NIR-MFCO dataset: Near-infrared-based false-color images of post-consumer plastics at different material flow compositions and material flow presentations.

Determining mass-based material flow compositions (MFCOs) is crucial for assessing and optimizing the recycling of post-consumer plastics. Currently, MFCOs in plastic recycling are primarily determined through manual sorting analysis, but the use of inline near-infrared (NIR) sensors holds potential to automate the characterization process, paving the way for novel sensor-based material flow characterization (SBMC) applications. This data article aims to expedite SBMC research by providing NIR-based false-color images of plastic material flows with their corresponding MFCOs. The false-color images were created through the pixel-based classification of binary material mixtures using a hyperspectral imaging camera (EVK HELIOS NIR G2-320; 990 nm-1678 nm wavelength range) and the on-chip classification algorithm (CLASS 32). The resulting NIR-MFCO dataset includes n = 880 false-color images from three test series: (T1) high-density polyethylene (HDPE) and polyethylene terephthalate (PET) flakes, (T2a) post-consumer HDPE packaging and PET bottles, and (T2b) post-consumer HDPE packaging and beverage cartons for n = 11 different HDPE shares (0% - 50%) at four different material flow presentations (singled, monolayer, bulk height H1, bulk height H2). The dataset can be used, e.g., to train machine learning algorithms, evaluate the accuracy of inline SBMC applications, and deepen the understanding of segregation effects of anthropogenic material flows, thus further advancing SBMC research and enhancing post-consumer plastic recycling.

Influence of material alterations and machine impairment on throughput related sensor-based sorting performance.

Experiments with sensor-based sorting (SBS) machinery provide insight into the effect of throughput rate and input composition on the sorting performance. For this purpose, material mixtures with certain compositions and particle size distributions were created from waste fractions and sorted at various throughput rates. To evaluate the sorting performance of the SBS unit (using near infrared technology) in dependence of the applied load, four assessment factors concerning the output fractions were studied: yield, product purity, recovery/product quantity and incorrectly discharged share of reject particles. The influences on the assessment parameters of light twodimensional (2D) particles in the input of a sorting stage and failing air valves in an SBS unit were evaluated for various input compositions at different throughput rates. It was found that a share of approximately 5 wt% 2D particles in the input had a similar negative effect on the yield as the malfunction of 20% of all air valves in an SBS machine at high throughput rates. Additionally, the failure of the air valves reduced the product purity of the sorting stage at increased throughput rates. Furthermore, qualitative observations concerning systematic effects of prior studies could be confirmed. Resulting graphs for a specific input composition of an SBS unit at varying throughput rates could be used to adjust the throughput rate to meet the exact demands for a sorting stage.

X-ray fluorescence sorting of non-ferrous metal fractions from municipal solid waste incineration bottom ash processing depending on particle surface properties.

A heavy non-ferrous metal fraction (< 50 mm) of municipal solid waste incineration bottom ashes from wet-mechanical treatment was separated by screening, magnetic separation and eddy-current separation into ferrous metals, non-ferrous metals and residual sub-fractions. The non-ferrous metal fractions were divided and subjected to (i) a washing process, (ii) dry abrasion and (iii) no mechanical pre-treatment to study the effect of resulting different surface properties on a subsequent X-ray fluorescence sorting into precious metals, zinc, copper, brass, stainless steel and a residual fraction. The qualities of the X-ray fluorescence output fractions were investigated by chemical analyses (precious metal fraction and the residual fraction), pyrometallurgical tests and subsequent chemical analyses of the metals and slags produced by the melting processes (zinc, copper, brass and stainless steel fraction). Screening directs brass and stainless steel primarily into the coarser fractions, while copper and residual elements were rather transferred into the finer fractions. X-ray fluorescence sorting yielded zinc, copper, brass, stainless steel and precious metals fractions in marketable qualities. Neither a negative nor a positive impact of mechanical pre-treatment on the composition of these fractions was identified. Solely the yield of the brass fraction in the grain size 16-20 mm decreased with increasing mechanical pre-treatment. The pre-treatment also had no impact on yield and quality of the products of pyrometallurgical tests.

Influence of surface roughness and surface moisture of plastics on sensor-based sorting in the near infrared range.

In the project 'NEW-MINE' the use of sensor-based sorting machinery in the field of 'landfill mining' is investigated. Defilements pose a particular challenge in the treatment and sorting of plastics contained in landfills. For this reason, the effects of various pollutants caused by the interactions in the landfill body or the mechanical treatment steps in landfill mining are examined. In the following elaboration, the focus is on the influences of surface moisture and surface roughness of plastics on sensor-based sorting by means of near-infrared technology. Near-infrared radiation (NIR) in a wavelength range of 990 nm to 1500 nm has been used for the detection and classification of plastic particles. The experiments demonstrate that increased surface roughness reduces signal noise and thereby improves the classification of both spectrally similar and transparent plastics, but reduces the yield of low-softening plastics because their sliding speed on a sensor-based chute sorter varies as a result of the heating of the chute. Surface moisture causes the absorption of radiation from 1115 nm (high density polyethylene [HDPE], linear low density polyethylene [LLDPE], polyethylen terephthalate [PET] and polyvinylchloride [PVC]) or from 1230 nm (low density polyethylene [LDPE], polypropylene [PP] and thermoplastic polyurethane [TPU]) up to at least 1680 nm, which causes amplification or attenuation of various extremes in the derivative. However, the influence of surface moisture on the yield of plastics is usually very low and depends on the spectral differences between the different plastics.