An extensive investigation on the
noble metal (NM) content in different
classes of waste printed circuit boards (WPCBs: random access memories,
RAMs; network interface controllers, NICs; motherboards; TV, DVD/CD
player, hard-drive, and mobile phone PCBs) has been performed to define
the most appropriate case study and provide a robust database useful
for workers in the waste valorization field. Following accurate selection,
mechanical comminution, representative sampling, quantitative digestion,
and analytical characterization (ICP-AES), RAMs and mobile phone PCBs
confirmed to be the “richest” source, while TV PCBs
are the “poorest” one in term of NM content. Accordingly,
the RAM case study has been employed for the application of a new
NMs recovery method, previously set up on finely comminuted waste
electric and electronic equipment underwent materials enrichment by
mechanical separation. Despite the very large amount of vitreous-plastic
and metallic materials present in the mixture, satisfactory NM recovery
yields (Cu 70%, Ag 92%, Au 64%) with limited byproduct formation have
been obtained using safe and recyclable reagents in mild conditions:
citric acid for base metal leaching, ammonia in oxidizing environment
for Cu and Ag separation and recovery, triiodide aqueous solution
for gold recovery, at room pressure, and 25–100 °C. The
reported results provide useful quantitative parameters for assessing
the profitability of an industrial scale-up of the new sustainable
NMs recovery method.
Waste of electric and electronic equipment (WEEE) is the fastest-growing waste stream in Europe. The large amount of electric and electronic products introduced every year in the market makes WEEE disposal a relevant problem. On the other hand, the high abundance of key metals included in WEEE has increased the industrial interest in WEEE recycling. However, the high variability of materials used to produce electric and electronic equipment makes key metals’ recovery a complex task: the separation process requires flexible systems, which are not currently implemented in recycling plants. In this context, hyperspectral sensors and imaging systems represent a suitable technology to improve WEEE recycling rates and the quality of the output products. This work introduces the preliminary tests using a hyperspectral system, integrated in an automatic WEEE recycling pilot plant, for the characterization of mixtures of fine particles derived from WEEE shredding. Several combinations of classification algorithms and techniques for signal enhancement of reflectance spectra were implemented and compared. The methodology introduced in this study has shown characterization accuracies greater than 95%.
Waste from electric and electronic equipment (WEEE) represents the fastest growing waste stream in EU. The large amount and the high variability of electric and electronic products introduced every year in the market make the WEEE recycling process a complex task, especially considering that mechanical processes currently used by recycling companies are not flexible enough. In this context, hyperspectral imaging systems (HSI) can represent an enabling technology able to improve the recycling rates and the quality of the output products. This study shows the preliminary results achieved using a HSI technology in a WEEE recycling pilot plant, for the characterization of fine metal particles derived from WEEE shredding.
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