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In Deutschland werden jährlich rund 20 Millionen Tonnen künstliche Mineralwolle für die Dämmung von Dächern und Fassaden sowie für Brandschutzprodukte verwendet. Um künstliche Mineralwolle aus Rückbaumaßnahmen in den Produktionsprozess zurückführen zu können, ist eine Trennung in Glas- und Steinwolle erforderlich, um eine Vermischung der beiden Produkte, die unterschiedliche Schmelztemperaturen aufweisen, zu vermeiden. Anstatt die Mineralwolle in spezielle Labors zu schicken, was zeitaufwendig und teuer ist, wurde das Potenzial eines tragbaren Nahinfrarot-Spektrometers (NIR) für den Einsatz vor Ort getestet. 140 verschiedene Mineralwolleproben wurden untersucht, um eine NIR-basierte Methode für die Vor-Ort-Unterscheidung zwischen Glas- und Steinwolle zu etablieren. Die Validierung der Methode mit Testproben und die Anwendung auf Materialien, die aus BigBags für Deponien entnommen wurden, haben gezeigt, dass die Methode präzise und robust ist. Als Referenzmethode wurde die Röntgenfluoreszenzspektroskopie (RFA) mit einer Kalibrierung auf der Grundlage der VDI 3492 verwendet.
Around 2.5 million tons of municipal sewage sludge (dry matter) are produced in Ger-many every year. The disposal or recycling of this mass often confronts plant operators with considerable problems. In addition to organic substances, sewage sludges also contain important inorganic nutrients that can be recycled. Due to the finite nature of phosphorus as a resource and in favor of natural material cycles, it makes sense to utilize the phosphorus bound in sewage sludge. Therefore, Phosphorus recycling from sewage sludge will be obligatory in Germany from 2029. However, the pollutants pre-sent in sewage sludge, such as heavy metals and organic trace pollutants, are prob-lematic. In many cases, the sewage sludge is incinerated, removing organic compo-nents, and leaving a mineral residue. Various processes exist for the reprocessing of sewage sludge ashes. Reliable analytics and process monitoring are required for all of them.
In this context, the first and most important task of BAM regarding new materials or processes is safety in technology and chemistry through validated and correct analyt-ics. Since there are no reference materials for sewage sludge ashes so far, it is not possible to make any statements about the extent to which the measured values of the comparative measuring methods are correct at all. Therefore, suitable, and representa-tive reference materials are indispensable for the validation of the measurement results and the quality assurance during the entire recycling process. Great care is required to select and prepare these reference materials. The reference materials must corre-spond in matrix to the samples that are to be investigated in the industrial process. An iron-rich and an aluminum-rich sewage sludge ash from mono-incineration plants were selected for this purpose. 10 kg of each sewage sludge ash were homogenized, char-acterized, and prepared. The main, minor and trace element compositions of the sew-age sludge ashes are determined by different measuring methods. The candidate ref-erence materials will be available as BAM-U200 und BAM-U201.
The leaching behavior of scandium (Sc) from bauxite residues can differ significantly when residues of different geological backgrounds are compared. The mineralogy of the source rock and the physicochemical environment during bauxitization affect the association of Sc in the bauxite i.e., how Sc is distributed amongst different mineral phases and whether it is incorporated in and/or adsorbed onto those phases. The Sc association in the bauxite is in turn crucial for the resulting Sc association in the bauxite residue. In this study systematic leaching experiments were performed on three different bauxite residues using a statistical design of experiments approach. The three bauxite residues compared originated from processing of lateritic and karstic bauxites from
Germany, Hungary, and Russia. The recovery of Sc and Fe was determined by ICP-OES measurements. Mineralogical changes were analyzed by X-ray-diffraction and subsequent Rietveld refinement. The effects of various parameters including temperature, acid type, acid concentration, liquid-to-solid ratio and residence time were studied. A response surface model was calculated for the selected case of citric acid leaching of Hungarian bauxite residue. The investigations showed that the type of bauxite residue has a strong influence. The easily leachable fraction of Sc can vary considerably between the types, reaching ~20–25% in German Bauxite residue and ~50% in Russian bauxite residue. Mineralogical investigations revealed that a major part of this fraction was released from secondary phases such as cancrinite and katoite formed during Bayer processing of the bauxite.
The effect of temperature on Sc and Fe recovery is strong especially when citric acid is used. Based on the exponential relationship between temperature and Fe-recovery it was found to be particularly important for the selectivity of Sc over Fe. Optimization of the model for a maximum Sc recovery combined with a minimum Fe
recovery yielded results of ~28% Sc recovery at <2% Fe recovery at a temperature of 60 ◦C, a citric acid normality of 1.8, and a liquid-to-solid ratio of 16 ml/g. Our study has shown that detailed knowledge about the Sc association and distribution in bauxite and bauxite residue is key to an efficient and selective leaching of Sc
from bauxite residues.
Rückgebaute Mineralwolledämmstoffe und Baustellenverschnitte werden in der Regel deponiert und damit als Rohstoffe dem Markt entzogen. Ziel dieses Projektes ist es darzulegen, dass das Recycling von Glas- und Steinwolle im großmaßstäblich volumenrelevanten Umfang für das Schmelzwannenverfahren technisch umsetzbar und ökonomisch und ökologisch vorteilhaft ist. Neben verfahrenstechnischen Herausforderungen, gilt es die wirtschaftliche in-situ-Identifikation unbekannter Mineralwolle zu ermöglichen. Dazu wird auf erste erfolgversprechende Tastversuche mit spektroskopischen Methoden weiter aufgebaut.
The project “Intelligence for Soil” (I4S) aims at the design of an integrated system for improvement of soil functions and fertilizer recommendations. This system is composed by different sensors that will provide a detailed assessment of soil properties and processes, which are prerequisites for a site-specific, resource-saving and ecofriendly soil management, considering the soil as a sustainable resource for the bioeconomy. One of these sensors will be an energy-dispersive X-Ray Fluorescence spectrometer. It is a non-destructive technique suitable for in-situ measurements due to a minimum sample preparation and it allows fast multielement analyses. In this work, an automatic system has been developed using a handheld equipment from Olympus (Vanta C series). A polypropylene (PP) film was used to protect the measuring window of the device from dust and possible cross-contamination. To control the stepper motor that unrolls the PP film, a microcontroller was used to ensure that a piece of clean PP is in front of the measuring window for each new analysis.
Preliminary calibration studies using pre-defined methods, Geochem and Soil Methods, were performed with the following Certified Reference Materials (CRMs): NRC Till 1-3, NIST 2710, BAM U110, ERM CC141, BCR 142R, IAEA Soil 7. The CRMs were measured 10 times at different spots. The spot size was 10 mm in diameter, irradiation time was 60 ? s. The averaged data from X ray characteristic emission line intensities for Al, P, Si, Ca, Fe, Mn, Zn, Cu and Ni Kα were in close agreement with certified mass fraction data. The linear correlation coefficients (r) ranged from 0.852 for P to 0.999 for Mn. A second round of calibration studies were performed with the following CRMs: GBW07402, GBW 07405, NCS DC 73023, NCS DC 73030, NCS DC 85109, NCS DC 87104, NIST 1646a, NIST 2704, NIST 2710, NRC Till 1-3, VS 2498-83, and the same pre-defined methods and experimental parameters were employed. The results of the 13 CRMs were now compared with the values obtained by a validated WDXRF method. The linear correlation coefficients (r) ranged from 0.998 for Ca to 0.999 for Zn. Other elements such as S, K and Ti can also be properly determined, but validation still requires more robust calibration models.
Further calibration studies will be performed in order to circumvent matrix effects and to guarantee reliable results. Besides that, the automatic system will be placed on a mobile sensor platform and the system will be tested in the field. A guidance for on site-specific fertilization integrating the results obtained from different sensors placed on the platform is expected.
Gegenstand dieser Arbeit ist die Untersuchung eines bestehenden pyrometallurgischen Prozesses zur Rückgewinnung von Tantal und Niob aus metallurgischen Reststoffen mit vorwiegend niedriger Wertstoffkonzentration.
Zur näheren Erforschung der im vorliegenden Stoffsystem ablaufenden Reduktionsprozesse wurden in einem Elektrolichtbogenofen Schmelzversuche im Pilotmaßstab durchgeführt. Als Reduktionsmittel diente Koks, welcher mithilfe einer Argon-gespülten Eisenlanze in die flüssige mineralische Schmelze eingebracht wurde. Während der Reduktionsbehandlung werden Refraktärmetalle wie Tantal und Niob in ihre Carbide überführt und anschließend in der erschmolzenen eisenbasierten Metallphase am Boden des Reaktors angereichert. Neben Tantal und Niob gelangt auch ein Teil des im Einsatzmaterial enthaltenen Titans als unerwünschtes Begleitelement in die Metallphase.
Sein Großteil verbleibt jedoch als Oxid in der Schlacke und wird dort hauptsächlich im Mineral Perowskit (CaTiO3) gebunden. Die erstarrten Schlackeproben wurden mit verschiedenen Methoden wie Röntgenfluoreszensanalyse, Röntgenbeugung und Rasterelektronenmikroskopie mit gekoppelter energiedispersiver Röntgenanalyse untersucht, um die Bildung tantalhaltiger Mineralphasen zu verschiedenen Stadien des Reduktionsprozesses zu verfolgen.
Die hier gewonnenen Erkenntnisse zeigen, dass weniger die durch das Einblasen von Koks verursachte Reduktionsreaktion, sondern das Absinken der tantalreichen Eisentröpfchen in der flüssigen mineralischen Schmelze, gefolgt von ihrer Anreicherung in die Metallphase, für die Kinetik ausschlaggebend ist.
Die vom BMBF unterstütze Forschungsinitiative BonaRes entwickelt Strategien um Boden als nachhaltige Ressource für die Bioökonomie zu nutzen. Das Projekt Intelligence for Soil (I4S) ist ein Teil dieser Initiative und beschäftigt sich mit der Entwicklung eines integrierten Systems zur ortsspezifischen Düngung. Ein Ziel dieses Projektes ist die Etablierung einer mobilen Sensorplattform zur Bodenkartierung. Aufgabe der BAM ist dabei das Installieren und die Optimierung eines RFA Sensors für die online Messung direkt auf dem Feld. Die RFA ist eine zerstörungsfreie Technik, die kaum Probenvorbereitung benötigt und einen schnelle Multielement Analyse ermöglicht. Das schnelle Kartieren des Bodens ermöglicht später eine ortsspezifische Düngung mit Nährstoffen wie z.B. K, Ca und P.
Die vom BMBF unterstütze Forschungsinitiative BonaRes entwickelt Strategien um Boden als nachhaltige Ressource für die Bioökonomie zu nutzen. Das Projekt Intelligence for Soil (I4S) ist ein Teil dieser Initiative und beschäftigt sich mit der Entwicklung eines integrierten Systems zur ortsspezifischen Düngung. Ein Ziel dieses Projektes ist die Etablierung einer mobilen Sensorplattform zur Bodenkartierung. Aufgabe der BAM ist dabei das Installieren und die Optimierung eines RFA Sensors für die online Messung direkt auf dem Feld. Die RFA ist eine zerstörungsfreie Technik, die kaum Probenvorbereitung benötigt und einen schnelle Multielement Analyse ermöglicht. Das schnelle Kartieren des Bodens ermöglicht später eine ortsspezifische Düngung mit Nährstoffen wie z.B. K, Ca und P.
Within the framework of precision agriculture, the determination of various soil properties is moving into focus, especially the demand for sensors suitable for in-situ measurements. Energy-dispersive X-ray fluorescence (EDXRF) can be a powerful tool for this purpose. In this study a huge diverse soil set (n = 598) from 12 different study sites in Germany was analysed with EDXRF. First, a principal component analysis (PCA) was performed to identify possible similarities among the sample set.
Clustering was observed within the four texture classes clay, loam, silt and sand, as clay samples contain high and sandy soils low iron mass fractions. Furthermore, the potential of uni- and multivariate data evaluation with partial least squares regression (PLSR) was assessed for accurate Determination of nutrients in German agricultural samples using two calibration sample sets. Potassium and iron were chosen for testing the performance of both models. Prediction of these nutrients in 598 German soil samples with EDXRF was more accurate using PLSR which is confirmed by a better overall averaged deviation and PLSR should therefore be preferred.
As part of the BonaRes research initiative, funded by the BMBF, strategies are being developed to use soil as a sustainable resource in the bio economy. The interdisciplinary subproject I4S - “Intelligence for soil” - is responsible for the development of an integrated system for site-specific management of soil fertility. For this purpose, a platform is constructed and various sensors are installed. Real-time data will be summarised in models and decision-making algorithms will be used to control fertilisation and accordingly improve soil functions. Aim of the BAM in the frame of I4S is the characterisation of an energy-dispersive X-ray fluorescence (EDXRF) based sensor for robust determination of plant essential nutrients in soil.
First a principal component analysis (PCA) was used to identify outliers and to observe the largest variance within the German soil samples. It could be monitored that splitting of the samples was due to their iron content. Given that clay samples contain high amounts of iron and sandy samples low amounts, a classification of the samples by their soil texture according to VD LUFA was possible. Considering the complex composition of soil, a matrix-specific calibration was carried out by univariate and multivariate data analysis. The figures of merit demonstrated that a more robust calibration model with negligible matrix effects can be obtained by a multivariate approach using partial least squares regression (PLSR). A better correlation between predicted values compared to reference values for German soil samples was observed for the chemometric calibration model than for the univariate one.
Different factors can affect the received calibration models such as moisture and particle size distribution which is especially important due to later online analysis.
In first studies the influence of moisture on the detection of plant essential nutrients was investigated. With increasing water content, the characteristic fluorescence peaks decrease and start to increase again at a water content of 15 %. With lower moisture content the soil agglomerates which leads to lower packing of the sample, resulting in a rougher surface which negatively influence the signals. Whereas, agglomerates are not formed at higher water content. This allows the sample to be packed more tightly thus a smoother surface and a better homogeneity is obtained.
Furthermore, particle size distribution leads to significantly higher uncertainties and lower signals when comparing grounded (< 500 μm) and not grounded (< 2 mm) samples. This can be explained by amplifying of the already known inhomogeneity of soils.
Both factors must be included in the chemometric PLSR to obtain robust calibration models for each macro and micro nutrient.