Spatio-temporal characterization of ablative Cu plasma produced by femtosecond filaments

Standoff Identification of Plastic Waste Using a Low-Cost Compact Laser-Induced Breakdown Spectroscopy (LIBS) Detection System

We report the standoff/remote identification of post-consumer plastic waste by utilizing a low-cost and compact standoff laser-induced breakdown spectroscopy (ST-LIBS) detection system. A single plano-convex lens is used for collecting the optical emissions from the plasma at a standoff distance of 6.5 m. A compact non-gated Czerny-Turner charge-coupled device (CCD) spectrometer (CT-CCD) is utilized to analyze the optical response. The single lens and CT-CCD combination not only reduces the cost of the detection system by tenfold, but also decreases the collection system size and weight compared to heavy telescopic-based intensified CCD systems. All the samples investigated in this study were collected from a local recycling plant. All the measurements were performed with only a single laser shot which enables rapid identification while probing a large number of samples in real time. Furthermore, principal component analysis has shown excellent separation among the samples and an artificial neural network analysis has revealed that plastic waste can be identified within ∼10 ms only (testing time) with accuracies up to ∼99%. Finally, these results have the potential to build a compact and low-cost ST-LIBS detection system for the rapid identification of plastic waste for real-time waste management applications.

Time-Dependent Intensity Ratio-Based Approach for Estimating the Temperature of Laser Produced Plasma

Reported here is a rapid and simplified approach for modeling the temporal evolution of the plasma temperature. The use of only two emission lines makes this technique simple, accurate, and fast. Usually, multiple emission lines are required for estimating plasma temperature using Boltzmann/Saha-Boltzmann plots. But, in several cases, either multiple emission lines are not available for every element and/or sufficient lines are not free from self-absorption effect. The proposed method greatly increases the possibility of plasma temperature estimation as it requires only two lines. A brass target was used to generate the plasma, using a conventional single-pulse nanosecond laser of ∼7 ns pulse duration at an excitation wavelength of 532 nm. The initial temperature of plasma and the radiation decay constant were estimated using a proposed intensity ratio model. The results were estimated using various combinations of emission lines, which show an excellent agreement with the values obtained using the previously reported method.

Effect of non-resonant background on the extraction of Raman signals from CARS spectra using deep neural networks

We report the retrieval of the Raman signal from coherent anti-Stokes Raman scattering (CARS) spectra using a convolutional neural network (CNN) model. Three different types of non-resonant backgrounds (NRBs) were explored to simulate the CARS spectra viz (1) product of two sigmoids following the original SpecNet model, (2) Single Sigmoid, and (3) fourth-order polynomial function. Later, 50 000 CARS spectra were separately synthesized using each NRB type to train the CNN model and, after training, we tested its performance on 300 simulated test spectra. The results have shown that imaginary part extraction capability is superior for the model trained with Polynomial NRB, and the extracted line shapes are in good agreement with the ground truth. Moreover, correlation analysis was carried out to compare the retrieved Raman signals to real ones, and a higher correlation coefficient was obtained for the model trained with the Polynomial NRB (on average, ∼0.95 for 300 test spectra), whereas it was ∼0.89 for the other NRBs. Finally, the predictive capability is evaluated on three complex experimental CARS spectra (DMPC, ADP, and yeast), where the Polynomial NRB model performance is found to stand out from the rest. This approach has a strong potential to simplify the analysis of complex CARS spectroscopy and can be helpful in real-time microscopy imaging applications.