Lithium ion detection in liquid with low detection limit by laser-induced breakdown spectroscopy

Sensitivity, precision, and accuracy of fs-LIBS for heavy metal detection in flowing aqueous solutions

This investigation employs femtosecond laser-induced breakdown spectroscopy (fs-LIBS) to measure the concentrations of chromium (Cr), lead (Pb), and copper (Cu) in flowing aqueous solutions. The fs pulsed laser excites the water, generating plasma in a dynamic setting that prevents liquid splashing-a notable advantage over static methods. The flowing water column maintains a stable liquid level, circumventing the laser focus irregularities due to liquid-level fluctuations. Calibration curves, based on a linear function, reveal limits of detection (LODs) as low as 0.0179 μg/mL for Cr, 0.1301 μg/mL for Pb, and 0.0120 μg/mL for Cu. The reliability of the experiment is confirmed by R2 values exceeding 0.99. These findings offer valuable insights for the analysis of trace heavy metals in flowing aqueous solutions using fs-LIBS, demonstrating the technique's potential for environmental monitoring.

Determination of detonation characteristics by laser-induced plasma spectra and micro-explosion dynamics

Determination of macroscale detonation parameters of energetic materials (EMs) in a safe and rapid way is highly desirable. However, traditional experimental methods suffer from tedious operation, safety hazards and high cost. Herein, we present a micro-scale approach for high-precision diagnosis of explosion parameters based on radiation spectra and dynamic analysis during the interaction between laser and EMs. The intrinsic natures of micro-explosion dynamics covering nanosecond to millisecond and chemical reactions in laser-induced plasma are revealed, which reveal a tight correlation between micro-detonation and macroscopic detonation based on laser-induced plasma spectra and dynamics combined with statistic ways. As hundreds to thousands of laser pulses ablate on seven typical tetrazole-based high-nitrogen compounds and ten single-compound explosives, macroscale detonation performance can be well estimated with a high-speed and high-accuracy way. Thereby, the detonation pressure and enthalpies of formation can be quantitatively determined by the laser ablation processes for the first time to our knowledge. These results enable us to diagnose the performance of EMs in macroscale domain from microscale domain with small-dose, low-cost and multiple parameters.

Determining metal elements in liquid samples using laser-induced breakdown spectroscopy and phase conversion technology

A phase conversion technology, involving the loading of brine samples with anionic polyacrylamide (APAM) colloidal droplets, is proposed to detect metal elements rapidly and accurately in liquid samples using laser-induced breakdown spectroscopy. The experimental conditions were optimized by comparing the obtained emission intensities and the signal-to-noise ratios, including the concentration of APAM, volume ratio of APAM solution to sample, delay time, and lens-to-sample distance (LTSD). Three kinds of complex brine samples with slightly soluble salts were used to test the analytical performance of the proposed method. The results show that the discrepancies of the concentrations of Li, Sr and Ca were 0.74-3.59%, compared with those obtained using inductively coupled plasma-optical emission spectrometry. This suggests that the proposed method can successfully determine metal elements in liquid samples, featuring short sample preparation time (less than 20 min), small sample volume (10 μL), and simple operation (no adsorption).

Detection of Low Lithium Concentrations Using Laser-Induced Breakdown Spectroscopy (LIBS) in High-Pressure and High-Flow Conditions

This paper describes the effects of laser pulse rate and solution flow rate on the determination of lithium at high pressure for water and 2.5% sodium chloride solutions using laser-induced breakdown spectroscopy (LIBS). Preliminary studies were performed with 0-40 mg L^-1 Li solutions, at ambient pressure and at 210 bar, and in static and flowing (6 mL · min^-1) regimes, for a combination of four different measurement conditions. The sensitivity of calibration curves depended on the pressure and the flow rate, as well as the laser pulse rate. The sensitivity of the calibration curve increased about 10% and 18% when the pressure was changed from 1 to 210 bar for static and flowing conditions, respectively. However, an effect of flow rate at high pressure for both 2 and 10 Hz laser pulse rates was observed. At ambient pressure, the effect of flow rate was negligible, as the sensitivity of the calibration curve decreased around 2%, while at high pressure the sensitivity increased around 4% when measurements were performed in a flow regime. Therefore, it seems there is a synergistic effect between pressure and flow rate, as the sensitivity increases significantly when both changes are considered. When the pulse rate is changed from 2 to 10 Hz, the sensitivity increases 26-31%, depending on the pressure and flow conditions. For lithium detection limit studies, performed with a laser pulse energy of 2.5 mJ, repetition rate of 10 Hz, gate delay of 500 ns, gate width of 1000 ns, and 1000 accumulations, a value around 40 µg L^-1 was achieved for Li solutions in pure water for all four measurement conditions, while a detection limit of about 92 µg L^-1 was determined for Li in 2.5% sodium chloride solutions, when high pressure and flowing conditions were employed. The results obtained in the present work demonstrate that LIBS is a powerful tool for the determination of Li in deep ocean conditions such as those found around hydrothermal vent systems.

Quantitative analysis of lithium in brine by laser-induced breakdown spectroscopy based on convolutional neural network

In this study, a simple and effective method for accurate determination of lithium in brine samples was developed by the combination of laser induced breakdown spectroscopy (LIBS) and convolutional neural network (CNN). Our results clearly demonstrate that the use of CNN could efficiently overcome the complex matrix effects, and thus allows for on-site Li quantitative determination in brine samples by LIBS. Specifically, two CNN models with different input data (M-CNN with matrix emission lines, and DP-CNN with double Li lines) were constructed based on the primary matrix features on spectrum and Boltzmann equation, respectively. It was observed that DP-CNN model could greatly improve the accuracy of Li analysis. We also compared the quantitative analysis capabilities of DP-CNN model with partial least squares regression (PLSR) and principal component analysis-support vector regression (PCA-SVR) model, and the results clearly showed DP-CNN offers the best quantification results (higher accuracy and less matrix interference). Finally, five real brine samples were successfully analyzed by the proposed DP-CNN model, confirming by the average absolute error of the prediction of 0.28 mg L^-1 and the average relative error of 3.48%. These results clearly demonstrate that input data plays an important role in the training of CNN model in LIBS analysis, and the proposed DP-CNN provides an effective approach to solve the matrix effects encountered in LIBS for Li measurement in brine samples.