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

Accurate determination of plasma temperature and electron density using a reference target: one-point calibration LIBS elemental analysis of alloy samples

Elemental analysis of aluminum alloy samples with calibration-free laser-induced breakdown spectroscopy (CF-LIBS) encounters two difficulties: the inconvenience of determining accurate temperature and electron density of the plasma and the influence of self-absorption of the observed aluminum lines. To solve this problem, target-enhanced orthogonal double-pulse laser-induced breakdown spectroscopy in the reheating regime combined with the one-point calibration method was proposed in this work. A mixture of copper powders and K H C O 3 grains was pressed to a pellet and used as the target. Accurate determination of plasma temperature and electron density can be obtained using a reference target. The plasma temperature could be determined with Saha-Boltzmann plot of copper, and the electron density of the plasma could be determined according to the Stark broadening of the H α line of hydrogen. Aluminum alloy samples were analyzed with a relative error of better than 0.02% for a major element. This approach provides a convenient way to determine the temperature and electron density of the plasma more accurately and is able to reduce the influence of self-absorption, which is helpful for realizing quantitative elemental analysis of different samples while using a calibration-free algorithm.

Quantitative elemental analysis of bismuth brass with target-enhanced orthogonal double-pulse LIBS combined with variant one-point calibration

Self-absorption and unknown transition probabilities of the analytical lines hinder the accurate quantitative elemental analysis of bismuth brass with conventional calibration-free laser-induced breakdown spectroscopy (LIBS). In this work, target-enhanced orthogonal double-pulse LIBS combined with a variant one-point calibration method was used to solve this problem and realize quantitative elemental analysis of bismuth brass with a relative error of less than 4%. This approach is able to reduce the influence of self-absorption and capable of using analytical lines with unknown transition probabilities while using a calibration-free algorithm, which is helpful for accurate quantitative elemental analysis of bismuth brass and other samples.

Accurate elemental analysis with variant one-point calibration laser-induced breakdown spectroscopy capable of using analytical lines with unknown transition probabilities

Calibration-free laser-induced breakdown spectroscopy (CF-LIBS) is a very useful elemental analysis technique. However, it requires knowledge of transition probabilities of the analytical lines. To solve this problem, a variant one-point calibration (OPC) LIBS method was proposed. Quantitative elemental analysis on Cu-Zn-Ag-Au alloys was realized with this method capable of using zinc analytical lines with unknown transition probabilities. The relative error was demonstrated to be less than 3.3%. This variant OPC method will be helpful for quantitative elemental analysis of different samples using CF-LIBS, no matter whether the transition probabilities of the observed lines are known or unknown.

A novel hybrid filter/wrapper method for feature selection in archaeological ceramics classification by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy (LIBS) has been appreciated as a valuable analytical tool in the cultural heritage field owing to its unique technological superiority, particularly in combination with chemometric methods. Feature selection (FS) as an indispensable pre-processing step in data optimization, for eliminating the redundant or irrelevant features from high-dimensional data to enhance the predictive capacity and result comprehensibility of multivariate classification based on LIBS technology. In this paper, a novel hybrid filter/wrapper method based on the MI-DBS algorithm was proposed to enhance the qualitative analysis performance of the LIBS technique. The proposed method combines the advantages of the mutual information (MI) algorithm based filter method and bi-directional selection (DBS) algorithm based wrapper method. The MI algorithm is the first to remove the redundant or uncorrelated features so that a simplified input subset can be established. Then, the DBS algorithm is used to further select the retained features and hence to seek an optimal feature subset with good predictive performance. To benefit the above feature selection process, the wavelet transform denoising (WTD) method was used to reduce the noise from LIBS spectra. LIBS experiments were performed using 35 archaeological ceramic samples. Besides, the proposed hybrid filter/wrapper method was implemented through a random forest (RF) based nonlinear multivariate classification method. Through a comparison between several other feature selection methods and the proposed method, it has been seen that the proposed method is the best regarding the predictive performance and number of the selected features. Finally, the MI-DBS algorithm is used to seek the optimal features from the full spectrum (220-720 nm); the corresponding sensitivity, specificity and accuracy acquired through the RF classifier for the test set were 0.9722, 0.9956 and 0.9850. It is shown from the general results that the MI-DBS algorithm is more effective in terms of improving the model performance and decreasing the redundant or uncorrelated features and computational time and serves as a good alternative for FS in multivariate classification.

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

Accurate management of soil nutrients and fast and simultaneous acquisition of soil properties are crucial in the development of sustainable agriculture. However, the conventional methods of soil analysis are generally labor-intensive, environmentally unfriendly, as well as time- and cost-consuming. Laser-induced breakdown spectroscopy (LIBS) is a “superstar” technique that has yielded outstanding results in the elemental analysis of a wide range of materials. However, its application for analysis of farmland soil faces the challenges of matrix effects, lack of large-scale soil samples with distinct origin and nature, and problems with simultaneous determination of multiple soil properties. Therefore, LIBS technique, in combination with partial least squares regression (PLSR), was applied to simultaneously determinate soil pH, cation exchange capacity (CEC), soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), available phosphorus (AP), and available potassium (AK) in 200 soils from different farmlands in China. The prediction performances of full spectra and characteristic lines were evaluated and compared. Based on full spectra, the estimates of pH, CEC, SOM, TN, and TK achieved excellent prediction abilities with the residual prediction deviation (RPDV) values > 2.0 and the estimate of TP featured good performance with RPDV value of 1.993. However, using characteristic lines only improved the predicted accuracy of SOM, but reduced the prediction accuracies of TN, TP, and TK. In addition, soil AP and AK were predicted poorly with RPDV values of < 1.4 based on both full spectra and characteristic lines. The weak correlations between conventionally analyzed soil AP and AK and soil LIBS spectra are responsible for the poor prediction abilities of AP and AK contents. Findings from this study demonstrated that the LIBS technique combined with multivariate methods is a promising alternative for fast and simultaneous detection of some properties (i.e., pH and CEC) and nutrient contents (i.e., SOM, TN, TP, and TK) in farmland soils because of the extraordinary prediction performances achieved for these attributes.

Accuracy improvement of quantitative analysis for major elements in laser-induced breakdown spectroscopy using single-sample calibration

Accurate determination of major elements using limited standard samples is always a big challenge in laser-induced breakdown spectroscopy (LIBS). Based on a simple calculation process, we propose a new one-point calibration method called single-sample calibration LIBS (SSC-LIBS) to build the calibration and improve the accuracy of determination of major elements. In this work, several major elements (Fe, Cu, Zn, Ni, Cr, Nb, and Mo) in three sets of matrix-matched certified samples were determined without sample preparation. The results showed that compared with multipoint calibration LIBS (MPC-LIBS), the R², RMSECV, and ARE of Cu elements were improved from 0.40 to 0.97, 3.55 wt% to 0.76 wt%, and 5.19% to 1.05%, respectively, while the ARSD decreased from 16.22% to 1.15%. Furthermore, the AREs in the concentration ranges of 1-10, 10-20, 30-40, 50-60, 60-70, and 80-100 wt% were 5.16%, 2.55%, 1.75%, 1.69%, 1.05%, and 0.44%, respectively, with almost all less than 5%, as calculated by SSC-LIBS. These results demonstrated that SSC-LIBS can improve the accuracy and stability of detecting major elements using only one standard sample, which can greatly promote the application of LIBS.

One-point and multi-line calibration method in laser-induced breakdown spectroscopy

The calibration-free laser-induced breakdown spectroscopy (CF-LIBS) and its variations are low cost, short time consumption, and high adaptability. However, seeking a more flexible and simple quantitative analysis method remains a challenge. A one-point and multi-line calibration (OP-MLC) was presented as a simple quantitative analysis method of LIBS. The results showed that OP-MLC-LIBS method can achieve quantitative analysis using only one standard sample, and the average relative errors (AREs) are 9, 22, 21 and 36% for Mn, Cr, Ni and Ti elements in six tested low-alloy steel samples, respectively. The method requires neither a large number of standard samples nor complicated calculations, which provides a flexible and low-cost quantitative analysis approach for development and application of LIBS.

A Calibration-Free Laser-Induced Breakdown Spectroscopy (CF-LIBS) Quantitative Analysis Method Based on the Auto-Selection of an Internal Reference Line and Optimized Estimation of Plasma Temperature

The quantitative analysis accuracy of calibration-free laser-induced breakdown spectroscopy (CF-LIBS) is severely affected by the self-absorption effect and estimation of plasma temperature. Herein, a CF-LIBS quantitative analysis method based on the auto-selection of internal reference line and the optimized estimation of plasma temperature is proposed. The internal reference line of each species is automatically selected from analytical lines by a programmable procedure through easily accessible parameters. Furthermore, the self-absorption effect of the internal reference line is considered during the correction procedure. To improve the analysis accuracy of CF-LIBS, the particle swarm optimization (PSO) algorithm is introduced to estimate the plasma temperature based on the calculation results from the Boltzmann plot. Thereafter, the species concentrations of a sample can be calculated according to the classical CF-LIBS method. A total of 15 certified alloy steel standard samples of known compositions and elemental weight percentages were used in the experiment. Using the proposed method, the average relative errors of Cr, Ni, and Fe calculated concentrations were 4.40%, 6.81%, and 2.29%, respectively. The quantitative results demonstrated an improvement compared with the classical CF-LIBS method and the promising potential of in situ and real-time application.

Novel Applications of Laser-Induced Breakdown Spectroscopy

The goal of this review article is to provide a description of recent and novel laser-induced breakdown spectroscopy (LIBS) applications and developments, especially those discussed during the NASLIBS Conference, held during SciX in Providence, RI, in September 2015. This topic was selected in view of the numerous recent overall review papers that have successfully given a broad view of the current understanding of laser-material interactions and plasma development and have also discussed the wide landscape of analytical applications of LIBS. This paper is divided into sections that focus on a few of the many applications under development in the LIBS community. We provide a summary of updates to calibration-free LIBS (CF-LIBS) and associated developments using plasma characteristics to improve quantification in LIBS output, both in a dedicated section and as applications are discussed. We have also described the most recent publications studying the sources, generation, and use of molecular features in LIBS, including those naturally present in the spectra of organic materials, and those induced with the addition of salts to enable the measurement of halogens, not typically present in LIBS signals. In terms of development of applications of LIBS, we focused on the use of LIBS for indirect measurements such as pH and degree of humification in soil and heating value in coal. We also reviewed the extant literature on LIBS analysis of agricultural materials, coal, minerals, and metals. Finally, we discuss the nascent developments of spatially heterodyne spectroscopy, a method that seeks to circumnavigate a serious drawback of most spectrometers - very small optical throughput - through the use of interferometers.

Archaeometric analysis of Roman bronze coins from the Magna Mater temple using solid-state voltammetry and electrochemical impedance spectroscopy

Voltammetry of microparticles (VMP) and electrochemical impedance spectroscopy (EIS) techniques, complemented by SEM-EDX and Raman spectroscopy, were applied to a set of 15 Roman bronze coins and one Tessera from the temple of Magna Mater (Rome, Italy). The archaeological site, dated back between the second half and the end of the 4th century A.D., presented a complicated stratigraphic context. Characteristic voltammetric patterns for cuprite and tenorite for sub-microsamples of the corrosion layers of the coins deposited onto graphite electrodes in contact with 0.10 M HClO₄ aqueous solution yielded a grouping of the coins into three main groups. This grouping was confirmed and refined using EIS experiments of the coins immersed in air-saturated mineral water using the reduction of dissolved oxygen as a redox probe. The electrochemical grouping of coins corroborated the complex stratigraphy of the archaeological site and, above all, the reuse of the coins during the later periods due to the economic issues related to the fall of the Roman Empire.

Mobile Spectroscopic Instrumentation in Archaeometry Research

Mobile instrumentation is of growing importance to archaeometry research. Equipment is utilized in the field or at museums, thus avoiding transportation or risk of damage to valuable artifacts. Many spectroscopic techniques are nondestructive and micro-destructive in nature, which preserves the cultural heritage objects themselves. This review includes over 160 references pertaining to the use of mobile spectroscopy for archaeometry. Following a discussion of terminology related to mobile instrumental methods, results of a literature survey on their applications for cultural heritage objects is presented. Sections devoted to specific techniques are then provided: Raman spectroscopy, X-ray fluorescence spectrometry, Fourier transform infrared spectroscopy, laser-induced breakdown spectroscopy, and less frequently used techniques. The review closes with a discussion of combined instrumental approaches.

Acidity analysis of iron ore based on calibration-free laser-induced breakdown spectroscopy (CF-LIBS) combined with a binary search algorithm (BSA)

Calibration-free laser-induced breakdown spectroscopy (CF-LIBS) combined with binary search algorithm (BSA) is proposed to determine the acidity (CaO/SiO₂ mass ratios) of iron ore.

Less is more: Avoiding the LIBS dimensionality curse through judicious feature selection for explosive detection

Despite its intrinsic advantages, translation of laser induced breakdown spectroscopy for material identification has been often impeded by the lack of robustness of developed classification models, often due to the presence of spurious correlations. While a number of classifiers exhibiting high discriminatory power have been reported, efforts in establishing the subset of relevant spectral features that enable a fundamental interpretation of the segmentation capability and avoid the ‘curse of dimensionality’ have been lacking. Using LIBS data acquired from a set of secondary explosives, we investigate judicious feature selection approaches and architect two different chemometrics classifiers –based on feature selection through prerequisite knowledge of the sample composition and genetic algorithm, respectively. While the full spectral input results in classification rate of ca.92%, selection of only carbon to hydrogen spectral window results in near identical performance. Importantly, the genetic algorithm-derived classifier shows a statistically significant improvement to ca. 94% accuracy for prospective classification, even though the number of features used is an order of magnitude smaller. Our findings demonstrate the impact of rigorous feature selection in LIBS and also hint at the feasibility of using a discrete filter based detector thereby enabling a cheaper and compact system more amenable to field operations.

A single-beam-splitting technique combined with a calibration-free method for field-deployable applications using laser-induced breakdown spectroscopy

In this work, a single-beam-splitting laser-induced breakdown spectroscopy (LIBS) technique using one single laser system is demonstrated.