ABSTRACT
The recycling of refractory scraps began to be forged just over a decade ago. Until then, virtually all refractory scraps were disposed off in landfill sites without any application. Over these past few years, a growing interest and a gain steady momentum of the circular economy, the emergent framing around waste and resource management that promotes the notions of their productive cycling, has been the driving force towards the "zero waste" culture across the spectrum of refractory users and producers. In this way, the circular economy, operated following strategies such as, but not limited to, reusing, recycling, and remanufacturing, has played the pillar role in the different essential value chains of the refractory industry to the entering the new era of secondary raw material supply. In any case, prior to starting any sustainable process, it is really necessary to know the wastes and to classify them. In this context, the present research focused on a refractory residue-classification strategy based on combined laser-induced breakdown spectroscopy (LIBS) and a decision tree algorithm for a qualitative analytical performance. This tandem approach allowed the categorization of a rich set of residues in up to 10 different refractory groups. By choosing original LIBS emission intensities and intensity ratios involving the most relevant constituent elements (Al, Mg, C âthrough its related-species CNâ, Si and Zr) of various refractory wastes, a decision tree with multiple nodes that decided how to classify inputs was designed and trained. Categorization performed from LIBS emission spectra of "blind" refractory residues showed that LIBS data combined with this supervised machine learning algorithm provided good refractory scraps-classification performance, with a classification accuracy of up to 75%. However, some more than justified decisions of the algorithm on allegedly misclassified residues showed that scores for the decision tree could found to be far superior to those obtained. The results achieved support the strategy designed for its industrial implementation, either directly in the iron and steel industry, as the major end-user of refractories, in the refractory waste management industry, or in both.
Subject(s)
Algorithms , Lasers , Decision Trees , Iron , Spectrum AnalysisABSTRACT
The present work focuses on the influence of the angle of observation on the emission signal from copper plasmas. Plasma plumes have been generated inside a home-made chamber consisting of two parallel glass windows spaced by 2.5 mm. This chamber allows observing plasma plumes from different collection angles throughout their perimeter, spanning from 20° to 80° with respect to the surface of the Cu target. In order to minimize the observed volume of the plasma, measurements were made from the closest distance possible through a metallic hollow tube. Single-pulse and collinear double-pulse excitation schemes with a Nd:YAG laser (1064 nm, 5 ns) have been investigated. The results have shown that the selection of the best angle to collect light from the plasma is related to the excitation mode. On the other hand, the shot-to-shot signal variability has been found to depend on the shape of plasma plumes. In single-pulse excitation, a good correlation between the observed laser-induced breakdown spectroscopy (LIBS) emission (from spatially confined plumes) and their integrated signal of plasma image has been ascertained. However, this fact was less evident in double-pulse LIBS, which could be due to a different mechanism involved in the ablation process.
ABSTRACT
The potential of a multi-pulse (MP) laser excitation scheme for deep stratigraphy of electrolytically galvanized steel using laser-induced breakdown spectrometry (LIBS) has been evaluated. For this purpose, a commercial electro-optically (EO) Q-switched Nd:YAG laser was employed, where by reducing the delay between the Q-switch opening and the flash lamp, a train of pulses (up to 11) separated by approximately 7.40 µs was generated during one lamp flashing. Plasma emission after each individual laser pulse of the MP sequence was detected by a spectrograph equipped with an intensified charge-coupled device (iCCD) detector. With MP excitation, the ablation efficiency was increased ten-fold on iron sample and 22.5-fold on zinc material with respect to dual-pulse or single-pulse excitation. The LIBS signal generated by MP excitation shows an analogous enhancement. Although the total energy per shot delivered to samples was only 60 mJ, it was possible using LIBS to measure the sample stratigraphy up to depths of 90 µm on zinc-coated steel sheets. A satisfactory agreement between the Zn thickness determined by the MP-LIBS system and data from the manufacturer has also been obtained.
ABSTRACT
The application of laser-induced breakdown spectroscopy (LIBS) for online analysis of novel Zn based alloy coatings during continuous production of galvannealed steel has been demonstrated. Field trials were carried out at the ThyssenKrupp Steel (TKS) pilot plant in Dortmund, Germany. For this purpose, a portable LIBS demonstrator was constructed and evaluated, based on a dual-pulse Q-switched Nd:YAG laser, operated at 1064 nm. This system was used to generate plasmas on the moving sample surface after the annealing process, in order to control on-line the thickness of Mg on electrolytically galvanized steel. For variable Mg thicknesses (depending on strip speed of the pilot line, 100-1200 nm), and for steel sheets with a predetermined and constant Zn thickness (of 2 or 9 µm), a satisfactory agreement between plant LIBS measurements and data from laboratory chemical analysis (dissolution of the metallic coating and subsequent inductively coupled plasma-optical emission spectroscopy (ICP-OES) analysis) of Mg coating thicknesses has been obtained. The effects of environmental conditions on field measurements (strip temperature, mechanical vibrations, moisture on surface, etc.) have been demonstrated to be negligible, whereas minimal damage (crater diameters less than 150 µm) to the sample surface was caused.
