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A spectral transformation strategy based on the dynamic time warping algorithm is proposed to eliminate systematic errors between primary and secondary instruments.

A novel ion-molecule reactor based on traveling wave technology was developed for the first time. The proposed TW-IMR technology opens up a new avenue to enhance the performance of the existing PTR-TOFMS methods.

Benzene compounds that are prevalent in the soil as organic pollutants mainly include BTEX (benzene, toluene, ethylbenzene, and three xylene isomers) and PAHs (polycyclic aromatic hydrocarbons). These pose a severe threat to many aspects of human health. Therefore, the accurate measurement of BTEX and PAHs concentrations in the soil is of great importance. The samples for analysis of BTEX and PAHs need to be suitable for the various detection methods after pretreatment, which include Soxhlet extraction, ultrasonic extraction, solid-phase microextraction, supercritical extraction, and needle trap. The detection techniques mainly consist of gas chromatography (GC), mass spectrometry (MS), and online sensors, and provide comprehensive information on contaminants in the soil. Their performance is evaluated in terms of sensitivity, selectivity, and recovery. Recently, there has been rapid progress in the pretreatment and analysis methods for the quantitative and qualitative analyses of BTEX and PAHs. Therefore, it is necessary to produce a timely and in-depth review of the emerging pretreatment and analysis methods, which is unfortunately absent from the recent literature. In this work, state-of-art extraction techniques and analytical methods have been summarized for the determination of BTEX and PAHs in soil, with a particular focus on the potential and limitations of the respective methods for different aromatic hydrocarbons. Accordingly, the paper will describe the basic methodological knowledge, as well as the recent advancement of pretreatment and analysis methods for samples containing BTEX and PAHs.

Glass beads with improved physical properties were obtained by high-frequency pulse laser fusion of sandstone samples, which improved the stability of the LIBS signal.

By combining a convolutional neural network (CNN) and laser induced breakdown spectroscopy, this study reports a multi-task analysis method to simultaneously solve the problems of lithological recognition and the quantitative analysis of seven major chemical elements in rock analysis.

Catalytic hairpin assembly (CHA) appears to be a particularly appealing nucleic acid circuit because of its powerful amplification capability, simple protocols, and enzyme-free and isothermal conditions, and can combine with various signal output modes for the biosensing of various analytes. Especially in the last five years, vast CHA related studies have sprung up. With the deep exploration of the CHA mechanism, some novel and excellent CHA strategies have been proposed; meanwhile the CHA cascade strategies with various amplification techniques further improve the analysis performance. Furthermore, diverse CHA based biosensors have been tactfully engineered and extensively employed in imaging applications in living cells and

A hybrid method combining discharge-assisted laser-induced breakdown spectroscopy (D-LIBS) with wavelet transform represents a highly promising detection technology for the quantitative determination of trace elements in liquids.

Sensitive and efficient monitoring of food-borne bacteria is of great importance for food safety control. Herein, a novel biosensor for highly sensitive detection of Staphylococcus aureus (S. aureus) was constructed by combining hybridization chain reaction (HCR) and nicking enzyme. Different from the upstream-downstream based circuit, the proposed biosensor integrated HCR circuit and three-way DNA junction nicking enzyme assisted signal amplification (3WJ-NEASA) into a virtuous circle of promotion. In the HCR-mediated 3WJ-NEASA sensing strategy, target DNA of S. aureus initiated the self-assembly between HCR hairpins (H1 and H2), which exposed the gap to capture molecular beacon (MB) and construct the 3WJ structure. Meanwhile, MB increased the stability of HCR nanowires and enhanced the efficiency of the HCR circuit, and thus more 3WJ-NEASA circuits were generated in HCR nanowires. Benefiting from the synergistic amplification coupling HCR and 3WJ-NEASA, this isothermal biosensor can detect as low as 6.7 pM of target DNA in one step within only 30 min. Furthermore, the HCR-mediated 3WJ-NEASA assay has been applied in the detection of S. aureus with a limit of detection (LOD) as low as 1.2 × 101 cfu mL−1, and has exhibited reliable practicability in spiked milk. It is the first time that a DNA biosensor combining HCR and 3WJ-NEASA for dual signal amplification was developed and has been adopted to the sensitive analysis of food-borne bacteria. Additionally, this strategy can serve as a universal platform for monitoring other analytes, and therefore possesses broad application prospects in food safety and environmental monitoring.

As an enzyme-free isothermal amplification strategy, catalytic hairpin assembly (CHA) is a very promising method for cell imaging. However, the practical application of CHA on intracellular miRNA imaging is limited by slow kinetics, insufficient amplification efficiency and strong interference in living cells. Herein, a localized catalytic hairpin assembly-based DNA nanomachine (LCHA nanomachine) was developed for the rapid, efficient and reliable fluorescence resonance energy transformation (FRET) imaging of miRNA-21 in living cells. The nanomachine was simply constructed by a one-step self-assembly process of a stator strand, a pair of hairpin probes from CHA and an AS1411 aptamer. Benefiting from the spatial-confinement effect, a pair of hairpin probes with high collision frequency was rapidly and efficiently assembled using miRNA-21 as the catalyst on a stator strand in every nanomachine. Compared with the free-CHA nanomachine, the LCHA nanomachine shortened the reaction time by 4.5-fold for reaching a plateau and significant improved the sensitivity by 7.6-fold for miRNA-21 detection in vitro. Importantly, the nanomachine was successfully applied for miRNA-21 imaging in living cells. With the assistance of an AS1411 aptamer and stator strand, the pair of hairpin probes with the ratio of 1 : 1 synchronously transported into a co-site of the cytoplasm, which ensures efficient imaging of trace miRNA-21. The signal output of the ratio of 6-carboxy-fluorescein (FAM) to tetramethyl rhodamine (TAMRA) intensities guaranteed reliability through avoiding the interference from different amounts of the nanomachine that enters into cells. Notably, the nanomachine can distinguish the miRNA-21 expression level in different kinds of cancer cells. By virtue of the advantages of simplicity, efficiency and reliability, the proposed strategy provides a powerful method for exploring the functions of miRNA and diagnosis of disease.

In this study, an innovative rapid detection technology for quickly screening and quantifying organophosphorus pesticides (OPPs) in vegetables was developed based on ambient micro-fabricated glow discharge plasma desorption/ionization mass spectrometry (MFGDP-MS), where Fe3O4/ZrO2 synthesized by a one-step coprecipitation was used for enrichment. It can not only effectively enrich OPPs, but can be separated by an external magnetic field, thereby simplifying the traditional steps of centrifugation and cleanup in sample preparation. The introduction of a temperature control system (TCS) can tackle the problem of the low ionization efficiency in MFGDP and expand its application range. Under optimized experimental conditions, the limits of detection (LODs) of the standard solution as low as 0.0068-0.7500 μg L-1 mm-2 were achieved, with relative standard deviations (RSDs) being less than 17.8%. Moreover, vegetable extracts were spiked to evaluate the accuracy of the method, and good recoveries (76.9-123.5%) were obtained. Remarkably, it took no more than 7 minutes from sample preparation to testing, resulting in significantly improved ability of the quantitative detection of plentiful samples.

In recent years, the low sensitivity caused by plasma quenching has restricted the development of LIBS technology in practical applications. In order to improve the sensitivity of the LIBS analysis method, we proposed a nanoparticle-assisted metal–organic framework (MOF) enhanced laser-induced breakdown spectroscopy, which combines a metal–organic framework (MOF), Au nanoparticles (AuNPs), and a portable LIBS instrument. Common metal ions in water were selected as the research objects to be tested by the proposed method. First, the synthesized three-dimensional (3D) MOF, namely [Zn2(L2)]2DMA·3H2O (complex 1) [H2L = 2-(imidazole-1-yl)terephthalic acid], was used to capture metal ions. Second, complex 1 loaded with metal ions induced AuNPs to aggregate on its surface. Third, the samples were attached to the glass substrate with double-sided tape and analyzed by LIBS. As a result, the limits of detection (LODs) for Pb and Cr obtained in this work were 8.0 and 4.2 ng mL−1, respectively, which were notably 8–10 times lower than those of the complex 1 enrichment method alone and 4 orders of magnitude lower than those of traditional LIBS methods. The significant improvement in LODs was also a new breakthrough for LIBS in liquid analysis. The great improvement in sensitivity can be mainly attributed to the unique microporous structure and the exposed metal binding sites of complex 1, which provide a huge space to accommodate metal ions. Also, the coupling action between laser electromagnetic fields and the surface plasmon of AuNPs greatly improved the laser ablation efficiency in the process of laser–matter interaction. Finally, the analysis of actual samples yielded good recoveries (92.8–99.0%) and reproducibility (lower than 11.9%), which shows the great potential of the combination of this method and portable LIBS in-field detection.

Heavy metal ion-induced water pollution has become a severe environmental problem in the world. Although providing a powerful technique for multi-element detection, laser-induced breakdown spectroscopy (LIBS) suffers from insufficient sensitivity for detecting heavy metal ions in aqueous solution due to water splashing and surface ripples. In this work, a simple and sensitive method called gold nanoparticle (AuNP) surface-enhanced laser-induced breakdown spectroscopy (SELIBS) was proposed to detect trace or ultra-trace heavy metal ions in aqueous solutions using a portable instrument. Firstly, the coulombic force allows the adhesion of negatively charged AuNPs and cationic amphiphilic solutions to capture heavy ions, thereby directly improving signal intensity. Interestingly, AuNP size-dependent signal enhancement was found in heavy metal ions through LIBS. To be specific, the signal intensity of Cu, Pb, and Cr increased by 9, 23, and 26 times, respectively, under the optimal AuNP size with a diameter of 13 nm compared to that of the pure target solution. Although the sizes of AuNPs did not affect the plasma temperature and electron density, the local electric field and coulombic force effectively enhanced the LIBS signal. Under optimized experimental conditions, the proposed method achieves sensitive detection of heavy metal ions of Cu, Pb, and Cr with low detection limits (LODs) of 5 ng mL−1, 22 ng mL−1, and 9 ng mL−1, respectively. Moreover, the recoveries of all analytical elements in environmental water samples were analyzed by the standard addition method. The recoveries were in the range of 92.70–100.19%, which further proves the feasibility and potential of surface-enhanced laser-induced breakdown spectroscopy of AuNPs in analyzing actual liquid samples.

Here, we show that molecular N2 was efficiently captured by organic arylium cations in a well-defined manner at ambient pressure and temperature, which was monitored by on-line mass spectrometry analysis. A kinetic picture was proposed to disclose the principle of the ion–molecule reaction behavior for exclusive aryldiazonium production. The observation has an implication for direct nitrogen fixation into an organic framework via the intermediacy of such cationic species.

An enzyme-mediated universal fluorescent biosensor template for rapid detection of pathogens was developed based on the strategy of a three-dimensional (3D) DNA walker and catalyzed hairpin assembly (CHA) reaction. In the bacterial recognition step, a strand displacement reaction between bacteria and the double-stranded complex caused the release of the walker strand. The walker strand triggered the DNA walker to produce an enzyme fragment, and the DNA walker used gold nanoparticles (AuNPs) as the track to provide an excellent DNA ligand anchoring area. In the CHA step, the enzyme fragment induced the CHA cycle to yield fluorescence signals, which greatly enhanced the conversion ratio of trigger DNA and the sensitivity of the fluorescent biosensor. The effect of the distance and density of the DNA ligand was studied by adjusting the length of poly-adenine (PolyA), and was further explored by its reaction kinetics. By comparing the maximum reaction rate (Vmax), Michaelis constant (Km) and turnover number (Kcat), the optimized PolyA probe was assessed and identified. In this work, the optimized PolyA-DNA probe exhibited an outstanding sensitivity in Salmonella typhimurium (S. ty) detection, which is 11.9 times and 4.6 times higher than those of the SH-DNA and the MCH treated SH-DNA. Meanwhile, a detection limit of 28.1 CFU mL-1 was achieved in Escherichia coli (E. coli) detection. Furthermore, the biosensor achieved good selectivity and high repeatability with recoveries of 91%-115% for real sample detection. Considering these advantages, this template has great potential as a routine tool for pathogen detection and has wide applications in the field of global public health and food safety.

Rapid detection and efficient removal of heavy metal ions from environmental water are of considerable importance to tackle the water pollution problem. In this work, a simple but efficient strategy named metal-chelate induced nanoparticle aggregation enhanced laser-induced breakdown spectroscopy (MINAELIBS) was proposed for signal enhancement aiming at ultra-sensitive detection of trace levels of metal elements in liquid samples. Unlike the surface contact approach previously reported in the literature, direct mixing of gold nanoparticles (AuNPs) and metal chelates increased the contact area, adhesion force, and uniformity between analytes and AuNPs. As a result, under the optimal conditions, the limits of detection (LODs) of Cd, Cu, Ag, Pb, and Cr were 4.6, 1.5, 3.4, 3.5, and 3.5 ng mL−1, respectively. The LODs of target elements were notably 7–10 times lower than those of chelating reagent enrichment alone and 3–4 orders of magnitude lower compared to traditional LIBS methods, which demonstrates the feasibility of MINAELIBS in analysis of liquid samples at the ppb level. Application of AuNPs for high-performance signal enhancement has undoubtedly pushed the method sensitivity of traditional LIBS analyses to a new level. In addition, the recoveries of all the analytical elements in the environmental water samples were in the range from 88.6% to 109.9%, which further proves the feasibility and potential of MINAELIBS in practical liquid sample analysis.

As photonic crystals (PCs) are one of the most widely studied artificial biomimetic periodic nanostructures, their preparation methods have attracted significant attention. Recently, several methods have been developed for the self-assembly of PCs at solid and air/water interfaces. However, to date, their self-assembly at a hydrogel interface (HI) with special properties has not been explored and that at an air/gel interface is also rarely reported. Herein, a simple and novel strategy for the rapid self-assembly of PCs using a HI as an assembly interface is demonstrated. This approach is completely different from the preparation strategy of polymerized crystalline colloidal arrays (PCCAs), which involves the entrapment of a colloidal array inside a gel. Unlike the self-assembly at solid or air/water interfaces, the proposed method is faster and simpler and has the ability to prepare three-dimensional (3D) PCs on flat or curved surfaces. The reflection intensity of the hydrogel interface-photonic crystals (HI-PCs) could exceed 80%. Particularly, the transmissivity at a specific wavelength reached as low as 0.1%. Therefore, with the recent progress in the self-assembly of interfaces, soft matter interfaces, such as a hydrogel interface, will play an important new role, which is expected to open up an interesting field of research and provide more ideas for the preparation of advanced materials.

Widespread use of organophosphorus pesticides poses serious environmental threats, and hence calls for effective analysis methods for these classes of compounds. In this study, a lab-made graphene-based solid-phase microextraction (SPME) fiber was fabricated by the sol-gel method and combined with a gas chromatography-flame photometry detector (GC-FPD) to realize the detection of trace OPPs in water samples. Compared to the commercial fiber coatings, the new sol-gel graphene fiber coatings showed advantages of good durability and solvent resistance, which were attributed to the hydrophobic and antibacterial properties of the functionalized graphene and 3-(trimethoxysilyl)propyldimethyloctadecylammonium chloride (QAS). A headspace SPME method in combination with a GC-FPD was established to evaluate the performance of the novel fibers. The proposed method showed a good linear relationship for the eight OPPs (R2≥ 0.9957) in the concentration range of 1 to 1000 μg L-1, with limits of quantification of 0.11-3.37 μg L-1 and limits of detection of 0.03-1.01 μg L-1. Furthermore, the developed method also exhibited good recoveries for the analysis of OPPs both in rainwater and lake water, which demonstrates that this method is an alternative choice for multi-residue analysis of OPPs, and it has the potential for broader applications in the future.

A low-cost and multi-channel smartphone-based spectrometer was developed for LIBS. As the CMOS detector is two-dimensional, simultaneous multichannel detection was achieved by coupling a linear array of fibres for light collection. Thus, besides the atomic information, the spectral images containing the propagation and spatial distribution characters of a laser induced plasma plume could be recorded. With these additional features, accurate rock type prediction was achieved by processing the raw data directly through a deep learning model.

It is crucial to make comprehensive assessments of soil under economic and efficiency requirements in order to guide the rational use of soil resources, including the identification of attributes, the control of pollutants, and the management of nutrients. Laser induced breakdown spectroscopy (LIBS) is excellent for such applications due to its unique advantages of simple preparation, rapid measurement, and multiple-element analysis. An analysis of Si, Al, Mg, Ca, Na, K, Mn, Ba, Ti, Cr, Cu, Sr and P in different standard soils using LIBS is reported here for the comparison of the quantitative results of a univariate regression method (calibration curve) and two multivariate regression methods (partial least squares regression (PLSR) and support vector regression (SVR)). As a result, the correlation coefficients (R2) of the Ca, K, Mg, Na and Sr elements were all greater than 0.90, while the calibration curves of Al, Ba, Cr, Cu, Mn, Ti and P presented poor linear performances with low R2 values of below 0.90. The robustness of the SVR model was superior to the PLSR model with a better prediction ability and a lower relative standard deviation (RSD) for both the training data and the test data, whilst the opposite was observed for the predicted data set used as external verification. The predicted relative errors of the prediction data given by PLSR for all analysis elements except Na and K were lower than those given by SVR. The relative errors of PLSR for Si, Al and Sr were within 10%, while the values for the other elements were between 10% and 20%, and 45% for Cu. It is therefore meaningful to propose a quantitative reference among the univariate linear regression, the multivariate linear regression and the multivariate nonlinear regression methods for the multi-element analysis of soil samples under complex matrix conditions.

Nicking endonucleases, widely applied for signal amplification, have an intrinsic limitation on sequences, as they require specific nucleotide sequences to recognize. Endonuclease IV (Endo IV) recognizes a specific site rather than specific sequences and is used for the first time to amplify colorimetric signals for DNA detection in this work. Our proposed colorimetric sensing platform with Endo IV-aided signal amplification and G-quadruplex-hemin DNAzyme is demonstrated using the human immunodeficiency virus type 1 (HIV-1) DNA as a target model. We designed a visual signal probe containing an apurinic/apyrimidinic (AP) site. In the presence of the targeted DNA, the signal probe turns from “Off” to “On”, and thus the AP site can be recognized and cleaved by Endo IV to circularly release the G-quadruplex DNAzyme sequences for signal amplification. Consequently, color changes related to G-quadruplex DNAzyme can be acquired, which is discernable even with the naked eye. Our proposed sensing platform shows a good ability for detection of the targeted DNA ranging from 2.50 nM to 120 nM, with a limit of detection (LOD) as low as 1.22 nM. This sensing platform also shows a high selectivity towards the targeted DNA. Moreover, the sensing platform has been demonstrated to be potentially useful for the targeted DNA detection in human serum. Considering the good sensitivity and specificity, as well as the intuitive and simple-to-operate features, this sensing platform has a great potential of becoming a routine tool for DNA detection and provides valuable information for biological studies and early clinical diagnosis.

Sample introduction has always been a significant issue in the research of plasma emission spectrometry. In this paper, the continuous direct solid sampling (CDSS) technique, a novel and alternative technique for direct solid analysis based on microwave plasma atomic emission spectrometry (MWP-AES), was firstly proposed. By allowing the plasma column to directly interact with the solid sample surface, the sample was heated and melted, and the elements in the sample were atomized and excited continuously. With the help of multivariate analysis, elements including Corg, Cu, Pb and Cr in geological samples were qualitatively and quantitatively determined. To construct a robust and accurate support vector regression (SVR) model, spectral bands consisting of characteristic lines and adjacent noise zones were selected as input variables. The penalty parameter C and the key parameter of the radial basis function (RBF) were optimized to be 16.0453 and 2.9008, respectively. The optimized model showed satisfactory results with a linearity correlation coefficient R2 better than 0.99 and RSD lower than 11.08% for all target elements. The proposed CDSS technique can be used to successfully conduct direct solid analysis, avoiding the use of chemical reagents, which makes it green and environmentally friendly. The total analysis time can cost less than half a minute, indicating that the proposed method can be promising in high throughput and rapid analysis. What is more, the CDSS technique combines sampling, atomization and excitation together, which eliminates the use of an electrothermal vaporization or laser ablation unit when analyzing solid samples directly using MWP-AES. The proposed method opens a promising and alternative door for plasma spectrometry especially for MWP-AES due to the advantages of continuous direct solid analysis, rapid analysis speed, no or minimal sample pretreatment, and a simplified analytical system, which is suitable for in situ and field analysis.

Laser-induced breakdown spectroscopy (LIBS) has been gradually adopted as a quantitative technique for metallurgy analysis in recent years. However, the accuracy and efficiency of quantitative analysis is still a challenge. In this work, a novel method is proposed to achieve precise in situ composition prediction, based on wavelet packet transform (WPT) and relevance vector machine (RVM). We discuss the difference in LIBS spectral features extracted by the traditional method and WPT, as well as the absolute error of prediction and the mean relative error used as measurement criteria. The analysis results showed that the WPT method of extracting spectral features was more effective than the traditional method. Besides, for predicting the elemental compositions of the regression model, a better performance was obtained using RVM with a modified Laplacian kernel function (MRVM). The mean values of the root mean square error prediction (RMSEP) of MRVM, the calibration curve, RVM, and support vector machine were 0.159, 0.210, 0.303 and 0.179, respectively. Analysis results demonstrated that MRVM possessed superior efficiency, generalization ability and robustness for accurate and reliable compositional prediction. We thought that the proposed algorithm combined with LIBS can be used in real-time composition monitoring of steel samples.

We fabricate a high-efficient ion source for real time on-line monitoring of trace compounds in ambient air by introducing a weak longitudinal magnetic field to a micro-fabricated DC glow discharge. Mass spectrometric detection of various samples indicates that the signal intensity increases by an order of magnitude and the limit of detection can be lowered to 1/10 of the original level. This improvement results from the increasing ion transport efficiency through the magnetic confinement.

Laser-induced breakdown spectroscopy (LIBS) is becoming a rapid and easy technique for quantitative elemental analysis. However, the implementation of accurate quantitative LIBS analysis is always subject to noise interference. In this work, in order to improve LIBS analysis performance for trace elements in aluminium alloys, a modified trade-off soft and hard threshold method is proposed based on the wavelet theory, where optimal parameters are deduced to eliminate noise interference. By using the modified algorithm combined with an Al I line at 308.215 nm as an internal standard, the statistical parameters including the determination coefficient (R2), the root mean square error (RMSE) and the relative standard deviation (RSD) of magnesium (Mg), manganese (Mn) and cuprum (Cu) in aluminium alloys are all significantly improved. The most significant improvement of R2 is 0.066 for Cu. The maximum RMSE reduction value is 0.583 for Mg, and the mean value of RMSE reduction is 0.261 for all three trace elements. And after de-noising, the value of RSD gets smaller for each trace element. Such results indicate that the optimized algorithm is valid for the effective improvement of the accuracy of quantitative LIBS analysis in the trace element determination of aluminium alloys.

Concomitant findings of acetone (ACE) and isopropanol (IPA) in blood and other biological samples have been reported in diabetic decedents and clinic cases, but exhaled IPA has rarely been studied in breath research. This study aimed to investigate expression of exhaled IPA in diabetes and further explore the correlations between exhaled IPA and ACE, and to evaluate diabetes diagnostic applicability of exhaled IPA in combination with ACE. Exhaled breath samples at one time point from 85 type 2 diabetic patients and 56 healthy controls, and from four healthy individuals after ketogenic diet experiments were analyzed by gas chromatography mass spectrometry coupled with solid phase micro-extraction technique. Concentrations of exhaled IPA in the diabetic group (mean 85.44 ppbv) were significantly higher than those in the healthy group (mean 17.99 ppbv, p < 0.001). Ketogenic diet experiments showed that both IPA and ACE levels were elevated after keto-meals when under fat-consuming metabolic states. And they shared a similar changing pace, even though there was no linear relationship between IPA and ACE in terms of concentrations. The Spearman Correlation Coefficient between exhaled IPA and ACE in diabetes was 0.66, which indicated that IPA and ACE were metabolically correlated. ROC curve analysis showed that IPA possessed promising discriminatory ability (AUC 0.86) with a sensitivity of 75.3% and a specificity of 85.7% for diabetes diagnosis. This research indicates that endogenously produced IPA is a valuable biomarker for noninvasive diabetes diagnosis in breathomics analysis. This work also addressed the speculation that IPA can be metabolized from ACE via the reversible action of alcohol dehydrogenase.

Laser-induced breakdown spectroscopy (LIBS) is a simple, fast, and direct technique for the elemental analysis of various samples. However, the practical application of this method in direct liquid analysis is limited due to its inherent disadvantages including surface ripples and extinction of emitted intensity. Applicable treatments of liquids always involve complicated procedures or additional instruments, which is disadvantageous to its analytical performance. In this study, we proposed a novel method for the LIBS analysis of liquid samples via a hydrogel-based solidification technique. In this new method, aqueous solution is directly poured into sodium polyacrylate resins. Owing to the high hydroscopicity of sodium polyacrylate resins, the resins quickly form a hydrogel and immediately solidify the liquid samples. After this, the LIBS analysis is directly performed. To estimate the analytical performance of this proposed method, calibration curves were established and limits of detection for Al, Cu, and Cr were obtained. The limits of detection (LODs) for the emission lines of Al(I) 308.21 nm, Cu(I) 324.75 nm, and Cr(I) 425.43 nm were 0.460 μg mL−1, 4.69 μg mL−1, and 4.44 μg mL−1, respectively. According to the obtained results, this proposed method demonstrates its better analytical performance in terms of LODs at the ppm level and requires shorter processing time as compared to other analytical methods based on the LIBS technique for liquid sample analysis. Especially, the short pretreatment of samples and simple auxiliary equipment make this hydrogel-based solidification method bring LIBS out of the laboratory for the direct analysis of environmental liquid samples. The feasibility and potential of this novel method have also been discussed for special analytical applications in slurry samples.

A novel and simple experimental system was designed in the present work for real-time particle analysis using a laser-induced breakdown spectroscopy (LIBS) technique without time-consuming pretreatment processes, which can also effectively avoid inherent difficulties such as particle splashing during the particle LIBS analysis. In addition, the advantages of this novel and simple experimental system, including being simple and fast, are in conformity with the characteristics of the LIBS technique. In this study, Geochemical Standard Reference Soil particles were selected as the samples for demonstrating the novel analytical method. The soil samples were transferred to an adsorption plate via argon gas and the adsorption plate was placed on a two-dimensional rotating stage. Owning to good stickiness, the adsorption plate can hold a large number of particle samples, and the rotating stage ensures that each laser pulse shoots on a fresh target surface, which can effectively improve the accuracy during the LIBS analysis. To verify this novel analytical method, the calibration curves for titanium (Ti) and magnesium (Mg) were obtained. Under the optimized conditions, the limits of detection (LOD) for Ti and Mg in soil samples using this system are 124.571 μg g−1 and 0.0126%, respectively. The results show that the novel method designed in the present study is a feasible option for analyzing metallic elements in particle samples using the LIBS technique and could have potential applications for practical and online analysis.

Many reports have focused on breath analysis of breast cancer patients. However, only a few studies have investigated biomarkers through volatile organic components (VOCs) analysis in vitro. The aim of this work is to investigate the volatile organic components fingerprint of human breast cancer cell lines and human normal mammary cells and explore potential VOCs biomarkers for noninvasive diagnosis of breast cancer. MCF-7, MDA-MB-231 and CCD-1095Sk cell lines were employed in this work. Five biological replicates of each cell type were prepared for analysis. Gas chromatography and mass spectrometry (GC-MS) combined with solid-phase microextraction (SPME) was used to detect the VOCs released from the target cell lines. AMDIS-Spectconnect and metabolomic analysis were performed to process the data. According to the results, each kind of cell line shows a unique chromatogram. By applying Principal Component Analysis (PCA), Partial Least Squares Data Analysis (PLS-DA), four components, including 2-ethyl-1-hexanol, 2,4-dimethyl-benzaldehyde, cyclohexanol and p-xylene, were found to be potential biomarkers for discriminating breast cancer cell lines of the HER negative subtype and normal mammary cell line. The combination of the four components was more appropriate for the clinical diagnosis of breast cancer. The study indicated that the VOC profiles of breast cancer cell lines and human normal mammary cell lines were quite different and the investigated biomarkers may hold promise for non-invasive diagnosis of breast cancer.

A novel method with high sensitivity was developed for determining ultra-trace-amounts of metallic elements in liquids by LIBS analysis, based on crosslinked polyvinyl alcohol (PVA) supporting material. In this newly proposed approach, an aqueous solution sample was intensively mixed with PVA solution leading to phase conversion, which is distinguished from the desiccation process on a solid supporter as reported in the literature of liquid-to-solid conversion for LIBS analysis. The analytes were distributed in a thin PVA film (0.34 mm) as a result of crosslinking the polymer materials, and thereby the plasma signals generated by laser pulse were stronger and a lower amount of solid supporter was needed compared to traditional methods. Due to the low PVA thermal decomposition temperature, laser generated plasma energy was effectively utilized for not only ablating the sample, but rather exciting analytes within the sample. The limits of detection for Ag, Cu, Cr, Pb, Ni, Co and Cd obtained in this study were 1 ng mL−1, 8 ng mL−1, 16 ng mL−1, 1 μg mL−1, 1 μg mL−1, 2 μg mL−1 and 5 μg mL−1, respectively, which showed great improvement compared with those from direct liquid analysis by LIBS. The satisfactory figures of merits of the proposed method, including linearity, reproducibility and accuracy, were also obtained with the optimal experimental parameters. This unique method takes advantage of mixing an aqueous solution sample with supporter material in a liquid phase and it has characteristics of fast, simple and sensitive analysis for liquid sample compared with conventional liquid-to-solid conversion methods for LIBS.

A simple, label-free and cost-effective localized surface plasmon resonance (LSPR) immunosensing method was developed for detection of alpha-fetoprotein (AFP). The U-bend fiber optic probe was firstly pretreated by microwave-induced H2O/Ar plasma to ensure better silanization, which could greatly improve the adsorbed amounts and uniformity of the gold nanoparticles (GNPs) on the fiber optic probe surface. Furthermore, according to the sucrose refractive index (RI) testing result, the absorbance sensitivity to RI change of this sensor was obviously improved due to the plasma pretreatment. Finally, on the basis of this U-bend strategy and plasma pretreated method, the fabricated biosensor displayed good analytical performance for detection of AFP, ranged from 5 to 200 ng mL−1 in both phosphate-buffered saline (PBS) and human serum, with different detection limits of 0.85 and 3.3 ng mL−1 respectively. Therefore, the present strategy definitely paves a way for wider applications of LSPR in clinical research and may eventually become a promising technique for protein detection.

Laser-induced breakdown spectroscopy (LIBS) integrated with random forest (RF) was developed and applied to the identification and discrimination of ten iron ore grades. The classification and recognition of the iron ore grade were completed using their chemical properties and compositions. In addition, two parameters of the RF were optimized using out-of-bag (OOB) estimation. Finally, support vector machines (SVMs) and RF machine learning methods were evaluated comparatively on their ability to predict unknown iron ore samples using models constructed from a predetermined training set. Although results show that the prediction accuracies of SVM and RF models were acceptable, RF exhibited better predictions of classification. The study presented here demonstrates that LIBS–RF is a useful technique for the identification and discrimination of iron ore samples, and is promising for automatic real-time, fast, reliable, and robust measurements.

In this work, a single-beam-splitting laser-induced breakdown spectroscopy (LIBS) technique using one single laser system is demonstrated. An individual pulse delivered by a laser (1064 nm wavelength) was split into two sub-pulses by a beam splitter. Various copper alloy standard disks were used in this investigation. Intensity enhancement of emission lines under different laser energies was investigated and the maximum enhancement of 2.1 was reached with 30 mJ laser energy. Under this optimal condition, quantitative analysis based on single-beam-splitting ablation with a calibration-free (CF) method was performed and a better analytical result than that obtained based on single-pulse CF-LIBS was acquired. With combined internal reference for the self-absorption correction (IRSAC) method and calibration-free inverse method, the analytical results agreed well with the certified values of the elements in the sample, with an accuracy error between −17% and +12%.

Laser Induced Breakdown Spectroscopy (LIBS) is attracting more and more attention in geology fields because of its unique advantages of on-line and in situ analysis and the availability of portable even handheld instruments due to the development of laser sources and mini-spectrometers. However, parameters such as accuracy and precision of the instrument are still essential for field application. In this paper, two algorithms to determine the concentrations of five main elements (Si, Ca, Mg, Fe and Al) in sedimentary rock samples are proposed based on support vector regression (SVR) and partial least squares regression (PLSR). The proposed comparison demonstrates that the SVR model performed better with more satisfactory accuracy and precision under the optimized conditions. For SVR quantitative analysis, the spectral features (20 lines) without principal component analysis (PCA) were selected as the input variables. The optimized penalty parameter C and the key parameter of the radial basis function (RBF)-σ obtained by genetic algorithm (GA) were 4.63 and 0.9159, respectively. Also, the best number of the principal components of PLSR was optimized to be 8 by 10-fold cross-validation (CV) testing. Furthermore, the accuracy corresponding to the average relative standard deviations (RSDs) and the precision related to the root mean square error (RMSE) were calculated according to the performance of the two regression models. A significant enhancement of accuracy, of up to 43.50 times, and of precision, of 7.19 times, for the SVR model was obtained, which can eliminate the self-absorption of plasma efficiently compared with the linear machine learning method PLSR. In conclusion, the chemometric method of SVR with better accuracy and precision can be successfully applied for the quantitative analysis of complex geological samples using the LIBS technique.

Ambient ion sources for mass spectrometry have been frequently reported in the past 10 years. The most attractive features of these ion sources are that they are fast and an easy way to analyze various samples. The microwave induced plasma desorption ionization source, the MIPDI source, is one among them. In this study, the qualitative and quantitative behavior of the MIPDI source has been demonstrated by analyzing the preservatives in cosmetics for the first time. The detection limit for the preservatives is as low as pg mm−2. The relative standard deviation of continuous analysis is 5.25%. Preservatives in commercial cosmetics samples were successfully detected including those in facial cream, sunscreen and moisturizer. The fast screening capability of the MIPDI source is proved. Five commercial samples were successfully classified into two groups within 5 minutes according to the added preservatives. The ability to quantitatively analyze the preservatives in commercial cosmetics was also investigated. The standard adding and calibration curve methods were used in the quantitation process. The results showed that the quantitative analysis accuracy of MIPDI-MS is −49% and −66% for a liquid state sample and solid state sample respectively, i.e. semi-quantitation is possible. A conceptual experiment was also conducted to validate the accurate quantitative analysis capability of MIPDI-MS. The concentration of caffeine in cosmetic matrices was quantified satisfactorily with no sample pretreatment, with an RSD value of 5.5% and accuracy of 3.6%. The approaches established in this work indicate that the MIPDI source is a promising tool in future applications where rapid qualitative and quantitative analysis is needed.

In this study, a facile, ultrasensitive and interference-free method to detect cefalexin (CEX) was developed for the first time. This assay was carried out by covalently immobilizing cefalexin–ovalbumin (CEX–OVA) on high specific surface area amorphous nanoparticles of superparamagnetic iron oxide (SPIO). Here, the SPIO–CEX–OVA structure was rich in antibody domains for competitive immunological recognition to anti-CEX antibody and to AlexaFluor 488 labeled goat anti-mouse IgG. Compared with traditional laser induced fluorescence detection, the introduction of SPIO can preconcentrate analytes to reduce the detection limit and greatly shorten the assay time. A pulsed laser with higher peak energy was chosen as the excitation source for generating strong fluorescence signals and to improve sensitivity. The detection limit was 0.34 ng mL−1 with linearity in the range of 0.5 ng mL−1 to 50 ng mL−1, and the IC50 was 1.7 ng mL−1. The accuracy and reproducibility were determined by using spiked milk samples with three different concentrations of CEX (5, 20 and 50 ng mL−1). The recoveries of 85.2–111.4% were obtained with relative standard deviations of 5.3–9.1%, respectively. These results indicate that the method provides a pragmatic platform for convenient detection of small molecular residues due to its high sensitivity, selectivity and short assay time.

The aim of the study was to apply gas chromatography-mass spectrometry (GC-MS) combined with a metabolomics approach to identify distinct metabolic signatures of type 2 diabetes mellitus (T2DM) and healthy controls from exhaled breath, which are characterized by a number of differentially expressed breath metabolites. In this study, breath samples of patients with type 2 diabetes mellitus (T2DM, n = 48) and healthy subjects (n = 39) were analyzed by GC-MS. Multivariate data analysis including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) was successfully applied to discriminate the T2DM and healthy controls. Eight specific metabolites were identified and may be used as potential biomarkers for diagnosis of T2DM. Isopropanol and 2,3,4-trimethylhexane, 2,6,8-trimethyldecane, tridecane and undecane in combination might be the best biomarkers for the clinical diagnosis of T2DM with a sensitivity of 97.9% and a specificity of 100%. The study indicated that this breath metabolite profiling approach may be a promising non-invasive diagnostic tool for T2DM.

A direct current glow discharge microplasma source permits ambient ionization directly and can provide fast and accurate in situ detection combined with a spectrometer. In this study, a stable microplasma-based detector for nerve agent detection has been developed. The innovative concept of this new nerve agent detector is to detect two parts of the nerve agent components, the element phosphorus and the organic part, CH radicals, at the same time. Because there are two detection targets, our microplasma-based detector has enhanced selectivity for nerve agents. The reasons for this characteristic are studied through comparing the emission spectra of the microplasma and microwave plasma. We suggest that it's the very low gas temperature of our microplasma source that makes it possible to excite the nerve agent molecules without decomposition or splitting of the CH component. Thus the spectrometer can detect the emission lines of the element phosphorus and the organic CH radicals simultaneously. The influence of discharge current and gas flow rate on phosphorus signal intensity has been investigated. The emission intensity of phosphorus at 253.6 nm increases linearly with the discharge current in our tested range, but non-linearly with the gas flow rate. The detection curve has been calibrated. The emission intensity at 253.6 nm is in proportion to the concentration of the specimen triethyl phosphate (TEP) in the range from 41 ppm to 500 ppm by volume. The detection limit was calculated to be 5 ppm by volume. Small size, low power, low cost, and high selectivity make our device very suitable for nerve agent scanning in the field.

A novel method based on laser induced breakdown spectroscopy (LIBS) and random forest regression (RFR) was proposed for the quantitative analysis of multiple elements in fourteen steel samples. Normalized LIBS spectra of steel with characteristic lines (Si, Mn, Cr, Ni and Cu) identified by the NIST database were used as analysis spectra. Then, two parameters of RFR were optimized by out-of-bag (OOB) error estimation. The performance of the calibration model was investigated by different input variables (the whole spectral bands (220–800 nm) and spectra feature bands (220–400 nm)). In order to validate the predictive ability of the multiple element calibration RFR model in steel, we compared RFR with partial least-squares (PLS) and support vector machines (SVM) by means of prediction accuracy and root mean square error (RMSE). Thus, the RFR model can eliminate the influence of nonlinear factors due to self-absorption in the plasma and provide a better predictive result. This confirms that the LIBS technique coupled with RFR has good potential for use in the in situ rapid determination of multiple elements in steel and even in the field of metallurgy.

Every few years, a novel material with salient and often unique properties emerges and attracts both academic and industrial interest from the scientific community. The latest blockbuster is graphene, an increasingly important nanomaterial with atomically thin sheets of carbon, which has become a shining star and has shown great promise in the field of material science and nanotechnology. In recent years, it has changed from being the exclusive domain of physicists to the new passion of chemists and biologists. Graphene and its derivatives are now at the forefront of nearly every rapidly developing field of science and engineering, including biochemistry, biomedicine and certain cutting-edge interdisciplines that have intense popularity. The aim of this review is, firstly, to provide readers with a comprehensive, systematic and in-depth prospective of graphene's band structure and properties, and secondly, to concentrate on the recent progress in producing graphene-based nanomaterials, including mechanical exfoliation, chemical vapor deposition, plasma enhanced chemical vapor deposition, chemical reduction of graphene oxide, total organic synthesis, electrochemical synthesis and other fabrication strategies widely accepted by research scientists. At the same time, important definitions related to graphene are also introduced. The focus of this Tutorial Review is to emphasize the current situation and significance of using this new kind of two-dimensional material in the hot and emerging fields that are closely related to human life quality, for instance, cell biochemistry, bioimaging along with other frontier areas. Finally, the latest developments and possible impact that affect the heart of the whole scientific community have been discussed. In addition, the future trends along with potential challenges of this rapidly rising layered carbon have been pointed out in this paper.

Operation of a helium-based low-power microwave plasma under “off-cone” sampling mode can lead to significant background suppression without sacrificing the analyte signal intensity. The nearly clean background spectrum obtained with “off-cone” sampling provides a unique approach for isotope ratio measurements, especially for low-mass elements that are often problematic. In this work, calcium isotopes and isotope ratios are quantitatively measured using “off-cone” sampling with microwave plasma time-of-flight mass spectrometry. The viability of measurements for all calcium isotopes, from the most abundant isotope (40Ca) to the least abundant isotope (46Ca), has been established for this technique. Several calcium isotope ratios are measured and calculated through both elemental calcium ion peaks and molecular calcium ion peaks. The relative standard deviations (RSD) for isotope ratios measured are in a range of 1.2 to 2.5% for commonly used major calcium isotopes. The absolute measurement errors are around 0.8% or less in most cases for major isotopes.

The research objective of this work is to develop a new type of ion source for elemental mass spectrometry. In this work, a simple glow discharge (GD) device has been set up and coupled with a microwave induced plasma (MIP) source to form a so-called 'tandem source'. In the tandem source, the first source (GD) serves to provide free sample atoms produced by cathode sputtering and partial ionization, and the second source (MIP) serves to enhance the ionization of the free atoms. Since MIP is ordinarily even farther from local thermal dynamic equilibrium than other plasmas, it would seem to be best used in conjunction with another source that is capable of more efficient sample atomization, such as glow discharge. The design and construction of such a tandem source has been performed in our laboratory, and the source has been coupled to a self-assembled time-of-flight mass spectrometer (TOFMS). Primary examinations of operational parameters are pursued. Significant signal enhancement is observed with a microwave power of 15 W, discharge voltage around 420 V, and working pressure of 2.0 Torr. The analytical performance of the new tandem source with and without microwave discharge boosting is compared. Some synergistic benefits derived from the tandem source are discussed. For the isotopes studied, enhancement factors of 3–4 are achieved.

The major application of the laser-induced breakdown spectroscopy (LIBS) technique had been in the analysis of solid samples because the measurement of LIBS for liquid samples experiences some experimental difficulties, such as splashing, a quenching effect, and a shorter plasma lifetime. In the present work, electrospun ultrafine fibers were explored and used for the first time as a solid-phase support to quantify chromium (Cr) and copper (Cu) in aqueous solutions by LIBS. The liquid sample was first transferred to an ultrafine fiber surface, which could minimize the drawbacks of liquid sample analysis with LIBS. Due to the special micro-porous structure, the electrospun ultrafine fibers could hold a larger liquid sample and also the liquid sample was easy to evaporate. On the other hand, as a polymer substrate, the porous electrospun ultrafine fibers contributed to the minimal blank since there was no other unwanted heavy metal matrix that affected the detection during the liquid LIBS analysis. Meanwhile, the large sampling spot to fiber diameter ratio will minimize the potential influence generated in the liquid sample distribution process. With this pre-treated sample technique, the sensitivities of LIBS for liquid samples are improved considerably and the detection limits for Cr and Cu reached 1.8 ppm and 1.9 ppm, respectively. Therefore, the present strategy definitely paves the way for a wider application of LIBS in liquid sample analysis.

In the present research, dispersive solid phase micro-extraction was combined with laser induced breakdown spectroscopy for the first time to achieve matrix conversion and preconcentration of Ag+, Mn2+ and Cr3+ in liquid samples. Nano-graphite was selected as a novel adsorbent due to its superior adsorption ability, water solubility and lower cost compared with carbon nanotubes and graphene. Sodium diethyldithiocarbamate was used as a complexing reagent to enhance the interaction between nano-graphite and metal ions. After adsorption, the nano-graphite powder was immobilized by mixing with commercial epoxy adhesive before LIBS analysis instead of the traditional tableting method to solve the problem that some carbonaceous materials are difficult to be tableted. Under optimized experimental conditions, the calibration curves were built in the range of 0.1–1.2 mg L−1 and good linearity (R squared better than 0.980 for all of the three target elements) can be obtained. The detection limits of Ag+, Mn2+ and Cr3+ were 16.59 ng mL−1, 10.85 ng mL−1 and 9.51 ng mL−1 respectively. In real sample analyses, the recoveries of three elements at different concentration levels were all in the range of 92.66–105.80% and the relative standard deviations of parallel samples were less than 8.98%.

Recent experimental and industrial advances in the field of nanotechnologies have boosted the development of interdisciplinary research, one of the most constructive and inspiring of human pursuits. Many scientists specialize in manufacturing new forms of nanomaterials that hold promise for various applications such as medical diagnosis and therapy, environmental monitoring, energy production and storage, molecular computing and much more. Graphene, an increasingly important nanosized material reported in 2004, has emerged to become an exciting two-dimensional material with distinct attributes that has attracted great interest in the fields of physics, chemistry, biology and medicine, as well as their related interdisciplinarities. The unique nature of graphene makes it stand out and applicable to various technologies. Its photoelectric properties and inherent Raman spectroscopy make it an ideal candidate for the development of new devices and methods in many branches of life sciences and technology. The electronic properties of graphene make it a highly useful nanomaterial. It carries a high charge mobility which allows it to be extensively applied to field effect transistors. Graphene also has unparalleled transparency and conductivity, making it a viable electrode in solar cells. In addition, the specific area of graphene makes energy storage possible. Although these properties are inherent to the compound, graphene can also be modified into a better nanomaterial. Due to its outstanding performance, graphene development shows great promise in several scientific fields. This paper aims to elaborate on the details of current studies using graphene with regards to the optical and electronic characteristics, fabrication techniques, and various relevant applications.

A low-power, portable dc microplasma source has been developed for use in molecular emission spectrometry. The device employs a 450 nL plasma chamber in which an atmospheric pressure dc glow discharge is generated with argon gas. The discharge ignites spontaneously when the system is operated at dc input power of 0.95–6.5 W and gas flows of 100–2500 mL min−1. Two sample introduction modes are used to enable direct analysis of gaseous and liquid samples. The detection of volatile organic compounds was achievable via the emissions from CN at 387.15 nm, CH at 431.41 nm and C2 at 516.53 nm. Under the optimized experimental conditions, the limit of detection (LOD) down to ppb (v/v) level can be achieved. These detection limits are competitive to or better than those of other microfabricated plasma devices. More importantly, the effect of organic compound structure on emission response is systematically studied. It was found for the first time that the ratio of C2/CH emission is closely associated with the ratio of hydrogen to carbon atoms (H/C) in a molecule, which might be potentially used for direct semi-qualitative analysis of organics. The dc microplasma detector possesses the advantages of simple construction, high sensitivity, low power consumption, long lifetime, and potential for portability in mass reduction and instrumentation.

The plasma-cavity ringdown spectroscopic (Plasma-CRDS) technique has been demonstrated as a powerful tool for elemental and isotopic measurements in recent studies. This work reports the first application of plasma-CRDS to measurements of elemental mercury and its stable isotopes at the 254 nm transition under atmospheric conditions. A microwave-induced plasma (MIP) operating at 80–100 W is used to generate Hg atoms from standard HgCl2 solutions diluted by 2% nitric acid solvent. It is found that a background absorption, attributed to the overlap of two broadened rovibrational transitions R21(21) and P1(15) of the OH A-X (3-0) band located at 253.65 nm, generates significant spectral interference with the absorption peak of Hg at 254 nm. With an optimized operating condition, including plasma powers, gas flow rates, and laser beam positions in the plasma, the detection sensitivity of Hg is determined to be 9.1 ng ml−1 in aqueous solution, equivalently 221 pptv in the gas phase; this detection limit is approximately 2-fold higher than the theoretical detection limit, 126 pptv, which was estimated by using the parameters of the instrument system and the calculated absorption cross-section, 2.64 × 10−14 cm2 atom−1, of the transition under atmospheric plasma conditions. High-resolution spectral scans show a clear contour of the stable isotopes of the 254 nm transition. The technical challenges encountered and the potential for further development of the Hg analyzer using the MIP-CRDS technique are discussed.

An electrothermal vaporization device has been designed for use in sample introduction and this has been coupled with microwave-induced plasma atomic absorption spectrometry (ET-MIP-AAS). Various vaporization chambers were tested to minimize the turbulence and the dead volume. A series of experimental parameters were examined and optimized. Some influences, such as concomitant element and easily ionized element (EIE) effects, which are commonly encountered in microwave-induced plasma atomic emission spectrometry were investigated. The analytical figures of merit for ET-MIP-AAS are discussed. The characteristic concentrations obtained in this work were found to be at the ng ml–1 or higher level. The precision for the determination of Ca, Ag and Cu was shown to be in the range 5.6–7.8%. The recommended method was also used to analyse real samples, and satisfactory results were obtained.

A low-powered argon microwave plasma torch discharge is introduced into atomic fluorescence spectrometry (AFS) for the first time. The configuration and the characteristics of the plasma for AFS are described in this paper. Some factors influencing the determination of mercury, such as the flow rates of the carrier gas and the plasma gas, are discussed in detail. The detection limit for mercury by this method is shown to be 3 ppb and the relative standard deviation for a solution concentration of 1 µg ml–1 is 2.5%(n= 11). The proposed method is relatively free from background interference and gives a large dynamic range.