Laser-induced breakdown spectroscopy of archaeological findings with calibration-free inverse method: Comparison with classical laser-induced breakdown spectroscopy and conventional techniques

A modified version of the calibration-free (CF) method was applied to the analysis of a set of archaeological brooches made of various copper-based alloys and coming from the archaeological site of Egnatia (Apulia, Southern Italy). The developed methodology consists in determining the plasma temperature by reversing the set of equations employed in the usual CF algorithm, and it is thus referred to as “inverse method”. The plasma temperature is determined for one certified standard, by using its known elemental composition as an input data, and then applied to the set of unknown samples to evaluate their composition in a CF mode. The feasibility of such an approach is demonstrated by comparing the results obtained with classical LIBS (drawing calibration lines with a series of matrix-matched certified standards) and with independent measurements performed with a conventional technique (LA-ICP-MS).     

Comments on the paper: “Accurate quantitative analysis of gold alloys using multi-pulse laser-induced breakdown spectroscopy and a correlation-based calibration method”

The problem of finding new methods for the analysis of precious alloys has stimulated, in recent years, a number of different proposals for improving the analytical procedures introducing more robust calibration (or calibration-free) methods. In the paper “Accurate quantitative analysis of gold alloys using multi-pulse laser-induced breakdown spectroscopy and a correlation-based calibration method” by G. Galbács, N.Jedinski, G.Cseh, Z. Galbács and L. Túri [Spectrochimica Acta Part B, Volume 63, Issue 5, 591–597 (May 2008)] the authors proposed the use of multiple-pulse LIBS and a correlation-based method for building calibration curves for quantitative analysis of gold alloys. The method is proposed for gold alloys prepared using a fixed proportion of the alloying element. The general case where the relative concentration of the elements of the matrix is not a priori known is not discussed in the paper. In this communication, we will demonstrate that the method proposed is extremely fragile against matrix effects, and therefore cannot be usefully applied for the purpose of actual analytical measurements on gold alloys without a previous knowledge of the matrix composition.     

Classical univariate calibration and partial least squares for quantitative analysis of brass samples by laser-induced breakdown spectroscopy

In this work we compare the analytical results obtained by traditional calibration curves (CC) and multivariate Partial Least Squares (PLS) algorithm when applied to the LIBS spectra obtained from ten brass samples (nine standards of known composition and one ‘unknown’). Both major (Cu and Zn) and trace (Sn, Pb, Fe) elements in the sample matrix were analyzed. After the analysis, the composition of the ‘unknown’ sample, measured by X-ray Fluorescence (XRF) technique, was revealed. The predicted concentrations of major elements obtained by rapid PLS algorithms are in very good agreement with the nominal concentrations, as well as with those obtained by the more time-consuming CC approach. A discussion about the possible effects leading to discrepancies of the results is reported. The results of this study open encouraging perspectives towards the development of cheap LIBS instrumentation which would be capable, despite the limitations of the experimental apparatus, to perform fast and precise quantitative analysis on complex samples.     

A comparative study of laser induced breakdown spectroscopy analysis for element concentrations in aluminum alloy using artificial neural networks and calibration methods

A comparative study of analysis methods (traditional calibration method and artificial neural networks (ANN) prediction method) for laser induced breakdown spectroscopy (LIBS) data of different Al alloy samples was performed. In the calibration method, the intensity of the analyte lines obtained from different samples are plotted against their concentration to form calibration curves for different elements from which the concentrations of unknown elements were deduced by comparing its LIBS signal with the calibration curves. Using ANN, an artificial neural network model is trained with a set of input data of known composition samples. The trained neural network is then used to predict the elemental concentration from the test spectra. The present results reveal that artificial neural networks are capable of predicting values better than traditional method in most cases.     

Quantitative elemental analysis of nutritional,hazardous and pharmacologically active elements in medicinal Rhatany root using laser induced breakdown spectroscopy

Rhatany roots (RRs) have been used in indigenous systems of medicines to treat many common illnesses due to the presence of highly active astringent and antiviral biochemical constituents that possess strong therapeutic and pharmacological properties. Due to its widespread use, the accurate knowledge on the elemental composition of this medicinal plant can set a pharmacological research platform to investigate the effect of certain elements, and their ions in mediating the human metabolism and therapy. In this work calibration-free laser-induced breakdown spectroscopy (CF-LIBS) is used to detect the elements present in RRs sample, by analyzing the characteristic emission wavelengths and their respective intensities in the laser induced plasma, without the need for using any calibration standards or methods. Many nutritional elements, which are of human health significance and instrumental in mediating the established biological activities of RRs, were identified in a relative abundance. In addition to this, our analysis identified the trace level of a few toxic elements, whose overdose due to reckless intake wreaks havoc to human health and wellbeing. The reliability of qualitative and quantitative detection of the elements in RR by LIBS were validated by the standard inductively coupled plasma optical emission spectroscopy (ICP OES), the results of which are in good agreement with LIBS data with better relative accuracy. Also, in order to discriminate, and single out any two elements with the overlapping emission wavelength in LIBS, X-ray photoelectron spectroscopy was also carried out, which in its own right is in good agreement with the elemental analysis of LIBS in general.     

Laser Induced Breakdown Spectroscopy methodology for the analysis of copper-based-alloys used in ancient artworks

In this paper Laser Induced Breakdown Spectroscopy has been applied for determining the elemental composition of a set of ancient bronze artworks coming from archaeological site of Minervino Murge — Southern of Italy (dated around VII b.C.). Before carrying on the analysis of the archaeological samples, the characterization of the analytical technique has been accomplished by investigating the trueness of the typical assumptions adopted in LIBS, such as Local Thermodynamic Equilibrium, congruent ablation and plasma homogeneity. With this purpose, two different laser pulse durations, 7 ns and 350 fs, have been used. We have focused our attention on LIBS analysis of bronze standards by considering and discussing the bases of both methodology and analytical approach to be followed for the analysis of ancient copper-based-alloy samples. Unexpectedly, regardless from the laser pulse duration, the LIBS technique has shown, by considering an adequate approach on the emitting plasma features, that its peculiarities are anyway preserved so that a fast analysis of ancient copper-based-alloys can be achieved. After verifying the suitability of the methodology, it has been possible to fulfill the typical assumptions considered for the LIBS calibration curves method and use it for ancient bronze artworks analysis.     

Double-pulse laser-induced breakdown spectroscopy analysis of scales from petroleum pipelines

Pipeline scales from the Campos Bay Petroleum Field near Rio de Janeiro, Brazil have been analyzed by both Raman spectroscopy and by laser-induced breakdown spectroscopy (LIBS) using a double-pulse, calibration-free approach. Elements that are characteristic of petroleum (e.g. C, H, N, O, Mg, Na, Fe and V) were detected, in addition to the Ca, Al, and Si which form the matrix of the scale. The LIBS results were compared with the results of micro-Raman spectroscopy, which confirmed the nature of the incrustations inferred by the LIBS analysis. Results of this preliminary study suggest that diffusion of pipe material into the pipeline intake column plays an important role in the growth of scale. Thanks to the simplicity and relative low cost of equipment and to the fact that no special chemical pre-treatment of the samples is needed, LIBS can offer very fast acquisition of data and the possibility of in situ measurements. LIBS could thus represent an alternative or complementary method for the chemical characterization of the scales by comparison to conventional analytical techniques, such as X-ray diffraction or X-ray fluorescence.     

Support vector machine classification of suspect powders using laser‐induced breakdown spectroscopy (LIBS) spectral data

Classification of suspect powders, by using laser‐induced breakdown spectroscopy (LIBS) spectra, to determine if they could contain Bacillus anthracis spores is difficult because of the variability in their composition and the variability typically associated with LIBS analysis. A method that builds a support vector machine classification model for such spectra relying on the known elemental composition of the Bacillus spores was developed. A wavelet transformation was incorporated in this method to allow for possible thresholding or standardization, then a linear model technique using the known elemental structure of the spores was incorporated for dimension reduction, and a support vector machine approach was employed for the final classification of the substance. The method was applied to real data produced from an LIBS device. Several methods used to test the predictive performance of the classification model revealed promising results. Published 2012. This article is a US Government work and is in the public domain in the USA.     

Evaluation of laser induced breakdown spectroscopy for multielemental determination in soils under sewage sludge application

Laser induced breakdown spectroscopy (LIBS) is an atomic emission spectroscopy technique for simple, direct and clean analysis, with great application potential in environmental sustainability studies. In a single LIBS spectrum it is possible to obtain qualitative information on the sample composition. However, quantitative analysis requires a reliable model for analytical calibration. Multilayer perceptron (MLP), an artificial neural network, is a multivariate technique that is capable of learning to recognize features from examples. Therefore MLP can be used as a calibration model for analytical determinations. Accordingly, the present study proposes to evaluate the traditional linear fit and MLP models for LIBS calibration, in order to attain a quantitative multielemental method for contaminant determination in soil under sewage sludge application. Two sets of samples, both composed of two kinds of soils were used for calibration and validation, respectively. The analyte concentrations in these samples, used as reference, were determined by a reference analytical method using inductively coupled plasma optical emission spectrometry (ICP OES). The LIBS-MLP was compared to a LIBS-linear fit method. The values determined by LIBS-MLP showed lower prediction errors, correlation above 98% with values determined by ICP OES, higher accuracy and precision, lower limits of detection and great application potential in the analysis of different kinds of soils.     

Artificial neural network for on-site quantitative analysis of soils using laser induced breakdown spectroscopy

Nowadays, due to environmental concerns, fast on-site quantitative analyses of soils are required. Laser induced breakdown spectroscopy is a serious candidate to address this challenge and is especially well suited for multi-elemental analysis of heavy metals. However, saturation and matrix effects prevent from a simple treatment of the LIBS data, namely through a regular calibration curve. This paper details the limits of this approach and consequently emphasizes the advantage of using artificial neural networks well suited for non-linear and multi-variate calibration. This advanced method of data analysis is evaluated in the case of real soil samples and on-site LIBS measurements. The selection of the LIBS data as input data of the network is particularly detailed and finally, resulting errors of prediction lower than 20% for aluminum, calcium, copper and iron demonstrate the good efficiency of the artificial neural networks for on-site quantitative LIBS of soils.     

High resolution applications of laser-induced breakdown spectroscopy for environmental and forensic applications

Laser-induced breakdown spectroscopy (LIBS) has been used in the elemental analysis for a variety of environmental samples and as a proof of concept for a host of forensic applications. In the first application, LIBS was used for the rapid detection of carbon from a number of different soil types. In this application, a major breakthrough was achieved by using a multivariate analytical approach that has brought us closer towards a “universal calibration curve”. In a second application, it has been demonstrated that LIBS in combination with multivariate analysis can be employed to analyze the chemical composition of annual tree growth rings and correlate them to external parameters such as changes in climate, forest fires, and disturbances involving human activity. The objectives of using this technology in fire scar determinations are: 1) To determine the characteristic spectra of wood exposed to forest fires and 2) To examine the viability of this technique for detecting fire occurrences in stems that did not develop fire scars. These examples demonstrate that LIBS-based techniques are inherently well suited for diverse environmental applications. LIBS was also applied to a variety of proof of concept forensic applications such as the analysis of cremains (human cremation remains) and elemental composition analysis of prosthetic implants.     

Multi-elemental analysis of solidified mineral melt samples by Laser-Induced Breakdown Spectroscopy coupled with a linear multivariate calibration

Laser-Induced Breakdown Spectroscopy (LIBS) has been successfully applied for multi-elemental analysis of solidified mineral melt samples containing several oxides present in various concentrations. The plasma was generated using a Nd:YAG laser and the spectra were acquired using an Echelle spectrometer, coupled to an ICCD detector, which covers a spectral range from 200 to 780 nm. Using a set of 19 calibration samples, we first established univariate calibration curves for the major elements (Al, Fe, Mg, Ca, Ti and Si). We found out that the presence of matrix effects makes such a model, traditionally used in LIBS, not satisfying for quantitative analysis of such samples. Indeed, no sufficiently linear trends can be extracted from the calibration curves for the elements of interest considering all the samples. Instead, a much more robust calibration approach was obtained by considering a multivariate model. The matrix effects are then taken into account by correcting the spectroscopic signals emitted by a given species due the presence of the others ones. More specifically, we established here a calibration model using a 2nd order polynomial linear multivariate inverse regression. The capability of this approach was then checked using a 2nd set of samples with an unknown composition. A good agreement was observed between the analysis provided by X-ray fluorescence (XRF) and the LIBS measurements coupled to the multivariate model for the unknown samples.     

Quantitative analysis of alloys and glasses by a calibration-free method using laser-induced breakdown spectroscopy

Space-, time- and spectrally resolved optical diagnostics of laser ablation plasma has provided the opportunity to realize calibration-free analyses of solid materials. In general, this variant of optical emission spectroscopy of pulsed plasma allows the plasma matrix effects to be overcome, yielding satisfactorily precise and accurate quantitative results on elemental composition of materials without using calibration curves, certified reference materials, and internal standards. Such analysis is very close to be nondestructive due to the minimum possible ablated mass, a feature which is very important in many applications, especially for unique museum exhibits and jeweler samples. In this paper, the use of the method for the analysis of elements in bronze, brass and gold alloys, glass samples, and archaeological findings is demonstrated. The results presented confirm the suitability of the approach for routine applications of our instrumentation, while at the same time simplifying the overall analytical procedure.     

Multi-element analysis of iron ore pellets by Laser-induced Breakdown Spectroscopy and Principal Components Regression

Laser-induced Breakdown Spectroscopy (LIBS) in combination with Principal Components Regression (PCR) has been applied to determine the elemental composition of a series of run-of-mine (ROM) iron ore samples. The samples were presented for measurement both as compressed pellets and as loose chipped material. The present paper details the results of the measurements of the compressed pellets. Results from ore chips will be reported separately. LIBS spectral data was recorded in three separate spectral regions to measure major, minor and trace components of the iron ore sample pellets. Background stripping, normalization and spectral cleaning were applied to minimize the relative standard deviations of the LIBS data. PCR analysis was then applied to produce calibration models for iron, aluminum, silicon, manganese, potassium and phosphorous. These calibration models were then validated using independent LIBS measurements. Robust calibration models were determined for iron, aluminum, silicon and potassium, whilst the results for manganese were encouraging. Phosphorous, present at low levels in the ores measured, remained the most difficult element to determine accurately. The combination of LIBS and PCR shows potential for in-situ on-line determination of ore composition.     

Semi-quantitative analysis of binary alloys using laser-induced breakdown spectroscopy and a new calibration approach based on linear correlation

A new calibration approach to analyze binary solid samples at the percentage level is proposed, and its application to laser-induced breakdown spectroscopy (LIBS) is presented. The method is based on the observed dependence of the linear correlation coefficient on the analyte concentration in a binary sample. The linear correlation coefficient is calculated between spectra of a range of certified standards and the spectrum of a reference sample (the analyte in the form of a pure metal), and the resulting curve is used as a calibration curve. It was found that a quadratic function could be adequately used to fit the calibration points. The first part of this paper characterizes the proposed calibration method providing mathematical and simulational data, and also describes a possibility to extend it to multicomponent samples. In the second part, the method is successfully applied to the LIBS analysis of Cu in brass samples as well as Al, Si and Cu in aluminum alloys. The new method was found to give rise to results accurate to 1–5% for major components, and usually outperformed conventional calibration in terms of both precision and accuracy.     

Evaluation of self-absorption of manganese emission lines in Laser Induced Breakdown Spectroscopy measurements

This paper is part of a more general study aimed to the determination of the best experimental procedures for reliable quantitative measurements of Fe–Mn alloys by LIBS. In this work, attention is pointed on the self-absorption processes, whose effect deeply influences the LIBS measurements, reflecting in non-linear calibration curves. The effect of self-absorption on the line intensity can be quantified by defining a self-absorption coefficient, that measures the deviation of the line intensity from the linear extrapolation of the curve of growth in the optically thin regime. The authors demonstrated in a previous paper that self-absorption coefficients could be calculated once the electron density of the plasma is known and the Stark coefficients of the lines are available. However, when the Stark coefficients of the lines of interest are not known, a different approach is needed. In this work a new method for evaluation of self-absorption coefficients in LIBS measurements is presented, which does not require the knowledge of Stark coefficients. In order to understand the basic principles and setting out the theoretical tools that will be used for the analysis of the alloys, a preliminary study was done on pure Mn; LIBS spectra were acquired in different experimental conditions, at different laser energies and different delays after the laser irradiation of the sample. Moreover, collinear double pulse measurements were also performed. Analytical relations were derived and experimental procedures devised for evaluation of the self-absorption coefficients of several Mn lines, which are important for characterization and control of the experimental conditions in which the analysis is performed.     

Artificial neural network for Cu quantitative determination in soil using a portable Laser Induced Breakdown Spectroscopy system

Laser Induced Breakdown Spectroscopy (LIBS) is an advanced analytical technique for elemental determination based on direct measurement of optical emission of excited species on a laser induced plasma. In the realm of elemental analysis, LIBS has great potential to accomplish direct analysis independently of physical sample state (solid, liquid or gas). Presently, LIBS has been easily employed for qualitative analysis, nevertheless, in order to perform quantitative analysis, some effort is still required since calibration represents a difficult issue. Artificial neural network (ANN) is a machine learning paradigm inspired on biological nervous systems. Recently, ANNs have been used in many applications and its classification and prediction capabilities are especially useful for spectral analysis. In this paper an ANN was used as calibration strategy for LIBS, aiming Cu determination in soil samples. Spectra of 59 samples from a heterogenic set of reference soil samples and their respective Cu concentration were used for calibration and validation. Simple linear regression (SLR) and wrapper approach were the two strategies employed to select a set of wavelengths for ANN learning. Cross validation was applied, following ANN training, for verification of prediction accuracy. The ANN showed good efficiency for Cu predictions although the features of portable instrumentation employed. The proposed method presented a limit of detection (LOD) of 2.3 mg dm^− 3 of Cu and a mean squared error (MSE) of 0.5 for the predictions.     

Analysis of Soil by Magnetic Field Assisted Calibration-Free Laser Induced Breakdown Spectroscopy (CF-LIBS) and Laser Ablation – Time-of-Flight Mass Spectrometry (LA-TOF-MS)

The qualitative and quantitative analysis of soil samples collected from Sialkot, Pakistan (which contains leather industrial plants), has been performed using laser-induced breakdown spectroscopy (LIBS) and laser ablation time of flight mass spectrometry (LA-TOF-MS). The focused beam of a Q-switched Nd: YAG laser (532?nm) was used to ablate the soil samples in air at atmospheric pressure. The optical emission spectra demonstrate the presence of the spectral lines of Si, Fe, Al, Ca, Ti, K, Cr, Mg, Na, Ba, and Li in all of the samples. The emission lines intensities, electron number densities, and excitation temperatures were significantly enhanced in the presence of an external 0.3 T magnetic field applied perpendicular to the plasma plume. A maximum enhancement factor of approximately 8 was observed in the emission intensity. The emergence of several additional lines has also been detected using the magnetic field-assisted LIBS approach. The elemental composition determined using calibration-free laser-induced breakdown spectroscopy (CF-LIBS), with and without magnetic field, reveals that the external magnetic field only adjusts the laser-generated plasma dynamics without affecting the quantitative analysis of the samples. Importantly, the toxic and heavy elements such as chromium and barium were detected and quantified in all of the soil samples by both of these techniques. The variations in the compositional analysis using CF-LIBS with and without the applied magnetic field and LA-TOF-MS were less than 10%.     

Calibration-Free Laser-Induced Breakdown Spectroscopy: State of the art

The aim of this paper is offering a critical review of Calibration-Free Laser-Induced Breakdown Spectroscopy (CF-LIBS), the approach of multi-elemental quantitative analysis of LIBS spectra, based on the measurement of line intensities and plasma properties (plasma electron density and temperature) and on the assumption of a Boltzmann population of excited levels, which does not require the use of calibration curves or matrix-matched standards. The first part of this review focuses on the applications of the CF-LIBS method. Quantitative results reported in the literature, obtained in the analysis of various materials and in a wide range of experimental conditions, are summarized, with a special emphasis on the departure from nominal composition values. The second part is a discussion of the simplifying assumptions which lie at the basis of the CF-LIBS algorithm (stoichiometric ablation and complete atomization, thermal equilibrium, homogeneous plasma, thin radiation, detection of all elements). The inspection of the literature suggests that the CF-LIBS method is more accurate in analyzing metallic alloys rather than dielectrics. However, the full exploitation of the method seems to be still far to come, especially for the lack of a complete characterization of the effects of experimental constraints. However, some general directions can be suggested to help the analyst in designing LIBS measurements in a way which is more suited for CF-LIBS analysis.     

Elemental Analysis of Cement by Calibration-Free Laser Induced Breakdown Spectroscopy (CF-LIBS) and Comparison with Laser Ablation – Time-of-Flight – Mass Spectrometry (LA-TOF-MS), Energy Dispersive X-Ray Spectrometry (EDX), X-Ray Fluorescence Spectroscopy (XRF), and Proton Induced X-Ray Emission Spectrometry (PIXE)

The purpose of the present study is to determine the elemental composition of Pakistani cement brands using calibration-free laser induced breakdown spectroscopy (CF-LIBS) and to compare the obtained results with the other analytical techniques such as, laser ablation – time-of-flight – mass spectrometry (LA-TOF-MS), energy dispersive X-ray spectrometry (EDX), X-ray fluorescence spectroscopy (XRF) and proton induced X-ray emission spectrometry (PIXE). Compositional results reveal that all the cement brands are mainly composed of calcium, silicon, iron, aluminum, magnesium, potassium, sodium, titanium, lithium and strontium with varying concentrations. The compositions obtained by LIBS and LA-TOF-MS are in good agreement with results obtained by the other standard techniques and demonstrate the potential use of LIBS for the online monitoring of industrial cement production.