Analysis of Multi-elemental Thin Films via Calibration-Free Laser-Induced Breakdown Spectroscopy

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.

Supporting Electrolyte Manipulation for Simple Improvement of the Sensitivity of Trace Vanadium(V) Determination at a Lead-Coated Glassy Carbon Electrode

The paper presents a very simple way to extremely improve the sensitivity of trace V(V) determination. The application of a new supporting electrolyte composition (CH₃COONH₄, CH₃COOH, and NH₄Cl) instead of the commonly used acetate buffer (CH₃COONa and CH₃COOH) significantly enhanced the adsorptive stripping voltammetric signal of vanadium(V) at the lead-coated glassy carbon electrode (GCE/PbF). A higher enhancement was attained in the presence of cupferron as a complexing agent (approximately 10 times V(V) signal amplification) than in the case of chloranilic acid and bromate ions (approximately 0.5 times V(V) signal amplification). Therefore, the adsorptive stripping voltammetric system with the accumulation of V(V)-cupferron complexes at -1.1 V for 15 s in the buffer solution (CH₃COONH₄, CH₃COOH, and NH₄Cl) of pH = 5.6 ± 0.1 was selected for the development of a simple and extremely sensitive V(V) analysis procedure. Under optimized conditions, the sensitivity of the procedure was 6.30 µA/nmol L^-1. The cathodic peak current of V(V) was directly proportional to its concentration in the ranges of 1.0 × 10^-11 to 2.0 × 10^-10 mol L^-1 and 2.0 × 10^-10 to 1.0 × 10^-8 mol L^-1. Among the electrochemical procedures, the lowest detection limit (2.8 × 10^-12 mol L^-1) of V(V) was obtained for the shortest accumulation time (15 s). The high accuracy of the procedure was confirmed on the basis of the analysis of certified reference material (estuarine water) and river water 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.

Pressure Effects on Simultaneous Optical and Acoustics Data from Laser-Induced Plasmas in Air: Implications to the Differentiation of Geological Materials

The shockwave generated alongside the plasma is an intimately linked, yet often neglected additional input for the characterization of solid samples by laser-induced breakdown spectroscopy (LIBS). The present work introduces a dual LIBS-acoustics sensor that takes advantage of the analysis of the acoustic spectrum yielded by shockwaves produced on different geological samples to enhance the discrimination power of LIBS in materials featuring similar optical emission spectra. Six iron-based minerals were tested at a distance of 2 m using 1064 nm laser light and under pressure values ranging from 7 to 1015 mbar. These experimental parameters were selected to assess the effects of pressure, one of the main factors conditioning the propagation of sound as well as a commonly investigated influence in LIBS experiments. Moreover, precise values for carrying out the analyses were set based on one of the most exciting scenarios in which LIBS data may be enhanced by laser-induced acoustics: space exploration. This is exemplified by the tasks performed by the Mars 2020 SuperCam instrument located onboard the Perseverance rover. Authors evaluated the use of acoustic signals both in the time-domain and frequency-domain in sensitive cases for the distinguishing of minerals exhibiting LIBS spectra featuring almost the same emission lines using PCA schemes for each pressure setting. Thus, we report herein the impact of the surrounding pressure level upon this diagnostic tool. Overall, this paper seeks to show how the analytical potential of simultaneous phenomena taking place during a laser-produced plasma event is subjected to the defined operational conditions.

Deep Learning Models for Data-Driven Laser Induced Breakdown Spectroscopy (LIBS) Analysis of Interstitial Oxygen Impurities in Czochralski-Si Crystals

Analytical advantages of facile and expeditious spectral data collections from laser-induced breakdown spectroscopy (LIBS) are often offset by the low-accuracy quantitative analyses offered by the technique due to non-equilibrium plasma-matrix interactions. Herein, we developed a one-dimensional (1D) convolutional neural network (CNN) and a least absolute shrinkage and selection operator (LASSO) models for LIBS data analyses to predict trace amounts of interstitial oxygen impurities in commercial Czochralski-silicon (Cz-Si) crystals with known interstitial oxygen concentrations at 0-16 parts per million (ppm). While traditional spectral analyses from O(I) (777.2 nm) atomic lines offer poor accuracy, CNN and LASSO analyses generate excellent predictions for the interstitial oxygen concentrations. Specifically, CNN-based spectral analyses uniquely identified systematic alterations in LIBS fingerprints manifested by laser-matter interactions. Our results pave the path for combining facile and voluminous LIBS data collection with deep learning driven high-fidelity data analytics.

Langmuir Probe Perturbations during In Situ Monitoring of Pulsed Laser Deposition Plasmas

The recent advancements in pulsed laser deposition (PLD) control via plasma diagnostics techniques have been positive and raised questions on the limitation of some techniques, such as the Langmuir probe (LP). The particularities of laser-produced plasma can lead to incorrect interpretation of collected electrical signal. In this paper, we explored the limitations of LP as a technique for in situ PLD control by performing investigations on several metallic plasmas, expanding in various Ar atmosphere conditions. Sub-microsecond modulation was seen in the reconstructed IV characteristics attributed to non-equilibrium dynamics of the ejected charges. A perturbative regime was recorded for Ar pressures higher than 2 Pa, where ionic bursts were observed in the electron saturation region. This perturbation was identified as a plasma fireball. A non-linear multifractal model was developed here to explore these new regimes of the LP. The strange attractors characterizing each fireball were reconstructed, and their evolution with the Ar pressure is discussed. Both short- and long-time non-linear behavior were correlated via probe bias, and the pressure effect on the strange attractor’s defining the fireball-like behavior was investigated. A good correlation was noticed between the simulated data and experimental findings.

On the Dynamics of Transient Plasmas Generated by Nanosecond Laser Ablation of Several Metals

The dynamics of transient plasma generated by UV ns-laser ablation of selected metals (Co, Cu, Ag, Bi) were investigated by the Langmuir Probe method in angle- and time-resolved modes. Multiple ionic and electronic structures were seen for all plasmas with some corresponding to anions or nanoparticle-dominated structures. The addition of an Ar atmosphere energetically confined the plasma and increased the charge density by several orders of magnitude. For pressure ranges exceeding 0.5 Pa fast ions were generated in the plasma as a result of Ar ionization and acceleration in the double layer defining the front of the plasma plume. Several correlations between the target nature plasma properties were attempted. The individual plasma structure expansion velocity increases with the melting point and decreases with the atomic mass while the corresponding charged particle densities decrease with the melting point, evidencing the relationship between the volatility of the sample and the overall abated mass.

Measurement error due to self-absorption in calibration-free laser-induced breakdown spectroscopy

Self-absorption of spectral lines is known to lower the performance of analytical measurements via calibration-free laser-induced breakdown spectroscopy. However, the error growth due to this effect is not clearly assessed. Here we propose a method to quantify the measurement error due to self-absorption based on the calculation of the spectral radiance of a plasma in local thermodynamic equilibrium. Validated through spectroscopic measurements for a binary alloy thin film of compositional gradient, the method evidences that measurement performance lowering due to self-absorption depends on the spectral shape of the analytical transition and on the intensity measurement method. Thus, line-integrated intensity measurements of Stark broadened lines enable accurate analysis, even at large optical thickness, if line width and plasma size are precisely known. The error growth due to self-absorption is significantly larger for line shapes dominated by Doppler broadening and for line-center intensity measurements. The findings present a significant advance in compositional measurements via calibration-free laser-induced breakdown spectroscopy, as they enable straightforward selection of most appropriate analytical lines.

Short-Pulse Lasers: A Versatile Tool in Creating Novel Nano-/Micro-Structures and Compositional Analysis for Healthcare and Wellbeing Challenges

Driven by flexibility, precision, repeatability and eco-friendliness, laser-based technologies have attracted great interest to engineer or to analyze materials in various fields including energy, environment, biology and medicine. A major advantage of laser processing relies on the ability to directly structure matter at different scales and to prepare novel materials with unique physical and chemical properties. It is also a contact-free approach that makes it possible to work in inert or reactive liquid or gaseous environment. This leads today to a unique opportunity for designing, fabricating and even analyzing novel complex bio-systems. To illustrate this potential, in this paper, we gather our recent research on four types of laser-based methods relevant for nano-/micro-scale applications. First, we present and discuss pulsed laser ablation in liquid, exploited today for synthetizing ultraclean "bare" nanoparticles attractive for medicine and tissue engineering applications. Second, we discuss robust methods for rapid surface and bulk machining (subtractive manufacturing) at different scales by laser ablation. Among them, the microsphere-assisted laser surface engineering is detailed for its appropriateness to design structured substrates with hierarchically periodic patterns at nano-/micro-scale without chemical treatments. Third, we address the laser-induced forward transfer, a technology based on direct laser printing, to transfer and assemble a multitude of materials (additive structuring), including biological moiety without alteration of functionality. Finally, the fourth method is about chemical analysis: we present the potential of laser-induced breakdown spectroscopy, providing a unique tool for contact-free and space-resolved elemental analysis of organic materials. Overall, we present and discuss the prospect and complementarity of emerging reliable laser technologies, to address challenges in materials' preparation relevant for the development of innovative multi-scale and multi-material platforms for bio-applications.

Quantification of toxic metals using machine learning techniques and spark emission spectroscopy

The United States Environmental Protection Agency (US EPA) list of hazardous air pollutants (HAPs) includes toxic metal suspected or associated with development of cancer. Traditional techniques for detecting and quantifying toxic metals in the atmosphere are either not real time, hindering identification of sources, or limited by instrument costs. Spark emission spectroscopy is a promising and cost-effective technique that can be used for analyzing toxic metals in real time. Here, we have developed a cost-effective spark emission spectroscopy system to quantify the concentration of toxic metals targeted by the US EPA. Specifically, Cr, Cu, Ni, and Pb solutions were diluted and deposited on the ground electrode of the spark emission system. The least absolute shrinkage and selection operator (LASSO) was optimized and employed to detect useful features from the spark-generated plasma emissions. The optimized model was able to detect atomic emission lines along with other features to build a regression model that predicts the concentration of toxic metals from the observed spectra. The limits of detections (LODs) were estimated using the detected features and compared to the traditional single-feature approach. LASSO is capable of detecting highly sensitive features in the input spectrum; however, for some toxic metals the single-feature LOD marginally outperforms LASSO LOD. The combination of low-cost instruments with advanced machine learning techniques for data analysis could pave the path forward for data-driven solutions to costly measurements.

Half-life determination of inorganic-organic hybrid nanomaterials in mice using laser-induced breakdown spectroscopy

Inorganic or inorganic-organic hybrid nanomaterials have great potential for applications in the biomedical fields. Biological half-life is an essential pharmacokinetic parameter for these materials to function in vivo. Compared to inductively coupled plasma mass spectrometry (ICP-MS), which is the gold standard, laser-induced breakdown spectroscopy (LIBS) is a faster and more efficient elemental detection method. We investigated an efficient way to quantify the metabolic rate using LIBS. Nanoparticle platforms, such as manganese dioxide-bovine serum albumin (MnO2-BSA) or boehmite-bovine serum albumin (AlO(OH)-BSA) were injected into mice through intravenous administration for LIBS spectrum acquisition. First, the spectral background was corrected using the polynomial fitting method; The spectral interference was eliminated by Lorentz fitting for each LIBS spectrum simultaneously. The support vector regression (SVR) was then used for LIBS quantitative analyses. Finally, the LIBS results were compared with the ICP-MS ones. The half-lives of MnO2-BSA calculated by LIBS and ICP-MS were 2.49 and 2.42 h, respectively. For AlO(OH)-BSA, the half-lives detected by LIBS and ICP-MS were 3.46 and 3.57 h, respectively. The relative error of LIBS is within 5% compared to ICP-MS. The results demonstrate that LIBS is a valuable tool for quantifying the metabolic rates with a high degree of accuracy.

Exploiting Self-Absorption for Plasma Characterization in Laser-Induced Breakdown Spectroscopy Experiments: A Comparison of Two Recent Approaches

In this article, we compare two analytical methods that have been recently proposed: the columnar density Saha-Boltzmann plot method of Cristoforetti and Tognoni (Cristoforetti, G.; Tognoni, E. Spectrochim. Acta, Part B, 2013, 79-80, 63-71) and the C-sigma model of Aragon and Aguilera (Aragon, C.; Aguilera, J. A. J. Quant. Spectrosc. Radiat. Trans. 2014, 149, 90-102). Both methods are based on the exploitation of self-absorbed lines for the characterization of plasmas in laser-induced breakdown spectroscopy experiments. However, although the two methods can be safely applied in many cases, their usefulness is limited in many practical cases of interest because of the intrinsic constraints of the used plasma model or because of the complexity of the numerical treatment. The two methods are presented here and critically discussed. Finally, an extended C-sigma approach is proposed to merge the advantages of the two methods, overcoming their intrinsic limitations and simplifying the numerical treatment.