Quantum cascade laser absorption sensor for in-situ, real-time and sensitive measurement of high-temperature SO2 and SO3.

We report a mid-infrared quantum cascade laser absorption sensor capable of measuring SO2 and SO3 simultaneously and sensitively at elevated temperatures. In the sensor development, the intense transitions of SO2 and SO3 in the mid-infrared region of 1129 cm-1 and 1398 cm-1 were exploited by two quantum cascade lasers. A high-temperature multipass cell was adopted to increase the absorption path length to 10 m. The quantitative concentrations of SOx were directly obtained from the calibration-free wavelength modulation spectroscopic method, which was validated at varied temperature and pressure conditions. From Allan deviation analysis, we achieved a minimum detection limit of 8 parts per billion (ppb) for SO2 and 3 ppb for SO3, with an average time of 100 s. Lastly, we successfully demonstrated the real-time and sensitive measurement of SO2 and SO3 during the oxidation reaction of SO2 by O3 at 460 K. Our laser sensor shows great potential for in-situ and real-time monitoring of SOx from combustion emissions.

Programming Non-Nucleic Acid Molecules into Computational Nucleic Acid Systems.

Nucleic acid (NA) computation has been widely developed in the past years to solve kinds of logic and mathematic issues in both information technologies and biomedical analysis. However, the difficulty to integrate non-NA molecules limits its power as a universal platform for molecular computation. Here, we report a versatile prototype of hybridized computation integrated with both nucleic acids and non-NA molecules. Employing the conformationally controlled ligand converters, we demonstrate that non-NA molecules, including both small molecules and proteins, can be computed as nucleic acid strands to construct the circuitry with increased complexity and scalability, and can be even programmed to solve arithmetical calculations within the computational nucleic acid system. This study opens a new door for molecular computation in which all-NA circuits can be expanded with integration of various ligands, and meanwhile, ligands can be precisely programmed by the nuclei acid computation.

Exploiting Data Uncertainty for Improving the Performance of a Quantitative Analysis Model for Laser-Induced Breakdown Spectroscopy.

The accuracy and precision of laser-induced breakdown spectroscopy (LIBS) quantitative analysis are significantly limited by the spectral noise. Normalization and ensemble averaging of multiple spectra were often used to preprocess spectra. However, these methods cannot completely remove the spectral noise. Data uncertainty due to the irremovable spectral noise will affect LIBS quantitative analysis. Therefore, this paper proposes a method using data uncertainty to improve the performance of LIBS quantitative analysis. The proposed method uses several spectra to characterize each sample to preserve some data uncertainty in the calibration data matrix. Thus, the data uncertainty is used to optimize the calibration model for improving the toleration to the spectral signal variation. As a result, the optimized calibration model had better accuracy and robustness than the calibration model trained by conventional method. The best root mean square error of prediction (RMSEP) of the ash content of coal was 1.152% for the optimized calibration model, while that for the conventional calibration model was 1.718%. The optimized calibration model also showed a lower relative standard deviation (RSD) value of repeated predictions. Moreover, the calibration model for predicting the ash content in biomass was also optimized by the proposed method. The optimized calibration model outperformed the conventional calibration model again, which demonstrated the extensive applicability of the proposed method.

Optimizing the quantitative analysis of solid biomass fuel properties using laser induced breakdown spectroscopy (LIBS) coupled with a kernel partial least squares (KPLS) model.

The rapid analysis of fuel properties is important for the utilization of solid biomass due to its great variation in feedstock. Laser-induced breakdown spectroscopy (LIBS) technology combined with quantitative analysis models can be used for this analysis. Most existing prediction models used in LIBS for fuel property analysis are linear methods, such as the partial least squares (PLS) model, which fail to reflect the non-linear relationships between the LIBS spectrum and the fuel property index being predicted. In the present work, LIBS data combined with a kernel partial least squares (KPLS) method are used to analyze the gross calorific value, and the volatile matter, ash and fixed carbon content of the solid biomass fuel. Quantitative analysis performance of the KPLS model was compared to that of the widely used PLS method, with the results showing some improvements. The KPLS model was further improved using three data normalization methods (i.e., C internal standardization, total intensity standardization and standard normal variate). The best quantitative analysis results of the volatile matter and ash content were obtained when the KPLS model was combined with C internal standardization, with root mean square errors of prediction (RMSEP) of 1.365% and 0.290%, and average standard deviations (ASD) of 0.277% and 0.080%, respectively. The best quantitative analysis results of the gross calorific value and fixed carbon content were obtained when using KPLS without normalization. The RMSEP and ASD of the gross calorific value and fixed carbon content were 0.198 MJ kg-1 and 0.746%, and 0.070 MJ kg-1 and 0.111% respectively.

Optimizing analysis of coal property using laser-induced breakdown and near-infrared reflectance spectroscopies.

Coal properties have different correlations with elements or molecules. It is difficult to optimize the analysis of multiple coal properties simultaneously by a single analytical technique. This paper reports a method for optimizing analysis of coal properties by using laser-induced breakdown spectroscopy (LIBS) and near-infrared reflectance spectroscopy (NIRS). Briefly, LIBS, NIRS, as well as spectral information fusion of LIBS and NIRS (LIBS&NIRS) were used to establish the quantitative analysis models of coal properties with partial least squares (PLS) method. The performance of models based on different spectral information was compared with each other according to the determination coefficient (R2), root mean square error of prediction (RMSEP), average absolute error (AAE), and average relative error (ARE). As a result, the models of calorific value and volatile matter based on LIBS&NIRS have the best performance with minimum root mean square error for prediction (RMSEP) of 0.192 MJ/kg and 0.672%. However, for the model of ash content, the minimum RMSEP of 0.774% was achieved by using LIBS. Meanwhile, optimal performance of modeling moisture content was obtained from NIRS with the minimum RMSEP of 0.308%. After obtaining the best prediction results of volatile matter content, ash content, and moisture content, the fixed carbon content can be calculated by the definition formula. These results demonstrated that the reported method can optimize the rapid analysis of multiple coal properties simultaneously.

Evaluation of heavy metal element detection in municipal solid waste incineration fly ash based on LIBS sensor.

Heavy metal elements are the main pollutants in municipal solid waste incineration (MSWI) fly ash, the online detection of heavy metals in MSWI fly ash could benefit its subsequent solidification treatment and land-filling. In this paper, laser induced breakdown spectroscopy (LIBS) was introduced to the rapid measurement of heavy metal elements in MSWI fly ash. Considering the serious matrix effect in MSWI fly ash, the multiple linear regression model combined with internal standard method was used to establish the calibration curves of heavy metals. Validated samples were used to evaluate the performance of quantitative analysis models. The results show that linear regression coefficients (R2) of the calibration curves for Cd, Cr, Cu, Pb, Zn are 0.981, 0.988, 0.968, 0.978 and 0.993, respectively. The average relative error of the prediction results are from 6.8 to 20.3%. The detection limits of the heavy metal content are Cd (11.13 µg/g), Cr (44.87 µg/g), Cu (36.18 µg/g), Pb (10.83 µg/g), Zn (12.27 µg/g), respectively, which are far below those required in the Standard for Pollution Control on the Landfill Site of Municipal Solid Waste (GB16889-2008). All results indicate the great potential of LIBS sensor for online rapid detection of heavy metals in MSWI fly ash.

Two-Dimensional Temperature Measurement in a High-Temperature and High-Pressure Combustor Using Computed Tomography Tunable Diode Laser Absorption Spectroscopy (CT-TDLAS) with a Wide-Scanning Laser at 1335-1375 nm.

Tunable diode laser absorption spectroscopy (TDLAS) technology is a developing method for temperature and species concentration measurements with the features of non-contact, high precision, high sensitivity, etc. The difficulty of two-dimensional (2D) temperature measurement in actual combustors has not yet been solved because of pressure broadening of absorption spectra, optical accessibility, etc. In this study, the combination of computed tomography (CT) and TDLAS with a wide scanning laser at 1335-1375 nm has been applied to a combustor for 2D temperature measurement in high temperature of 300-2000 K and high pressure of 0.1-2.5 MPa condition. An external cavity type laser diode with wide wavelength range scanning at 1335-1375 nm was used to evaluate the broadened H2O absorption spectra due to the high-temperature and high-pressure effect. The spectroscopic database in high temperature of 300-2000 K and high pressure of 0.1-5.0 MPa condition has been revised to improve the accuracy for temperature quantitative analysis. CT reconstruction accuracy was also evaluated in different cases, which presented the consistent temperature distribution between CT reconstruction and assumed distributions. The spatial and temporal distributions of temperature in the high-temperature and high-pressure combustor were measured successfully by CT-TDLAS using the revised spectroscopic database.

Development of a Rapid Coal Analyzer Using Laser-Induced Breakdown Spectroscopy (LIBS).

Determination of coal quality plays a major role in coal-fired power plants and coal producers for optimizing the utilization efficiency and controlling the quality. In this work, a rapid coal analyzer based on laser-induced breakdown spectroscopy (LIBS) was developed for rapid quality analysis of pulverized coal. The structure of the LIBS apparatus was introduced in detail. To avoid time-consuming and complicated sample preparation, a pulverized feeding machine was designed to form a continuously stable coal particle flow. The standard deviation (SD) of characteristic peaks was used to estimate the spectral valid data in this experiment. Coupled with cluster analysis, artificial neural networks and genetic algorithm are employed as a nonlinear regression method in order to indicate the relationship between coal quality and the corresponding plasma spectra. It is shown that the average absolute error of ash, volatile matter, fixed carbon, and gross calorific value for the validation set is 0.82%, 0.85%, 0.96%, and 0.48 MJ/kg. The average standard deviation of repeated samples is 1.64%, 0.92%, 1.08%, and 0.86 MJ/kg, showing a high sample-to-sample repeatability. This rapid coal analyzer is capable of performing reliable and accurate analysis of coal quality.

Optimizing critical parameters for the directly measurement of particle flow with PF-SIBS.

A novel measurement technology named as particle flow-spark induced breakdown spectroscopy (PF-SIBS) was reported for real-time measurement of solid materials. Critical measurement parameters of PF-SIBS were optimized and a set of fly ashes with different carbon content were measured for evaluation of measurement performance. Four electrode materials, tungsten, copper, molybdenum and platinum, were compared in the aspects of signal stability, line interference and electrode durability. Less line interference and better signal stability were obtained with W and Cu electrode, while W electrode has better durability. Quartz sand with diameters from 48 µm to 180 µm were tested to investigate the influence of particle size. As the particle diameter increased, the intensity of Si 288.16 nm line decreased while that of ambient air constituents increased. To reduce the particle effect, the sum intensity from sample and ambient air were introduced to correct. The RSD of line intensity between the five diameters were reduced from 67.30% to 16.59% with Cu electrodes and from 63.21% to 13.64% with W electrodes. With the optimal measurement parameters and correction, fly ash samples with different carbon content were tested and the correlation coefficients R2 of multivariate calibration achieved 0.987.

Development and performance evaluation of self-absorption-free laser-induced breakdown spectroscopy for directly capturing optically thin spectral line and realizing accurate chemical composition measurements.

A novel self-absorption-free laser-induced breakdown spectroscopy (SAF-LIBS) technique is proposed to directly capture the optically thin spectral line by matching the measured doublet atomic lines intensity ratios with the theoretical one. To realize the experimental SAF-LIBS, the integration time, the fiber collection angle, and the delay time are optimized. The optically thin conditions are validated by comparing the linearity of Boltzmann plots with the traditional self-absorption (SA) correction method and evaluating the SA coefficients. The applicability and limitation of SAF-LIBS on element concentration and laser energy are also discussed. Univariate quantitative analysis results show that, compared with ordinary LIBS, the average absolute error of aluminum concentration has been reduced by an order of magnitude, which proves that this SAF-LIBS technique is qualified to realize accurate chemical composition measurements.

[Rapid Measurement of Carbon Dioxide with Laser-Induced Breakdown Spectroscopy Based on Atomic and Molecular Spectrum].

With the rapid development of economy and industrialization, global warming is becoming the most serious sensitive global climate issues, which causes the rising of sea level and many other negative effects. The cause of global warming is the emission of greenhouse gases and carbon dioxide is the main component of greenhouse gases. The control of CO2 emssion is beneficial to addressing gobal climate change and environmental degradation. Therefore, it's important to develop a rapid detection of CO2 for accurate control. There are amounts of methods to detect CO2 at present, including titration, electrochemical method, gas chromatography, infrared absorption spectroscopy and so on, however, t they still have the deficiency for online monitoring in industrial field. laser induced breakdown spectroscopy (LIBS), which is developing rapidly in recent few decades, is a detecting technology with characteristics of time-saving and synchronous measuring of multicomponent. What's more, there is no need for sample pretreating. To develop the online monitoring technique of CO2 emission in the industrial field, LIBS was employed to measure CO2 in this study. The mass flow controller was used to adjust the flow of high purity CO2 and N2 to obtain mixed gas with different CO2 concentrations. The mixed gas was firstly mixed in an air mixing chamber for thorough mixing and then sent to the sample cell for LIBS measurement. The evolution of C atomic spectral line and CN molecular band with different delay times were being studied, which demonstrated parts of CO2 react with air ambient to form CN molecular during the plasma generation, the CN molecular band should be taken into consideration for quantitative analysis, and the parameters were optimized for synchronous measurement of C line and CN band: 800 ns was the optimal delay time. During the plasma generation, many factors in the plasma may interact with others, the analysis index had close relationship wih serval measuring parameters. With the consideration of the effect of C, CN and the self-absorption in high concentration, multivariate calibration method was employed to establish calibration models of CO2. The results showed that the correlation coefficients R2 and the slope were 0.978 and 0.981, respectively. Compared with calibrated with single factor, the multivariate method improved the reliability of the model. What's more, the feasibility of the application of LIBS to measure CO2 rapidly was proved.

[A New Calibrated Model of Coal Calorific Value Detection with LIBS].

A set of coal samples were used for laser-induced breakdown spectroscopy (LIBS) experiment to measure the coal calorific value. Traditional channel normalization method didn't consider the physical / chemical mechanism of coal, which would limit the model in precision, accuracy and repeatability. Thus a new calibrated model based on the kinds of the effects of spectral deviation was proposed in this paper. The model selected 19 groups of coal samples, where the random 15 groups were used to establish quantitative analysis model of calorific value while the remaining four for inspection and evaluation. The model based on spectral deviation factors, and the transmission theory combined with the stark broadening formula was used to deduce the absorption effect mechanism and the deviation correction method under the condition of LIBS. The mutual interference between elements and the mechanism of matrix effect were being analyzed while K coefficient method was used to correct mutual interference between the elements in the LIBS. The establishment of numerical model with the electron density, the plasma temperature and the element concentration was used to deeply corrected spectrum deviation caused by matrix effect. Thus taking into consideration of the effect of self-absorption, interfere of inter-elements and matrix effect, the calibration model was established, while R2=0.967, RMSEP=0.49 MJ·kg-1, RMSE=0.45 MJ·kg-1, MRE=2.42%, ARE=1.64%, RSD=5.79% and RSDP=8.10%. Compared with the 0.405, 8.28 MJ·kg-1, 4.14 MJ·kg-1, 22.85%, 52.48%, 18.28% and 32.85% of traditional channel normalized-multiple linear regression method, it demonstrated that the precision and accuracy have been improved significantly and model has good application value.

[Influence of C-Fe Lines Interference Correction on Laser-Induced Breakdown Spectroscopy Measurement of Unburned Carbon in Fly Ash].

In coal-fired plants, Unburned carbon (UC) in fly ash is the major determinant of combustion efficiency in coal-fired boiler. The balance between unburned carbon and NO(x) emissions stresses the need for rapid and accurate methods for the measurement of unburned carbon. Laser-induced breakdown spectroscopy (LIBS) is employed to measure the unburned carbon content in fly ash. In this case, it is found that the C line interference with Fe line at about 248 nm. The interference leads to C could not be quantified independently from Fe. A correction approach for extracting C integrated intensity from the overlapping peak is proposed. The Fe 248.33 nm, Fe 254.60 nm and Fe 272.36 nm lines are used to correct the Fe 247.98 nm line which interference with C 247.86 nm, respectively. Then, the corrected C integrated intensity is compared with the uncorrected C integrated intensity for constructing calibration curves of unburned carbon, and also for the precision and accuracy of repeat measurements. The analysis results show that the regression coefficients of the calibration curves and the precision and accuracy of repeat measurements are improved by correcting C-Fe interference, especially for the fly ash samples with low level unburned carbon content. However, the choice of the Fe line need to avoid a over-correction for C line. Obviously, Fe 254.60 nm is the best

[Influence of laser energy on measurement of unburned carbon in fly Ash particle flow].

The fly ash particle flow was produced by a screw feeder and then ablated by a pulse laser to create plasma. The emission spectra of fly ash were detected by laser-induced breakdown spectroscopy. The present paper focused on the influence of laser energy on the measurement of unburned carbon. Seven groups of pulse laser in the range of 40 to 130 mJ were used to ablate the fly ash particle flow. The results show that the carbon line intensity is increased linearly with the increases in laser energy, but the SNR of carbon line increases in the range of 40 to 90 mJ and then trends to saturation, while the elimination rate of false data decreases. In this experiment, laser energy ranging from 90 to 100 mJ can enhance the plasma emission signal and improve the true spectral data of fly ash particle flow. So laser energy has close correlations with the ablation of the particle flow and the carbon line intensity. Reasonable laser energy is good for the effective ablation of the fly ash particle flow to get plasma spectra signals with good SNR.

Experimental study of laser-induced breakdown spectroscopy (LIBS) for direct analysis of coal particle flow.

Laser-induced breakdown spectroscopy (LIBS) was employed to directly analyze coal particles in the form of descending flow. Coal-particle ablation was performed using a 1064 nm neodymium-doped yttrium aluminum garnet (Nd : YAG) laser at atmospheric conditions. Spectral identification schemes were used to acquire spectra containing all the emission lines of the important elements in coal. These acquired spectra were classified as representative spectra. The background of the line emission plus three times the standard deviation of the background of the representative spectra was chosen as the threshold value. A method using a single line and a method using combined multiple lines (C, 247.8 nm; N, 746.8 nm; Si, 288.2 nm; and Ca, 396.8 nm) were compared to obtain the best results for the spectral identification of coal particle flow. The feasibility of rejecting the partial breakdown spectra was verified using quantitative analysis of fixed carbon in coal.

[Study of laser energy in multi-element detection of pulverized coal flow with laser-induced breakdown spectroscopy].

The logical range of laser power density and optimum laser power density were explored for multi-element analysis of pulverized coal flow with laser-induced breakdown spectroscopy in the present paper. The range of laser energy was chosen from 20 to 160 mJ in the experiment. Pulverized coal less than 200 microm in diameter of particles fell freely through feeder outlet and the rate of flow was controlled by screw feeder. Emissions were collected with pulse laser at 1 064 nm focusing on pulverized coal flow and plasma was generated. The intensity and cause of fluctuation of emission spectra at various laser energy levels were studied. A suitable range of laser power density is from 14.4 to 34.4 GW x cm(-2), and the optimum laser power density is 19.5 GW x cm(-2) for the determination of pulverized coal flow with LIBS.

[The study on the laser-induced breakdown spectroscopy properties of compound fertilizer with different physical forms].

In order to study the mechanism of laser-induced breakdown spectroscopy for detecting the chemical components content of compound fertilizer in detail, two physical forms of compound fertilizer samples (powder and granular) were used for this study. The authors analyzed the laser-induced breakdown spectroscopy properties of samples with different physical forms made under different preparation pressure. And the spectral characteristics and plasma characteristics of N,P and K in the powder and granules made under the preparation pressure of 0, 0. 5, 2, 4, and 6 MPa, respectively were compared experimentally. The experiments results showed that the spectral characteristics of the two forms have obvious difference when the pressure is small and the grain samples have significant higher line intensity than those of the powder samples. With the increase in the pressure, the difference in the plasma characteristics between these two physical forms was reduced, and all the characteristic spectral lines intensity of the same physical form samples increases firstly and reduces afterward.

Extracting coal ash content from laser-induced breakdown spectroscopy (LIBS) spectra by multivariate analysis.

Laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) analysis has been applied for the quantitative analysis of the ash content of coal in this paper. The multivariate analysis method was employed to extract coal ash content information from LIBS spectra rather than from the concentrations of the main ash-forming elements. In order to construct a rigorous partial least squares regression model and reduce the calculation time, different spectral range data were used to construct partial least squares regression models, and then the performances of these models were compared in terms of the correlation coefficients of calibration and validation and the root mean square errors of calibration and cross-validation. Afterwards, the prediction accuracy, reproducibility, and the limit of detection of the partial least squares regression model were validated with independent laser-induced breakdown spectroscopy measurements of four unknown samples. The results show that a good agreement is observed between the ash content provided by thermo-gravimetric analyzer and the LIBS measurements coupled to the PLS regression model for the unknown samples. The feasibility of extracting coal ash content from LIBS spectra is approved. It is also confirmed that this technique has good potential for quantitative analysis of the ash content of coal.

Experimental study on the characteristics of molecular emission spectroscopy for the analysis of solid materials containing C and N.

Solid materials with different structure containing C and N were analyzed by laser-induced breakdown spectroscopy (LIBS). Comparing the emission molecular species in different atmosphere (air and argon), it can be determined that whether the molecular species are directly vaporized from sample or generated through dissociation or the interaction between plasma and air molecules. The results showed that the characteristic of C2 bands emission is similar with that of neutral atomic carbon emission CI in different atmosphere (air and argon). While the characteristic of CN bands emission is more complicated and it has great relationship with the existence of CN radicals, the interaction between plasma and air ambient, and the recombination of excited partials.

[Application of wavelet transform in laser-induced breakdown spectra compression].

A method based on the wavelet transform (WT) was developed for the compression of laser-induced breakdown coal spectral data. By studing the impacts of main parameters such as the order of db wavelet, decompose level and threshold method on compression performance, it can summarize the compression parameter selection rule and select the proper compression scheme. The scheme was evaluated by compression scores and relative deviation of each spectral line between original and reconstructed. By choosing proper parameters for channel 1, channel 2 and channel 5 of LIBS spectrum of coal sample (No. 1-No. 8), the restore score RS and compress score CS are respectively 81%-92.11% and 79.02%-92.07%, with the spectral line relative deviation under 5%. It indicates that the storage space is reduced while the main characteristic of original spectrum is maintained. The result shows that this method is very effective.