Laser-induced Breakdown Research Articles

Electronic waste analysis using laser-induced breakdown spectroscopy (LIBS) and X-ray fluorescence (XRF): Critical evaluation of data fusion for the determination of Al, Cu and Fe

BackgroundElectronic waste (e-waste) proliferation and its implications underscore the imperative for advanced analytical methods to mitigate its environmental impact. It is estimated that e-waste production stands at a staggering 20–50 million tons yearly, of which merely 20–25% undergo formal recycling. The e-waste samples evaluated contain computers, laptops, smartphones, and tablets. ResultsForty-one samples were processed, involving the disassembly and separation of components. Subsequently, two analytical techniques, laser-induced breakdown spectroscopy (LIBS) and energy dispersive X-ray fluorescence (ED-XRF), were applied to quantify aluminum (Al), copper (Cu), and iron (Fe) in the e-waste samples. The samples were then analyzed after acid mineralization with 50% v v−1 aqua regia in a digester block and finally by ICP OES. A solid residue composed of Si and Ti was observed after the digestion of the samples. Multivariate calibration strategies such as partial least-squares regression (PLS), principal component regression (PCR), maximum likelihood principal component regression (MLPCR), and error covariance penalized regression (ECPR) were used for calibration. Finally, the figures of merit were calculated to verify the most suitable models. The results revealed robust models with notable sensitivity, varying from 8.98 to 35.04 Signal (a.u.)(% w w−1) −1, low Limits of Detection (LoD) within the range of 0.001–0.2 % w w−1, and remarkable relative errors ranging from 2% to 33%, particularly for Cu and Fe. SignificanceNotably, the models for Al faced inherent challenges, thus highlighting the complexities associated with its quantification in e-waste samples. In conclusion, this research represents an important step toward a more sustainable and efficient future for electronic waste recycling, signifying its relevance to global environmental welfare and resource conservation.

In situ chemical analysis of duplex stainless steel weld by laser induced breakdown spectroscopy

The high corrosion resistance and good mechanical properties of duplex stainless steel (DSS) are due to its special chemical composition, which is a balanced phase ratio of ferrite (α) and austenite (γ). Many industrial applications require the integration of DSS components. For this, Gas tungsten arc welding (GTAW) is an excellent choice, as it allows an automated operation with high reproducibility. However, when the weld pool solidifies, critical ratios of α- and γ- phases can occur, which lead to solidification cracking, increased susceptibility to corrosion, and a decrease in ductility and critical strength. Previous studies have shown that these defects can be caused by the accumulation of manganese and chromium in the heat affected zone (HAZ), requiring ongoing monitoring of this accumulation. A suitable method for such monitoring is laser-induced breakdown spectroscopy (LIBS), which can be used in two operating modes: calibration using standard reference samples and calibration-free. Unlike conventional quantitative LIBS measurements, which require reference samples to generate a calibration curve, calibration-free LIBS (CF-LIBS) allows chemical compositions to be determined solely from the emission spectrum of the plasma. Numerous publications show that CF-LIBS is a fast and efficient analytical method for the quantitative analysis of metal samples. In this work, CF-LIBS is applied to spectra obtained during GTAW DSS welding and the result is compared with those obtained by PLS analysis. A good correlation was found between both types of analysis, demonstrating the suitability of the CF-LIBS method for this application. The CF-LIBS method has a significant advantage over conventional LIBS due to the rapid in situ measurement of concentrations of major alloying elements without calibration procedure. This, combined with fast feedback and appropriate adjustment of welding parameters, helps prevent welding defects.

Controlling capillary flow by using laser-fabricated acrylic substrates with rectangular grooves for the improvement of repeatability of laser induced breakdown spectroscopy liquid analysis

To enhance the consistency of Laser-Induced Breakdown Spectroscopy (LIBS) in detecting dried liquid droplets, a rectangular groove substrate prepared by laser etching of a polymethyl methacrylate (PMMA) acrylic board is proposed in this work to suppress the Coffee Ring Effect (CRE). Located at the corner of the substrate, the right-angled heat source structure induces a significant inward thermal capillary flow within the groove, thus inhibiting solute capillary flow. At the later stages of heating, the edge deposition that occurs during evaporation is suppressed by the sawtooth-like microscopic grooves, along with the capillary effects in associated with the liquid. The rationale of CRE suppression by the rectangular groove substrate is theoredically analyzed based on the coupled thermal-solute capillary flow theory. With LIBS used to scan the samples within rectangular and circular groove substrates, it is revealed that the relative standard deviation (RSD) of spectral intensities for Cd I 259.28 nm and Cu I 324.27 nm in the rectangular groove substrate with a depth of 0.1 mm (RSD = 4.2%, RSD = 2.1%) is less significant than in the circular groove substrate (RSD = 41.2%, RSD = 39.3%). On average, the RSD is 7.6% and 7.3%, respectively, which indicates the effect of the rectangular groove substrate on CRE suppression. On this basis, calibration curves are drawn for Cd and Cu to indicate the good fitting results for the rectangular groove substrate, with the determination coefficient (R2) reaching 0.997 and 0.996 for Cd and Cu, respectively. The limit of detection (LOD) is 0.48 μg/mL and 0.35 μg/mL, respectively. The cross-validation root mean square error (RMSECV) is 2.02 μg/mL and 1.36 μg/mL, respectively. These results demonstrate that the rectangular groove substrate is effective in suppressing the CRE, and in enhancing the sensitivity of detection and the accuracy of heavy metal prediction, which provides guidance for platform selection in the pre-processing stage of LIBS technology.

Surface hardness determination of laser cladding using laser-induced breakdown spectroscopy and machine learning (PLSR, CNN, ResNet, and DRSN).

In this study, we employed laser-induced breakdown spectroscopy (LIBS) along with machine learning algorithms, which encompass partial least squares regression (PLSR), the deep convolutional neural network (CNN), the deep residual neural network (ResNet), and the deep residual shrinkage neural network (DRSN), to estimate the surface hardness of laser cladding layers. (The layers were produced using Fe316L, FeCrNiCu, Ni25, FeCrNiB, and Fe313 powders, with 45 steel and Q235 serving as substrates.) The research findings indicate that both linear and nonlinear models can effectively fit the relationship between LIBS spectra and surface hardness. Particularly, the model derived from the ResNet exhibits superior performance with an R 2 value as high as 0.9967. We hypothesize that the inclusion of numerous noises in the LIBS spectra contributes to the enhanced predictive capability for surface hardness, thereby leading to the superior performance of the ResNet compared to the DRSN.

A new method for calibration-free analysis by Laser-Induced Breakdown Spectroscopy using a time-integrated spectrometer

In this paper, we will discuss a new method for obtaining information about the plasma temporal evolution in Laser-Induced Breakdown Spectroscopy (LIBS) experiments using a time-integrated spectrometer.The method, inspired to the Bredice 3D-Boltzmann plot formalism, allows a precise determination of the temporal evolution of the emission line intensity in a LIBS plasma, starting from a series of time-integrated measurements obtained at different delay times after the laser pulse.In this way the application of a calibration-free algorithm using a time-integrated spectrometer is made possible.Examples of the application of the method are given in the analysis of two Zamac (a zinc alloy containing aluminum, magnesium, and copper) certified samples. A good agreement is obtained between the calculated and nominal concentrations of the two samples.A further validation of the method was performed on a third Zamac sample, of unknown composition. The sample was first characterized using a conventional CF-LIBS approach on a time-resolved spectrum; the obtained composition was then compared with the one determined using the series of time-integrated spectra.

Exploring Spectral Uncertainty on the Surface of Brass Samples by Laser-Induced Breakdown Spectroscopy

The shot-to-shot measurement uncertainty restricts the application of laser-induced breakdown spectroscopy (LIBS) technically, to a certain extent. In order to further deepen the understanding of spectral stability, in this paper, the effects of the laser’s focus depth, the delay of the spectrometer, and the position of the spectrum collection on the spectral stability were carefully researched. Moreover, the dynamic characteristics of plasma were studied at different laser focusing depths. Research has found that the morphological changes of plasma are relatively stable, without significant changes, despite varying depths of laser focus on the sample surface. In addition, it was found that stable elemental emission spectra can always be obtained in the early plasma aggregation region.

Quantitative measurement of sodium emissions during oxy-fuel combustion of a beech wood biomass particle using laser-induced breakdown spectroscopy

Oxy-fuel biomass combustion in a circulating fluidized bed is a clean and sustainable biomass utilization technology. Woody forest biomass is considered a promising source of renewable energy because of its widespread availability across the globe. However, effective biomass utilization in thermal power plants is largely limited by severe ash deposition and corrosion of heat transfer surfaces due to alkali metal and chlorine emissions during biomass combustion. In this study, laser-induced breakdown spectroscopy (LIBS) was applied to detect in-situ gas phase sodium (Na) emission during single particle combustion of widely available forest biomass, namely, beech wood. The operating conditions simulate the thermo-chemical conditions relevant to a fluidized bed combustor system, where the operating temperature varies between 1073K–1273K. This work aims to investigate the effect of O2 concentration, CO2 (oxyfuel environment), and particle size on the emission of sodium during the combustion of a single beech wood particle. The unresolved sodium doublet was used as the LIBS signal to quantify sodium emission concentration.Oxygen concentration is the most critical parameter affecting Na emissions, and an increase in O2 concentration led to higher Na emissions. It is observed that there is a significant reduction in the emission of Na in an O2/CO2 environment as compared to an O2/N2 environment. It is hypothesized that this drop in Na emissions in O2/CO2 environment could be due to lower particle temperatures caused by the lower diffusivity of O2 in CO2 as well as the endothermic gasification reaction in high CO2 environments. In addition, it is reported that the dissociation of sodium carboxylates and carbonates in the biomass matrix to release gaseous Na due to thermal decomposition is retarded at higher CO2 concentrations which could explain the drop in Na emissions. The effect of biomass particle size is pronounced mainly at lower concentration of O2 where, larger particles keep Na trapped in its matrix, however, at higher O2 concentrations (30%), the effect of particle size on Na emission is negligible.

Experimental study of ignition and combustion characteristics assisted by laser-induced plasma during oxy-coal atmosphere by optical emission spectroscopy

This investigation aims to understand the enhancement characteristics of plasma-assisted combustion in oxy-coal combustion. A 1064 nm Nd:YAG laser was added into a laminar flow reactor to produce laser-induced plasmas (LIPs). The high-speed visualization of the coal flame was used to reveal combustion's progress and evolution following laser-induced breakdown. To the best of our knowledge, this is the first time LIP has been applied to the optimization of pulverized coal combustion. The optical emission spectroscopy (OES) demonstrats that LIPs can generate adequate free electrons and ions during combustion. When the laser's pulse interval exceeds 60 ms, the LIP has a beneficial impact on combustion. For the heterogeneous reaction, the thermal effect generated by LIP only improves the intensity of flame radiation by 11–33 %. In contrast, the combination of chemical and thermal effects of plasma can result in significant enhancements of radiation intensity for high-volatile coals, with improvements of 76–203 %. Following laser-induced breakdown, the ignition delay time also decreases from lignite to anthracite, and the flame's peak intensity occurs earlier.

A Laser-Induced Breakdown Spectroscopy (LIBS) Instrument for In-Situ Exploration with the DLR Lightweight Rover Unit (LRU)

In the framework of the Helmholtz ARCHES project, a multitude of robots, including rovers and drones, were prepared for the autonomous exploration of a test site at the foothills of Mt. Etna, Sicily—a terrain resembling extraterrestrial locations such as the Moon. To expand the suite of tools and sensors available for the exploration and investigation of the test site, we developed a laser-induced breakdown spectroscopy (LIBS) instrument for the geochemical analysis of local geological samples. In alignment with the mission scenario, this instrument is housed in a modular payload box that can be attached to the robotic arm of the Lightweight Rover Unit 2 (LRU2), allowing the rover to use the instrument autonomously in the field. A compact Nd:YAG laser is utilized for material ablation, generating a micro-plasma that is subsequently analyzed with a small fiber-coupled spectrometer. A single-board computer controls the LIBS hardware components for data acquisition. In this study, we provide details of the ARCHES LIBS instrument implementation, report on preceding laboratory tests where the LRU2 operated the LIBS module for the first time, and showcase the results obtained during the successful ARCHES space analogue demonstration mission campaign in summer 2022 in Sicily.

The detection of elemental content changes in electrode coating using laser-induced breakdown spectroscopy

The elemental content of battery electrode coating is prone to change due to the production technology and ambient factors. To ensure the consistent performance and safety of a lithium battery, the elemental content of the electrode coating needs to be kept strictly consistent. This study proposes an internal mixed matrix method that combines laser-induced breakdown spectroscopy and chemometric method to achieve rapid and accurate detection of elemental content changes in electrode coating. The stoichiometric ratios of analytical elements are calculated by using the spectra of laser-induced breakdown spectroscopy. The relationships between that stoichiometric ratios and the actual content of analytical elements are studied and show that they are linear. Thus, the content change of the analytical element can be determined by calculating the change of the stoichiometric ratio. The average relative errors for content changes of iron, lithium, and phosphorus are 6.43%, 2.96%, and 4.12%, respectively, and the lowest detection limits are 278.2 mg/kg, 20.5 mg/kg, and 105.4 mg/kg, respectively. Furthermore, the internal reference method is proposed to correct the effect of ambient gases and improve detection accuracy. The results are that when Fe I 372.751 nm and Fe I 373.485 nm are used as analytical lines, after correcting for the effect of ambient gases, the average relative errors of Fe content changes are reduced by 62% and 72%, respectively, and the lowest detection limits are increased by 67% and 71%, respectively.

Plasma parameters correction method based on plasma image-spectrum fusion for matrix effect elimination in LIBS.

Matrix effect is one of the obstacles that hinders the rapid development of laser-induced breakdown spectroscopy (LIBS), and it is currently a hot, challenging, and focal point in research. To eliminate the matrix effect, this study proposed a plasma parameters correction method based on plasma image-spectrum fusion (PPC-PISF). This method corrects the total number density, plasma temperature, and electron number density variations caused by matrix effect using effective features in plasma images and spectra. To verify the feasibility of this method, experiments were conducted on pressed and metal samples, and the results were compared with those corrected by image-assisted LIBS (IA-LIBS). For the pressed samples, after correction by PPC-PISF, the R2 of the calibration curves all improved to above 0.993, the average root-mean-square error (RMSE) decreased by 41.05%, and the average relative error (ARE) decreased by 59.35% evenly in comparison to IA-LIBS. For the metal samples, after correction by PPC-PISF, the R2 of the calibration curves all increased to above 0.997. Additionally, the RMSE decreased by 29.63% evenly, the average ARE decreased by 38.74% compared to IA-LIBS. The experimental results indicate that this method is an effective method for eliminating the matrix effect, promoting the further development of LIBS in industrial detection.

Novel Combustion Instability Diagnosis Method With Upstream Pulsation of Repetitive Laser-Induced Plasmas

Abstract In this experimental study, we are presenting the ability of laser-induced plasmas with successive pulsation to identify combustion instabilities (CI) of a premixed lab-scale combustor. An acoustic disturbance equivalent to a shockwave perturbation is generated in the main air supply line of a swirled injector prior to the fuel addition by focusing nanosecond laser pulses of 1.6 W average power at 10 Hz. The shockwaves are attenuated to be strong pressure waves when reaching the combustor and impact the pressure field for short periods. After plasma breakdowns, the system returns back to its original state after 4 ms once the added acoustic energy has been fully dissipated. Given a set geometry, it is observed that the laser-induced breakdown amplifies the characteristic frequency peaks of the combustor system when actuated in cold flow. Furthermore, when applied to reacting flows, the pulsating acoustic perturbations impact the pressure fluctuation in the combustor, e.g., reducing the amplitude of the primary characteristic frequency peak at certain conditions. The identification of the main instability modes thanks to the plasma shockwave provides proof of the potential use of this novel diagnosis strategy in various and complex combustion systems.

Determination of heavy elements collected from the tropical river water by laser-induced breakdown spectroscopy (LIBS) technique: probable experimental approaches and challenges

Determination of heavy elements collected from the tropical river water by laser-induced breakdown spectroscopy (LIBS) technique: probable experimental approaches and challenges

Comparison of three nanoparticle deposition techniques potentially applicable to elemental mapping by nanoparticle-enhanced laser-induced breakdown spectroscopy

In this study, we compared the applicability of three nanoparticle deposition techniques (spray coating, spark discharge nanoparticle generation, magnetron sputtering) towards elemental mapping by nanoparticle-enhanced laser-induced breakdown spectroscopy (NE-LIBS). It was found that sputtering followed by a thermal treatment at 550 °C can provide a homogenous, practical and controllable way of NE-LIBS sample preparation with gold nanoparticles. The laser ablation properties of the created NP layer was also studied in detail and it was established that a 200 μm laser spot size is good compromise between the NE-LIBS signal enhancement and the spatial resolution required for mapping. A signal enhancement of about a factor of 10 with good repeatability (ca. 5 %RSD) in a line scanning demonstration was achieved on glass for Si detection. For samples that are fairly temperature and vacuum stable, this approach allows the signal enhancement to be used in mapping applications.

Analysis of Lithium Aging Using Machine Learning-Enhanced Spectroscopy Techniques.

Lithium compounds such as lithium hydride (LiH) and lithium hydroxide (LiOH) have a wide range of industrial applications, but are highly reactive in environments with H2O and CO2. These reactions lead to the ingrowth of secondary lithium compounds, which can alter the homogeneity and affect the application of particular lithium chemicals. This study performed an exploratory analysis of different lithium compounds using laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy. Machine learning models are trained on the recorded spectral data to discriminate emission features that differ between LiH, LiOH, and Li2CO3 to perform high-fidelity classification. Support vector machine classifiers yield perfect prediction accuracy between the three compounds with optimal training time. Multivariate methods are then used to produce regression models quantifying the ingrowth of LiOH in LiH. Performing a mid-level data fusion of selected LIBS and Raman features with partial least-squares regression produces the superlative model with a root mean square error of 2.5 wt and a detection limit of 6.3 wt.

Detection of Cadmium and Lead Heavy Metals in Soil Samples by Portable Laser-Induced Breakdown Spectroscopy

Heavy metal pollution in soil is becoming more and more serious. LIBS is one of the most promising technologies for rapid detection of heavy metal contamination in soil. However, due to the wide variety of soils and complex matrices, accurate quantification remains a challenge. In total, 451 soil samples were prepared and detected by the portable detector of LIBS, which were divided into six categories based on the compactness of the soil pellets, and a separate quantitative model for each type of soil sample was used for quantitative analysis by external standard method. It did not need a lot of data to train the model, and only a small number of calibration samples could be used for quantitative analysis of a large number of samples. The results showed that 78 standard samples and 334 collected samples were quantitatively analyzed by 39 standard samples. Compared with the standard value, the correlation coefficients were all above 0.95. A comparative experiment indicated that the portable LIBS system combined with soil classification and calibration methods can achieve fast and accurate quantitative detection.

Jewelry rock discrimination as interpretable data using laser-induced breakdown spectroscopy and a convolutional LSTM deep learning algorithm

In this study, the deep learning algorithm of Convolutional Neural Network long short-term memory (CNN–LSTM) is used to classify various jewelry rocks such as agate, turquoise, calcites, and azure from various historical periods and styles related to Shahr-e Sokhteh. Here, the CNN–LSTM architecture includes utilizing CNN layers for the extraction of features from input data mixed with LSTMs for supporting sequence forecasting. It should be mentioned that interpretable deep learning-assisted laser induced breakdown spectroscopy helped achieve excellent performance. For the first time, this paper interprets the Convolutional LSTM effectiveness layer by layer in self-adaptively obtaining LIBS features and the quantitative data of major chemical elements in jewelry rocks. Moreover, Lasso method is applied on data as a factor for investigation of interoperability. The results demonstrated that LIBS can be essentially combined with a deep learning algorithm for the classification of different jewelry songs. The proposed methodology yielded high accuracy, confirming the effectiveness and suitability of the approach in the discrimination process.

LIBS for prospecting and Raman spectroscopy for monitoring: two feasibility studies for supporting in-situ resource utilization

Laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy are still rather new techniques for in-situ exploration of extraterrestrial planetary surfaces but have shown their suitability and great potential in several successful robotic missions already. Next to serving primary scientific applications, both methods can also be used in the context of in-situ resource utilization (ISRU) such as scouting for wanted substances and the surveillance of extraction processes. Here, we present two laboratory studies conducted in the context of ISRU with a focus on the chain from prospecting to extracting oxygen from lunar regolith. For LIBS, with optimized data processing and combined with state-of-the-art multivariate data analysis approaches, we show the potential of the technique for identifying samples with increased ilmenite content and for elemental quantification. The measurements were done using lunar regolith simulant and low pressures simulating vacuum on atmosphereless bodies such as the Moon. With Raman spectroscopy, we analyzed lunar regolith simulant samples that underwent electrochemical alteration for oxygen extraction and production of metal alloys demonstrating the potential of Raman spectroscopy for ISRU process monitoring. We also discuss the results in a broader context, evaluating the potential of both methods for other aspects of ISRU support.

Accuracy Improvement For Minor Elements Determination Using Modified Self-Absorption Correction And One-Point Calibration Laser-Induced Breakdown Spectroscopy

Accuracy Improvement For Minor Elements Determination Using Modified Self-Absorption Correction And One-Point Calibration Laser-Induced Breakdown Spectroscopy

Rapid and ultra-sensitive trace metals detection of water by partial Leidenfrost superhydrophobic array surface enhanced laser-induced breakdown spectroscopy

The rapid and ultra-sensitive detection of trace elements in liquid is a primary concern for researchers. In this study, a partial Leidenfrost effect superhydrophobic (PLSHB) array surface was used for rapid in situ evaporation enrichment of sample droplets. Within 4 min, a 50 μL droplet sample was completely evaporated, resulting in all solutes in it being concentrated within a circular range measuring approximately 350 μm in diameter, without the formation of a coffee ring structure. The limits of detection for six metals (Pb, Ba, Be, Mn, Cr, Cu) in water were determined to be as follows: 0.82 μgL−1, 0.27 μgL−1, 0.033 μgL−1, 0.136 μgL−1, 0.241 μgL−1, and 0.083 μgL−1. Furthermore, laser-induced breakdown spectroscopy (LIBS) was employed to detect the enriched solutes from ten liquid samples with identical concentrations on the PLSHB array surface; these measurements exhibited a relative standard deviation (RSD) of only 3.7%. Spike experiments involving the addition of the aforementioned six metals into drinking water demonstrated recovery rates ranging from 85.7% to 117.7%. Therefore, the application potential of PLSHB array surface enhanced LIBS for rapid, stable, and ultra-sensitive detection and analysis of trace metal elements across various fields such as industry, environmental science, and biomedicine might be highly promising.