Characterization of industrially pre-treated waste printed circuit boards for the potential recovery of rare earth elements

Rare earth elements (REE) are classified as critical raw materials and the environmental impact of mining them is of growing concern. The recovery of REE from electronic waste (e-waste) could offer a more sustainable practice. Waste printed circuit boards (WPCBs) are an important resource in the e-waste stream due to their content of valuable materials. However, data regarding the concentration and distribution of REE in WPCBs is very limited. The aims of this research were: (a) to analyse the chemical composition of comminuted WPCBs prior to processing (industrially pre-treated) with emphasis on REE, and (b) to determine the distribution of REE and other metals in different size fractions of the pre-treated WPCBs. The samples were supplied by commercial e-waste recycling companies, which makes them representative of the e-waste processing industry in the UK. Correlation between elemental concentrations and particle size was analysed using Spearman’s rank correlation. Most REE concentrations were inversely correlated to the particle size. Concentrations of Y, La and Gd were found up to a thousand times higher in the smaller particle size compared with coarser particles. However, most of base metals including Cu, Sn, Pb and Zn did not show this trend. The present study highlights the occurrence of REE in comminuted WPCBs, and fine fractions as potential sources of these critical elements, currently not recovered during recycling process. A cost-effective sieving step is proposed to enrich the REE content for further recovery, prevent the possible loss of REE and maximize the total material recovered from WPCBs

Characterisation of “flushable” and “non-flushable” commercial wet wipes using microRaman, FTIR spectroscopy and fluorescence microscopy: to flush or not to flush

The introduction to the market of wet wipes, advertised and labelled as “flushable”, has been the subject of controversy due to their perceived potential to block sewer systems as observed with other non-woven cloths such as traditional non-flushable wipes. Non-woven cloths that enter wastewater systems can find their way into the aquatic environment via wastewater effluents and it has been suggested that the breakdown of these fabrics can release materials such as microplastics into the environment. Worldwide research has revealed the alarming number of aquatic organisms affected by the presence of plastic debris in the aquatic environment harbouring a potential risk to humans through the introduction of microplastics into the food chains. However, the actual material composition of flushable wipes, their fate and impacts in the aquatic environment have not yet been scientifically studied. This paper investigates the fibre composition of flushable and non-flushable wipes, specifically with regard to synthetic polymer material, using Fourier transform infrared (FTIR) and microRaman spectroscopy along with fluorescence microscopy. The study demonstrated the presence of polyester (polyethylene terephthalate, (PET)), high-density polyethylene (HDPE) and polyethylene/vinyl acetate (PEVA/EVA) in some flushable wipes and PET in all non-flushable. Other polymers such us polypropylene (PP), low-density polyethylene (LDPE), expanded polystyrene (EPS) and polyurethane (PU) were also identified as potential components in the flushable material. Hence, commercially available wet wipes labelled as flushable could also be considered as a possible source of microplastic fibres in the wastewater streams and, if not retained, in the environment

Release of microplastic fibres and fragmentation to billions of nanoplastics from period products: preliminary assessment of potential health implications

Health effects related to the plastic content of disposable period products have not been recognized or scientifically addressed. To begin to understand their potential impact on the environment and human health, this study employed standardised in vitro tests (Syngina), infrared spectroscopy (FTIR), confocal Raman microscopy, scanning electron microscopy (FEG-SEM) and nanoparticle tracking analysis (NTA) to characterize the bulk chemical composition of different components in period products, and quantified the amount of fibres released using in vitro experiments, and measured their fragmentation into smaller particles (nanoplastics) under conditions that mimic vaginal fluids. It was found that 12 out of 24 of the tested products contain synthetic polymers (plastics) that would be in direct contact with the vaginal wall when in use. Many of the products released fibres during in vitro tests and also fragmented to release up to 17 billion nanoplastics per tampon. These micro fibres and nanoplastics could be released into the environment upon disposal. The health implications within the body are unknown, but due to the large quantity of nano size plastics being released, public health concern could manifest in three ways: from the nanoplastics themeselves, from release of contaminants adsorbed to the nanoplastics and finally, from leaching of additives associated with the production of the plastics

Robustness and transferability of universal attacks on compressed models

Neural network compression methods like pruning and quantization are very effective at efficiently deploying Deep Neural Networks (DNNs) on edge devices. However, DNNs remain vulnerable to adversarial examples-inconspicuous inputs that are specifically designed to fool these models. In particular, Universal Adversarial Perturbations (UAPs), are a powerful class of adversarial attacks which create adversarial perturbations that can generalize across a large set of inputs. In this work, we analyze the effect of various compression techniques to UAP attacks, including different forms of pruning and quantization. We test the robustness of compressed models to white-box and transfer attacks, comparing them with their uncompressed counterparts on CIFAR-10 and SVHN datasets. Our evaluations reveal clear differences between pruning methods, including Soft Filter and Post-training Pruning. We observe that UAP transfer attacks between pruned and full models are limited, suggesting that the systemic vulnerabilities across these models are different. This finding has practical implications as using different compression techniques can blunt the effectiveness of black-box transfer attacks. We show that, in some scenarios, quantization can produce gradient-masking, giving a false sense of security. Finally, our results suggest that conclusions about the robustness of compressed models to UAP attacks is application dependent, observing different phenomena in the two datasets used in our experiments

HA-grid: security aware hazard analysis for smart grids

Attacks targeting smart grid infrastructures can result in the disruptions of power supply as well as damages to costly equipment, with significant impact on safety as well as on end-consumers. It is therefore of essence to identify attack paths in the infrastructure that lead to safety violations and to determine critical components that must be protected. In this paper, we introduce a methodology (HA-Grid) that incorporates both safety and security modelling of smart grid infrastructure to analyse the impact of cyber threats on the safety of smart grid infrastructures. HA-Grid is applied on a smart grid test-bed to identify attack paths that lead to safety hazards, and to determine the common nodes in these attack paths as critical components that must be protected

A Verilog-A Based Fractional Frequency Synthesizer Model for Fast and Accurate Noise Assessment

This paper presents a new strategy to simulate fractional frequency synthesizer behavioral models with better performance and reduced simulation time. The models are described in Verilog-A with accurate phase noise predictions and they are based on a time jitter to power spectral density transformation of the principal noise sources in a synthesizer. The results of a fractional frequency synthesizer simulation is compared with state of the art Verilog-A descriptions showing a reduction of nearly 20 times. In addition, experimental results of a fractional frequency synthesizer are compared to the simulation results to validate the proposed model

Discovery of faint double-peak Halpha emission in the halo of low redshift galaxies

Aiming at the detection of cosmological gas being accreted onto galaxies of the local Universe, we examined the Halpha emission in the halo of 164 galaxies in the field of view of the Multi-Unit Spectroscopic Explorer Wide survey (\musew ) with observable Halpha (redshift < 0.42). An exhaustive screening of the corresponding Halpha images led us to select 118 reliable Halpha emitting gas clouds. The signals are faint, with a surface brightness of 10**(-17.3 pm 0.3) erg/s/cm2/arcsec2. Through statistical tests and other arguments, we ruled out that they are created by instrumental artifacts, telluric line residuals, or high redshift interlopers. Around 38% of the time, the Halpha line profile shows a double peak with the drop in intensity at the rest-frame of the central galaxy, and with a typical peak-to-peak separation of the order of pm 200 km/s. Most line emission clumps are spatially unresolved. The mass of emitting gas is estimated to be between one and 10**(-3) times the stellar mass of the central galaxy. The signals are not isotropically distributed; their azimuth tends to be aligned with the major axis of the corresponding galaxy. The distances to the central galaxies are not random either. The counts drop at a distance > 50 galaxy radii, which roughly corresponds to the virial radius of the central galaxy. We explore several physical scenarios to explain this Halpha emission, among which accretion disks around rogue intermediate mass black holes fit the observations best.Comment: pay attention to the last sentence of the abstract! Accepted for publication in Ap