Recent advances in laser-induced breakdown spectroscopy quantification: From fundamental understanding to data processing

Beam-crossing configuration to control plasma position, improve spatial resolution, and enhance emissions in single-pulse, laser-induced breakdown spectroscopy in gases

We report a relatively simple configuration of laser-induced breakdown spectroscopy (LIBS) that is suitable for gas flow diagnostics with increased spatial resolution, signal intensity, and stability. In this optical configuration, two laser beams are generated by splitting a single laser beam, and then they are focused and crossed orthogonally at the detection volume from two different optical paths. Different from dual-pulse LIBS, this LIBS configuration uses only one laser source, and thus is of relatively low cost. Several advantages were found for this simple beam-crossing LIBS when it was demonstrated in air in the present work, particularly on signal enhancement and stabilization, confining plasma volume, and controlling plasma position. Both of the latter two advantages are relevant to spatial resolution improvement of LIBS in gases, which has rarely been discussed in previous reports. An enhancement factor of 2 was found for atomic hydrogen, nitrogen, and oxygen emissions with respect to conventional LIBS. Another advantage is that the position of breakdown can be precisely controlled through adjustment of the propagation of the two beams, also resulting in smaller plasma volume and stable emission intensity. Furthermore, the technique is moderately tolerant to dust particles neutrally present in the environment, avoiding the spark occurring at a position out of the detection volume. Beyond LIBS, the new configuration has other potential applications, e.g., laser-induced ignition, which is also briefly discussed.

Improvement of sample discrimination using laser-induced breakdown spectroscopy with multiple-setting spectra

Laser-induced breakdown spectroscopy (LIBS) is a promising multi-elemental analysis technique and has the advantages of rapidness and minimal sample preparation. In traditional LIBS measurement, sample spectra are generally collected based on a single set of fixed experimental parameters, such as laser energy and delay time. When samples have the same main components and similar component concentrations, the difference in their spectral intensities becomes less obvious. This can lower the sensitivity of LIBS measurement and pose a threat to the accuracy and robustness of LIBS qualitative analysis. In this work, we propose a new method to increase the spectral difference between similar samples, namely multiple-setting spectra. For each sample, it adopts different sets of experimental parameters and obtains a group of spectra to increase the fingerprint spectral information. The effectiveness of the proposed method is theoretically verified and then tested on 11 similar coal samples. Specifically, the sample spectra were collected with different laser energy and delay time, and processed by principal component analysis (PCA) and Davies-Bouldin index (DBI). The results show that the use of multiple-settings spectra can significantly improve the sample discrimination accuracy from 81.8% to 96.4%. In addition, the proposed method can maintain the efficiency and cost of LIBS measurement.

Accuracy improvement in plastics classification by laser-induced breakdown spectroscopy based on a residual network

The whole ecosystem is suffering from serious plastic pollution. Automatic and accurate classification is an essential process in plastic effective recycle. In this work, we proposed an accurate approach for plastics classification using a residual network based on laser-induced breakdown spectroscopy (LIBS). To increasing efficiency, the LIBS spectral data were compressed by peak searching algorithm based on continuous wavelet, then were transformed to characteristic images for training and validation of the residual network. Acrylonitrile butadiene styrene (ABS), polyamide (PA), polymethyl methacrylate (PMMA), and polyvinyl chloride (PVC) from 13 manufacturers were used. The accuracy of the proposed method in few-shot learning was evaluated. The results show that when the number of training image data was 1, the verification accuracy of classification by plastic type under residual network still kept 100%, which was much higher than conventional classification algorithms (BP, kNN and SVM). Furthermore, the training and testing data were separated from different manufacturers to evaluate the anti-interference properties of the proposed method from various additives in plastics, where 73.34% accuracy was obtained. To demonstrate the superiority of classification accuracy in the proposed method, all the evaluations were also implemented by using conventional classification algorithm (kNN, BP, SVM algorithm). The results confirmed that the residual network has a significantly higher accuracy in plastics classification and shows great potential in plastic recycle industries for pollution mitigation.

Evaluation of femtosecond laser-induced breakdown spectroscopy system as an offline coal analyzer

Developments in femtosecond laser induced breakdown spectroscopy (fs-LIBS) applications during the last two decades have further centered on innovative métier tie-in to the advantageous properties of femtosecond laser ablation (fs-LA) introduced into LIBS. Yet, for industrially-oriented application like coal analysis, no research has exposed to view the analytical capabilities of fs-LA in enhancing the physical processes of coal ablation and the impact into quantitative correlation of spectra and data modeling. In a huge coal market, fast and accurate analysis of coal property is eminently important for coal pricing, combustion optimization, and pollution reduction. Moreover, there is a thirst need of precision standardization for coal analyzers in use. In this letter, the analytical performance of a one-box femtosecond laser system is evaluated relative to an industrially applied coal analyzer based on five objectives/measures: spectral correlation, relative sensitivity factors, craters topology, plasma parameters, and repeatability. Despite high-threshold operation parameters of the fs system, competitive results are achieved compared to the optimized analytical conditions of the ns-coal analyzer. Studies targeting the in-field optimization of fs-LIBS systems for coal analysis can potentially provide insights into fs-plasma hydrodynamics under harsh conditions, instrumental customization, and pave the way for a competitive next-generation of coal analyzers.