Multi-sensor characterization for an improved identification of polymers in WEEE recycling.

Polymers represent around 25% of total waste from electronic and electric equipment. Any successful recycling process must ensure that polymer-specific functionalities are preserved, to avoid downcycling. This requires a precise characterization of particle compounds moving at high speeds on conveyor belts in processing plants. We present an investigation using imaging and point measurement spectral sensors on 23 polymers including ABS, PS, PC, PE-types, PP, PVC, PET-types, PMMA, and PTFE to assess their potential to perform under the operational conditions found in recycling facilities. The techniques applied include hyperspectral imaging sensors (HSI) to map reflectance in the visible to near infrared (VNIR), short-wave (SWIR) and mid-wave infrared (MWIR) as well as point Raman, FTIR and spectroradiometer instruments. We show that none of the sensors alone can identify all the compounds while meeting the industry operational requirements. HSI sensors successfully acquired simultaneous spatial and spectral information for certain polymer types. HSI, particularly the range between (1600-1900) nm, is suitable for specific identification of transparent and light-coloured (non-black) PC, PE-types, PP, PVC and PET-types plastics; HSI in the MWIR is able to resolve specific spectral features for certain PE-types, including black HDPE, and light-coloured ABS. Fast-acquisition Raman spectroscopy (down to 500 ms) enabled the identification of all polymers regardless their composition and presence of black pigments, however, it exhibited limited capacities in mapping applications. We therefore suggest a combination of both imaging and point measurements in a sequential design for enhanced robustness on industrial polymer identification.

Detection of REEs with lightweight UAV-based hyperspectral imaging.

Rare earth elements (REEs) supply is important to ensure the energy transition, e-mobility and ultimately to achieve the sustainable development goals of the United Nations. Conventional exploration techniques usually rely on substantial geological field work including dense in-situ sampling with long delays until provision of analytical results. However, this approach is limited by land accessibility, financial status, climate and public opposition. Efficient and innovative methods are required to mitigate these limitations. The use of lightweight unmanned aerial vehicles (UAVs) provides a unique opportunity to conduct rapid and non-invasive exploration even in socially sensitive areas and in relatively inaccessible locations. We employ drones with hyperspectral sensors to detect REEs at the earth's surface and thus contribute to a rapidly evolving field at the cutting edge of exploration technologies. We showcase for the first time the direct mapping of REEs with lightweight hyperspectral UAV platforms. Our solution has the advantage of quick turn-around times (< 1 d), low detection limits (< 200 ppm for Nd) and is ideally suited to support exploration campaigns. This procedure was successfully tested and validated in two areas: Marinkas Quellen, Namibia, and Siilinjärvi, Finland. This strategy should invigorate the use of drones in exploration and for the monitoring of mining activities.

Multiple Optical Sensor Fusion for Mineral Mapping of Core Samples.

Geological objects are characterized by a high complexity inherent to a strong compositional variability at all scales and usually unclear class boundaries. Therefore, dedicated processing schemes are required for the analysis of such data for mineralogical mapping. On the other hand, the variety of optical sensing technology reveals different data attributes and therefore multi-sensor approaches are adapted to solve such complicated mapping problems. In this paper, we devise an adapted multi-optical sensor fusion (MOSFus) workflow which takes the geological characteristics into account. The proposed processing chain exhaustively covers all relevant stages, including data acquisition, preprocessing, feature fusion, and mineralogical mapping. The concept includes (i) a spatial feature extraction based on morphological profiles on RGB data with high spatial resolution, (ii) a specific noise reduction applied on the hyperspectral data that assumes mixed sparse and Gaussian contamination, and (iii) a subsequent dimensionality reduction using a sparse and smooth low rank analysis. The feature extraction approach allows one to fuse heterogeneous data at variable resolutions, scales, and spectral ranges and improve classification substantially. The last step of the approach, an SVM classifier, is robust to unbalanced and sparse training sets and is particularly efficient with complex imaging data. We evaluate the performance of the procedure with two different multi-optical sensor datasets. The results demonstrate the superiority of this dedicated approach over common strategies.

Comparing the optical properties and thermal stability of green (TbPO4), yellow (DyPO4), and red (PrPO4) emitting single crystal samples.

Blue, green and red-emitting phosphors for near-UV/blue based phosphor blend converted white-light emitting devices have been investigated extensively over the past years. Herein, we present our results on the optical spectroscopy of single crystal samples of TbPO4, DyPO4 and PrPO4 exhibiting prominent emission at green (545 nm), yellow (574 nm) and red (616 nm) region of the electromagnetic spectrum, respectively. We study the temperature dependence of their emission spectra for excitations at 365 and 455 nm, to mimic experimental conditions for phosphor converted light emitting diodes, to show that their thermal quenching temperature is 730 K for TbPO4 (excitation 365 nm), 490 and 520 K for DyPO4 (excitation at 365 and 455 nm), and 540 K for PrPO4 (excitation 455 nm). The TbPO4 emission does not show any considerable blue/red shift at elevated temperatures, while DyPO4 emission is observed close to the center of CIE coordinate diagram. The PrPO4 sample possesses high color purity which shows slight yellow-shift at elevated temperatures. The ground state of Pr3+ and Tb3+ are found to be within the band gap suggesting that both are able to trap holes from the valence band as evinced from the thermoluminescence glow curve data which shows peak maxima at 422 and 437 K due to hole release from the Pr4+ and Tb4+, respectively. The result suggests that the samples have large potential for solid state lighting devices upon choice of an appropriate excitation wavelength.

Non-quenching photoluminescence emission up to at least 865 K upon near-UV excitation in a single crystal of orange-red emitting SmPO4.

The adjustment of photoluminescence emission spectrum and an enhancement in the thermal stability of red/orange-red emitting phosphors is an important issue for the whole lighting industry. Herein, we present our results on the luminescence spectroscopy of a single crystal sample of SmPO4 exhibiting a prominent orange-red emission at 597 nm, along with a charge-transfer absorption (O2- → Sm3+) around 200 nm. We study the temperature dependence of emission spectra in SmPO4 for excitations at 365 and 455 nm, to mimic experimental conditions for phosphor converted light emitting diodes, to show that the sample has a non-quenching photoluminescence emission up to at least 865 K for an excitation at 365 nm, and ∼865 K for an excitation at wavelength, 455 nm. The thermal stability of SmPO4 was found to be much higher than its structural analogue, EuPO4, which is also an orange-red emission phosphor, but possesses a thermal quenching temperature of 710 K (exc. 365 nm), and 735 K (exc. 455 nm). The extraordinary thermal stability of SmPO4 is a result of the energy transfer from deep defects to the Sm3+ ions at high temperatures. The color purity of SmPO4 (65%) was found to be slightly lower than the EuPO4 sample (70%), at room temperature. The results suggests that the rare earth orthophosphate, SmPO4, has a large potential for near-UV excited phosphor converted solid state lighting devices.

Extending the temperature sensing range using Eu3+ luminescence up to 865 K in a single crystal of EuPO4.

Temperature evaluation through the measurement of emission intensities (the intensity ratio method) requires two distinct bands, one of which is used as a reference, and the emission intensity of the other is monitored as a function of a change in temperature. Herein, we report the influence of the excitation wavelength and a coupling scheme between the lanthanoid and defect emission from the host lattice to extend the temperature sensing range by using a single crystal of europium(iii) phosphate. The temperature dependence of the emission intensity was studied for different excitation wavelengths: 365 (intraconfigurational 4f2 excitation), 338 (defect excitation), and 254 nm (O2- → Eu3+ charge-transfer excitation), in the temperature range 293-865 K. We determined the Boltzmann equilibrium among different coupling schemes using a linear regression model to infer that for excitation at a 338 nm wavelength, and evaluating the intensity ratio between defect emission and the Eu3+ 5D0,17FJ transitions, the temperature sensing range can be extended up to at least 865 K, with relative sensitivity in the range 0.33-1.94% K-1 (at 750 K). The results showed a resolution of <1 K with excellent reproducibility, suggesting that the thermometers can be used with high reliability.

Multi-Sensor Spectral Imaging of Geological Samples: A Data Fusion Approach Using Spatio-Spectral Feature Extraction.

Rapid, efficient and reproducible drillcore logging is fundamental in mineral exploration. Drillcore mapping has evolved rapidly in the recent decade, especially with the advances in hyperspectral spectral imaging. A wide range of imaging sensors is now available, providing rapidly increasing spectral as well as spatial resolution and coverage. However, the fusion of data acquired with multiple sensors is challenging and usually not conducted operationally. We propose an innovative solution based on the recent developments made in machine learning to integrate such multi-sensor datasets. Image feature extraction using orthogonal total variation component analysis enables a strong reduction in dimensionality and memory size of each input dataset, while maintaining the majority of its spatial and spectral information. This is in particular advantageous for sensors with very high spatial and/or spectral resolution, which are otherwise difficult to jointly process due to their large data memory requirements during classification. The extracted features are not only bound to absorption features but recognize specific and relevant spatial or spectral patterns. We exemplify the workflow with data acquired with five commercially available hyperspectral sensors and a pair of RGB cameras. The robust and efficient spectral-spatial procedure is evaluated on a representative set of geological samples. We validate the process with independent and detailed mineralogical and spectral data. The suggested workflow provides a versatile solution for the integration of multi-source hyperspectral data in a diversity of geological applications. In this study, we show a straight-forward integration of visible/near-infrared (VNIR), short-wave infrared (SWIR) and long-wave infrared (LWIR) data for sensors with highly different spatial and spectral resolution that greatly improves drillcore mapping.

Fast 2D Laser-Induced Fluorescence Spectroscopy Mapping of Rare Earth Elements in Rock Samples.

Due to the rapidly increasing use of energy-efficient technologies, the need for complex materials containing rare earth elements (REEs) is steadily growing. The high demand for REEs requires the exploration of new mineral deposits of these valuable elements, as recovery by recycling is still very low. Easy-to-deploy sensor technologies featuring high sensitivity to REEs are required to overcome limitations by traditional techniques, such as X-ray fluorescence. We demonstrate the ability of laser-induced fluorescence (LIF) to detect REEs rapidly in relevant geological samples. We introduce two-dimensional LIF mapping to scan rock samples from two Namibian REE deposits and cross-validate the obtained results by employing mineral liberation analysis (MLA) and hyperspectral imaging (HSI). Technique-specific parameters, such as acquisition speed, spatial resolution, and detection limits, are discussed and compared to established analysis methods. We also focus on the attribution of REE occurrences to mineralogical features, which may be helpful for the further geological interpretation of a deposit. This study sets the basis for the development of a combined mapping sensor for HSI and 2D LIF measurements, which could be used for drill-core logging in REE exploration, as well as in recovery plants.

Feldspar flotation as a quartz-purification method in cosmogenic nuclide dating: A case study of fluvial sediments from the Pamir.

Cosmogenic nuclide (CN) dating relies on specific target minerals such as quartz as markers to identify geologic events, including the timing of landscape evolution. The presence of feldspar in sediment samples poses a challenge to the separation of quartz and affects the chemical procedures for extracting the radioactive CNs 10Be and 26Al. Additionally, feldspar contamination reduces the 26Al/27Al ratio, thus hinders the accurate determination of 26Al by accelerator mass spectrometry (AMS). Using fluvial sediment samples from Central Asia, which contain 16-50 weight percent (wt.%) of feldspar, we show that the standard physical separation and chemical cleaning-up procedures for quartz-enrichment reduces the feldspar content to only 9-47 wt.%. We present a new froth flotation mineral-separation device and procedure that allows for very effective quartz enrichment before CN chemistry. Our flotation cell, which has a volume of 600 cm3, is built of borosilicate glass, holds up to 90 g of sample, and achieves quartz and feldspar separation in ≤2 h for very feldspar-rich samples. We trace the stepwise enrichment of quartz to 95-100% purity with our procedure by X-ray diffraction analysis.