A Review on Pulsed Laser Fabrication of Nanomaterials in Liquids for (Photo)catalytic Degradation of Organic Pollutants in the Water System.

The water pollution caused by the release of organic pollutants has attracted remarkable attention, and solutions for wastewater treatment are being developed. In particular, the photocatalytic removal of organic pollutants in water systems is a promising strategy to realize the self-cleaning of ecosystems under solar light irradiation. However, at present the semiconductor-based nanocatalysts can barely satisfy the industrial requirements because their wide bandgaps restrict the effective absorption of solar light, which needs an energy band modification to boost the visible light harvesting via surface engineering. As an innovative approach, pulsed laser heating in liquids has been utilized to fabricate the nanomaterials in catalysis; it demonstrates multi-controllable features, such as size, morphology, crystal structure, and even optical or electrical properties, with which photocatalytic performances can be precisely optimized. In this review, focusing on the powerful heating effect of pulsed laser irradiation in liquids, the functional nanomaterials fabricated by laser technology and their applications in the catalytic degradation of various organic pollutants are summarized. This review not only highlights the innovative works of pulsed laser-prepared nanomaterials for organic pollutant removal in water systems, such as the photocatalytic degradation of organic dyes and the catalytic reduction of toxic nitrophenol and nitrobenzene, it also critically discusses the specific challenges and outlooks of this field, including the weakness of the produced yields and the relevant automatic strategies for massive production.

High-sensitivity determination of available cobalt in soil using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence.

Conventional laser-induced breakdown spectroscopy could not conduct high-sensitivity determination of available cobalt due to spectral interference and weak spectral intensity. To improve the poor detection sensitivity of available cobalt in soil, available cobalt was extracted from soil and prepared. Laser-induced breakdown spectroscopy assisted with laser-induced fluorescence was introduced to excite and detect the cobalt element. The results showed that coefficients of the calibration curve for the available cobalt element could reach 0.9991, and the limits of detection could reach 0.005 mg/kg in soil under optimized conditions, which were all much better than conventional LIBS and reach the international minimum detection standards. This work provides a possible approach for detecting available trace elements in soil.

The distribution of high-quality internal standard lines and their selection method based on the Q-value in portable laser-induced breakdown spectroscopy.

Internal standard lines play a crucial role in the univariate quantitative analysis in portable laser-induced breakdown spectroscopy (LIBS) technology. To overcome the uncertainty of the conventional internal standard method, the distribution principles of high-quality internal standard lines were studied and revealed at the macro and micro levels, and an automatic internal standard line selection method based on the Q-value was proposed. Using this method, in the quantitative analysis of Si in low-alloy steel samples, the average relative error of cross-validation (ARECV), root mean squared error of cross-validation (RMSECV), and the limit of detection (LoD) were decreased significantly from 27.42%, 0.041 wt%, and 1060 µg g-1 to 18.65%, 0.026 wt%, and 680 µg g-1, respectively. The quantitative analysis results of Cr, Cu and Ni showed that it has excellent generalization ability. The results indicate that this method can screen out the optimal internal standard lines efficiently and accurately, which provides a new approach to improve the performance of univariate quantitative analysis in portable LIBS.

Sensitive analysis of fluorine and chlorine elements in water solution using laser-induced breakdown spectroscopy assisted with molecular synthesis.

Fluorine and chlorine are key elements to affecting water quality, but they are hard to be determined by conventional laser-induced breakdown spectroscopy (LIBS). To achieve high sensitivity detection of them, the CaF and CaCl molecules were synthesized by combining calcium in calcite and F and Cl in sample. The temporal characteristics of CaF and CaCl molecular emissions were investigated. It shows that molecular emission of CaF and CaCl has a longer lifetime and high spectral intensity than that of their atomic emissions. Such unique feature of molecular emission inspired us to use it for high sensitivity analysis of Cl and F elements in water. The results show that these two elements can be sensitively and accurately detected using LIBS assisted with molecular emission. The limits of detections (LoDs) were 0.38 mg/L and 1.03 mg/L for F and Cl elements, respectively, and the limit of quantitation (LoQ) was 3.404 mg/L to 20.569 mg/L for fluorine elements and 9.986 mg/L to 39.757 mg/L for fluorine. These detection limits can meet the World Health Organization's detection requirements for F and Cl elements in water. The results show that LIBS assisted with molecular synthesis has a huge potential in water quality monitoring.

Sulfur determination in laser-induced breakdown spectroscopy combined with resonance Raman scattering.

Sulfur is an essential element in industry, but it is difficult to be detected by laser-induced breakdown spectroscopy (LIBS). In this work, the disulfide radical Raman scattering was observed in sulfur plasma by combining LIBS with resonance Raman scattering (LIBS-RRS). Sulfur has been ablated by a focused laser beam to generate plasma, in which some sulfur atoms were combined to form disulfide radicals. The disulfide radical resonance Raman was excited by a 306.4 nm wavelength laser and observed at 710 and 1420 cm-1 Raman shift. Using different contents of sulfur mixed with alumina (Al2O3) powder, both LIBS and LIBS-RRS calibrations were obtained at the same ablation laser energy. The calibration curve of sulfur atomic emission S I 921.28 nm was set up, and the linear coefficient (R2) was 0.285 and the detection limit (LoD) was 13.092 wt %. While the R2 was 0.966 and LoD was 0.118 wt % for S2 710 cm-1 in LIBS-RRS. The results indicate that disulfide radical Raman scattering by LIBS-RRS is promising for the determination of sulfur content and the diagnosis of molecular evolution in plasma.

An image features assisted line selection method in laser-induced breakdown spectroscopy.

Analytical lines play a crucial role in laser-induced breakdown spectroscopy (LIBS) technology. To improve the classification performance of LIBS, an image features assisted line selection (IFALS) method which based on spectral morphology and the characteristics of Harris corners was proposed. With this method, a classification experiment for 24 metamorphic rock samples was conducted with linear discriminant analysis (LDA) algorithm. The result showed that the classification accuracy was increased from 94.38% of the conventional classification model MLS-LDA (Manual line selection-linear discriminant analysis) to 98.54% of IFALS-LDA. Furthermore, the time required for the whole classification process was decreased from 2768.38 s of MLS-LDA to 4.36 s of the proposed method, thus the classification efficiency was greatly improved. In addition, compared with the existing automatic line selection method, the convergence rate of IFALS-LDA is significantly faster than that of ASPI (Automatic spectral peaks identification)-LDA. This study demonstrates that LIBS assisted with the image features in machine vision can promote the analytical performance of LIBS technology.

A quantitative analysis method assisted by image features in laser-induced breakdown spectroscopy.

The determination accuracy of alloying elements in high alloy steel is generally poor in laser-induced breakdown spectroscopy (LIBS) due to their matrix effect. To solve this problem, an image quantitative analysis (IQA) method was proposed and verified by determining nickel (Ni) in 17 stainless steel samples in this work. The results showed that the coefficient of determination (R2) was increased from 0.9833 of a conventional spectrum quantitative analysis (SQA) method to 0.9996 of the IQA method, and the average relative error of cross-validation (ARECV) and root mean squared error of cross-validation (RMSECV) were decreased from 56.80% and 1.0818 wt% to 15.93% and 0.9866 wt%, respectively. Besides, the determinations of chromium (Cr) and silicon (Si) demonstrated the generalization ability of the IQA. This study provides an effective approach to improving the quantitative performance of LIBS through the combination of image processing and computer vision technology.

Determination of chlorine with radical emission using laser-induced breakdown spectroscopy coupled with partial least square regression.

Chlorine is a crucial element which may cause the corrosion of reinforced concrete. However, the strongest chlorine atom/ion emission lines are in the UV region and the ground state atom is hard to excite by conventional single-pulsed laser-induced breakdown spectroscopy (SP-LIBS). Radical emission is a feasible alternative to atom/ion emission when detecting chlorine concentration. Here, Cl atomic emission and calcium chloride (CaCl) radicals were detected in SP-LIBS, the calibrations of both emissions were compared. To further improve the accuracy, partial least square regression (PLSR) was adopted to establish the calibrations. The results showed that CaCl radical signal is stronger than Cl atomic signal with low energy SP-LIBS in open air, achieving a LoD (limit of detection) of 0.0404 wt%. Meanwhile, CaCl calibration had a better accuracy with coefficient of determination (R2) and root mean square error of cross validation (RMSECV) of 0.9930 and 0.2016 wt% with the help of PLSR. In conclusion, this work provided a potential approach for Chlorine determination in industry.

Classification accuracy improvement of laser-induced breakdown spectroscopy based on histogram of oriented gradients features of spectral images.

To improve the classification accuracy of laser-induced breakdown spectroscopy (LIBS), image histogram of oriented gradients (HOG) features method (IHFM) for materials analysis was proposed in this work. 24 rice (Oryza sativa L.) samples were carried out to verify the proposed method. The results showed that the classification accuracy of rice samples by the full-spectra intensities method (FSIM) and IHFM were 60.25% and 81.00% respectively. The classification accuracy was obviously improved by 20.75%. Universality test results showed that this method also achieved good results in the plastics, steel, rock and minerals classification. This study provides an effective method to improve the classification performance of LIBS.