesion and induce cell apoptosis in vivo. High resolution 1H-MRS in vitro can detect diversified metabolism. The changing trend for different ingredient of choline compounds is not completely the same at early period of apoptosis.
文摘The multi-element components of low alloy steel were quantified by using laser-induced breakdown spectroscopy (LIBS) in deep UV. The Nd:YAG pulsed laser was used to produce plasma. The spectrum was simultaneously obtained by deep UV spectrometer. This paper studied the influence of experiment parameters on LIBS spectral intensity, such as delay, energy of laser, and the distance between the focusing lens and the surface of the sample. With the optimal expe- riment parameters, the characteristic lines of C, Ni, Si, Cr and Cu contained in low alloy steel were selected for quantit- ative analysis and the calibration curves of these elements were obtained. The linear correlation coefficient was good. Using the calibration curves to quantitative analysis for the sample 05-d, and the relative error of analytical results is less than 10% for most elements.
基金supported by National Key Research and Development Program of China(No.2016YFF0102502)the Key Research Program of Frontier Sciences,CAS(No.QYZDJ-SSW-JSC037)the Youth Innovation Promotion Association,CAS,Liao Ning Revitalization Talents Program(No.XLYC1807110)。
文摘In the spectral analysis of laser-induced breakdown spectroscopy,abundant characteristic spectral lines and severe interference information exist simultaneously in the original spectral data.Here,a feature selection method called recursive feature elimination based on ridge regression(Ridge-RFE)for the original spectral data is recommended to make full use of the valid information of spectra.In the Ridge-RFE method,the absolute value of the ridge regression coefficient was used as a criterion to screen spectral characteristic,the feature with the absolute value of minimum weight in the input subset features was removed by recursive feature elimination(RFE),and the selected features were used as inputs of the partial least squares regression(PLS)model.The Ridge-RFE method based PLS model was used to measure the Fe,Si,Mg,Cu,Zn and Mn for 51 aluminum alloy samples,and the results showed that the root mean square error of prediction decreased greatly compared to the PLS model with full spectrum as input.The overall results demonstrate that the Ridge-RFE method is more efficient to extract the redundant features,make PLS model for better quantitative analysis results and improve model generalization ability.
文摘Laser-induced breakdown spectroscopy(LIBS) is a sensitive optical technique that is capable of rapid multi-elemental analysis. The development of this technique for elemental analysis of pharmaceutical products may eventually revolutionize the field of human health. Under normal circumstances, the elemental analysis of pharmaceutical products based on chemical methods is time-consuming and complicated. In this investigation, the principal aim is to develop an LIBS-based methodology for elemental analysis of pharmaceutical products. This LIBS technique was utilized for qualitative as well as quantitative analysis of the elements present in Ca-based tablets. All the elements present in the tablets were detected and their percentage compositions were verified in a single shot, using the proposed instrument. These elements(e.g., Ca, Mg, Fe, Zn, and others) were identified by the wavelengths of their spectral lines, which were verified using the NIST database. The approximate amount of each element was determined based on their observed peaks and the result was in exact agreement with the content specification. The determination of the composition of prescription drug for patients is highly important in numerous circumstances. For example, the exploitation of LIBS may facilitate elemental decomposition of medicines to determine the accuracy of the stated composition information. Moreover, the approach can provide element-specific, meaningful, and accurate information related to pharmaceutical products.
基金supported by the National Key R&D Program of China(Nos.2017YFE0301506 and 2017YFE0301306)。
文摘Tokamak exhaust is an important part of the deuterium-tritium fuel cycle system in fusion reactions.In this work,we present a laser-induced breakdown spectroscopy(LIBS)-based method to monitor the gas compositions from the exhaust system in the tokamak device.Helium(He),a main impurity in the exhaust gas,was mixed with hydrogen(H_(2))in different ratios through a self-designed gas distribution system,and sealed into a measurement chamber as a standard specimen.A 532 nm wavelength laser pulse with an output power of 100 mJ was used for plasma excitation.The time-resolved LIBS is used to study the time evolution characteristics of the signal strength,signal-to-background ratio(SBR),signal-to-noise ratio(SNR)and relative standard deviation(RSD)of the helium and hydrogen characteristic lines.The Boltzmann twoline method was employed to estimate the plasma temperature of laser-induced plasma(LIP).The Stark-broadened profile of He I 587.56 nm was exploited to measure the electron density.From these studies,an appropriate time was determined in which the low RSD%was consistent with the high signal-to-noise ratio.The He I 587.56 nm and Hαemission lines with good signalto-noise ratio were extracted from the spectrum and used in the external standard method and internal standard method for quantitative analysis.The test results for mixed gas showed that the average relative error of prediction was less than 11.15%,demonstrating the great potential of LIBS in detecting impurities in plasma exhaust gas.
文摘Hyperspectral data fusion technique is the key to hyperspectral data processing in recent years. Many fusion methods have been proposed, but little research has been done to evaluate the performances of different data fusion methods. In order to meet the urgent need, quantitative correlation analysis(QCA) is proposed to analyse and compare the performances of different fusion methods directly from data before and after fusion. Experiment results show that the new method is effective and the results of comparison are in agreement with the results of application.
文摘BAIRD SPECTROVAC 2000(DV 5) consisting of new type of HR-400 high repeat rate spark spectrosource, air cooled sample stand and an annular purged tungsten counter electrode has been used continuously in the lab for many years and resulted in good economic benefits. The paper describes the application of the spectrometer in quantitative analysis of cast iron and steel products, and the experience and technique may be helpful to those who are using the same kind of instrument.
文摘The Laser Induced Breakdown Spectroscopy (LIBS) is a fast, non-contact, no sample preparation analytic technology;it is very suitable for on-line analysis of alloy composition. In the copper smelting industry, analysis and control of the copper alloy concentration affect the quality of the products greatly, so LIBS is an efficient quantitative analysis tech- nology in the copper smelting industry. But for the lead brass, the components of Pb, Al and Ni elements are very low and the atomic emission lines are easily submerged under copper complex characteristic spectral lines because of the matrix effects. So it is difficult to get the online quantitative result of these important elements. In this paper, both the partial least squares (PLS) method and the calibration curve (CC) method are used to quantitatively analyze the laser induced breakdown spectroscopy data which is obtained from the standard lead brass alloy samples. Both the major and trace elements were quantitatively analyzed. By comparing the two results of the different calibration method, some useful results were obtained: both for major and trace elements, the PLS method was better than the CC method in quantitative analysis. And the regression coefficient of PLS method is compared with the original spectral data with background interference to explain the advantage of the PLS method in the LIBS quantitative analysis. Results proved that the PLS method used in laser induced breakdown spectroscopy was suitable for simultaneous quantitative analysis of different content elements in copper smelting industry.
基金supported by the Pre-research project on Civil Aerospace Technologies(No.D020102)funded by China National Space Administration(CNSA)the funding from National Natural Science Foundation of China(Nos.U1931211,41573056)+1 种基金the Natural Science Foundation of Shandong Province(No.ZR2019MD008)the Major Research Project of Shandong Province(No.GG201809130208)。
文摘Laser-induced breakdown spectroscopy(LIBS)has been applied to many fields for the quantitative analysis of diverse materials.Improving the prediction accuracy of LIBS regression models is still of great significance for the Mars exploration in the near future.In this study,we explored the quantitative analysis of LIBS for the one-dimensional Chem Cam(an instrument containing a LIBS spectrometer and a Remote Micro-Imager)spectral data whose spectra are produced by the Chem Cam team using LIBS under the Mars-like atmospheric conditions.We constructed a convolutional neural network(CNN)regression model with unified parameters for all oxides,which is efficient and concise.CNN that has the excellent capability of feature extraction can effectively overcome the chemical matrix effects that impede the prediction accuracy of regression models.Firstly,we explored the effects of four activation functions on the performance of the CNN model.The results show that the CNN model with the hyperbolic tangent(tanh)function outperforms the CNN models with the other activation functions(the rectified linear unit function,the linear function and the Sigmoid function).Secondly,we compared the performance among the CNN models using different optimization methods.The CNN model with the stochastic gradient descent optimization and the initial learning rate?=?0.0005 achieves satisfactory performance compared to the other CNN models.Finally,we compared the performance of the CNN model,the model based on support vector regression(SVR)and the model based on partial least square regression(PLSR).The results exhibit the CNN model is superior to the SVR model and the PLSR model for all oxides.Based on the above analysis,we conclude the CNN regression model can effectively improve the prediction accuracy of LIBS.
基金support of National Natural Science Foundation of China(Nos.21873076,21675123,21605123,21375105)Natural Science Basic Research Plan in Shaanxi Province of China(No.2018JQ2013)Scientific Research Plan Projects of Shaanxi Education Department(No.17JK0780)。
文摘pH is one of the significant properties of soil,and is closely related to the decomposition of soil organic matter,anion-cation balance,growth of plants and many other soil processes.In the present work,laser-induced breakdown spectroscopy(LIBS) technique coupled with random forest(RF) was proposed to quantify the pH of soil.First,LIBS spectra of soil was collected,and some common elements in soil were identified based on the National Institute of Science and Technology database.Then,in order to obtain a better predictive result,the influence of different input variables(full spectrum,different spectral ranges,the intensity of characteristic bands and characteristic lines) on the predictive performance of RF calibration model was explored with the evaluation indicators of root mean square error(RMSE) and coefficient of determination(R2),the characteristic bands of four elements(AI,Ca,Mg and Si) were determined as the optimal input variables.Finally,the predictive performance of RF calibration model was compared with partial least squares calibration model with the optimal input variables and model parameters,and RF calibration model showed a better predictive performance,and the four evaluation indicators of R_p^2,RMSEP,mean absolute error and mean relative error were 0.9687,0.1285,0.1114 and 0.0136,respectively.It indicates that LIBS technique coupled with RF algorithm is an effective method for pH determination of soil.
