TY - CONF A1 - Broszies, T. A1 - Zänker, Steffen A1 - Schaudienst, F. A1 - Paul, Andrea A1 - Vogdt, F. U. T1 - Remelting Miwo - Recycling von Mineralwolldämmstoffen, die im Schmelzwannenverfahren hergestellt werden N2 - 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. T2 - 18. Projektetage der Bauforschung CY - Online meeting DA - 09.11.2021 KW - Mineralwolle KW - Circular Economy KW - NIR KW - RFA PY - 2021 UR - https://www.zukunftbau.de/veranstaltungen/projektetage-der-bauforschung/rueckblicke#c8553 AN - OPUS4-53982 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Gentzmann, Marie A1 - Paul, Andrea A1 - Serrano, Juan A1 - Adam, Christian T1 - Understanding scandium leaching from bauxite residues of different geological backgrounds using statistical design of experiments N2 - 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. KW - Bauxite residue KW - Scandium KW - Leaching KW - Design of experiments KW - Red mud PY - 2022 U6 - https://doi.org/10.1016/j.gexplo.2022.107041 SN - 0375-6742 VL - 2022 IS - 240 SP - 1 EP - 13 PB - Elsevier Science CY - Amsterdam AN - OPUS4-55531 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Rühlmann, Madlen A1 - Büchele, Dominique A1 - Ostermann, Markus A1 - Bald, Ilko A1 - Schmid, Thomas T1 - Challenges in the quantification of nutrients in soils using laser-induced breakdown spectroscopy – A case study with calcium N2 - The quantification of the elemental content in soils with laser-induced breakdown spectroscopy (LIBS) is challenging because of matrix effects strongly influencing the plasma formation and LIBS signal. Furthermore, soil heterogeneity at the micrometre scale can affect the accuracy of analytical results. In this paper, the impact of univariate and multivariate data evaluation approaches on the quantification of nutrients in soil is discussed. Exemplarily, results for calcium are shown, which reflect trends also observed for other elements like magnesium, silicon and iron. For the calibration models, 16 certified reference soils were used. With univariate and multivariate approaches, the calcium mass fractions in 60 soils from different testing grounds in Germany were calculated. The latter approach consisted of a principal component analysis (PCA) of adequately pre-treated data for classification and identification of outliers, followed by partial least squares regression (PLSR) for quantification. For validation, the soils were also characterised with inductively coupled plasma optical emission spectroscopy (ICP OES) and X-ray fluorescence (XRF) analysis. Deviations between the LIBS quantification results and the reference analytical results are discussed. KW - Laser-induced breakdown spectroscopy (LIBS) KW - Soil KW - Multivariate data analysis KW - Principal component analysis (PCA) KW - Partial least squares regression (PLSR) PY - 2018 U6 - https://doi.org/10.1016/j.sab.2018.05.003 VL - 146 SP - 115 EP - 121 PB - Elsevier B.V. AN - OPUS4-45070 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Büchele, Dominique A1 - Chao, Madlen A1 - Ostermann, Markus T1 - Development of a robust calibration model for determination of nutrients in soils using EDXRF N2 - 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. T2 - AK Prozessanalytik CY - Hannover, Germany DA - 03.12.2018 KW - EDXRF KW - Soil KW - Chemometrics PY - 2018 AN - OPUS4-48280 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Büchele, Dominique A1 - Chao, Madlen A1 - Ostermann, Markus T1 - Influence of moisture and grain sizes on the determination of nutriens in german agricultural soils using EDXRF N2 - 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. T2 - BonaRes Statusseminar CY - Leipzig, Germany DA - 19.02.2019 KW - XRF KW - Mmoisture KW - Chemometrics PY - 2019 AN - OPUS4-48281 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Büchele, Dominique A1 - Chao, Madlen A1 - Ostermann, Markus A1 - Bald, Ilko T1 - Herausforderungen bei der robusten online-Bestimmung von Nährstoffen in Böden mittels eines Röntgenfluoreszenzsensors N2 - 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 Online-determination of macro and minor 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). 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 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 and not grounded samples. Both factors must be included in the chemometric PLSR to obtain robust calibration models for each nutrient. N2 - Im Rahmen der vom BMBF geförderten Forschungsinitiative BonaRes werden Strategien entwickelt, um Boden als nachhaltige Ressource in der Bioökonomie zu nutzen. Das interdisziplinäre Teilprojekt I4S - „Intelligenz für den Boden“ - ist verantwortlich für die Entwicklung eines integrierten Systems zur standortspezifischen Steuerung der Bodenfruchtbarkeit. Zu diesem Zweck wird eine Plattform gebaut, auf der verschiedene Sensoren installiert sind. Echtzeitdaten werden in Modellen zusammengefasst und Entscheidungsalgorithmen werden verwendet, um die Düngung zu steuern und die Bodenfunktionen entsprechend zu verbessern. Ziel der BAM im Rahmen von I4S ist die Charakterisierung eines energiedispersiven Röntgenfluoreszenzsensors (EDXRF) zur robusten online-Bestimmung von Makro- und Mikronährstoffen im Boden. Zunächst wurde eine Hauptkomponentenanalyse (PCA) durchgeführt, um Ausreißer zu identifizieren und die größte Varianz innerhalb der deutschen Bodenproben zu beobachten. Es konnte festgestellt werden, dass die Aufspaltung der Proben auf ihren Eisengehalt zurückzuführen ist. Da Tonproben hohe Mengen an Eisen und Sandproben geringe Mengen enthalten, war eine Klassifizierung der Proben nach ihrer Bodentextur nach VD LUFA möglich. In Anbetracht der komplexen Bodenzusammensetzung wurde eine matrixspezifische Kalibrierung durch univariate und multivariate Datenanalyse durchgeführt. Die analytischen Güteziffern zeigen, dass ein robusteres Kalibriermodell mit vernachlässigbaren Matrixeffekten durch einen multivariaten Ansatz unter Verwendung der partiellen Regression kleinster Quadrate (PLSR) erhalten werden kann. Verschiedene Faktoren können die erhaltenen Kalibriermodelle beeinflussen, wie z. B. Feuchtigkeit und Partikelgrößenverteilung, was aufgrund der späteren online-Analyse besonders wichtig ist. In ersten Studien wurde der Einfluss von Feuchtigkeit auf den Nährstoffnachweis untersucht. Mit zunehmendem Wassergehalt nehmen die charakteristischen Fluoreszenzpeaks ab und beginnen bei einem Wassergehalt von 15% wieder anzusteigen. Bei geringerem Feuchtigkeitsgehalt agglomeriert der Boden, was zu einer geringeren Packung der Probe führt, dementsprechend zu einer raueren Oberfläche, die die Signale negativ beeinflusst. Bei höherem Wassergehalt bilden sich keine Agglomerate. Dadurch kann die Probe enger gepackt werden, wodurch eine glattere Oberfläche und eine bessere Homogenität erhalten wird. Darüber hinaus führt die Partikelgrößenverteilung beim Vergleich von gemahlenen und nicht gemahlenen Proben zu signifikant höheren Unsicherheiten und niedrigeren Signalen. Beide Faktoren müssen in die chemometrische PLSR einbezogen werden, um zuverlässige Kalibrierungsmodelle für jeden Nährstoff zu erhalten. T2 - AK Prozessanalytik - Doktorandenseminar CY - Berlin, Germany DA - 18.03.2019 KW - Boden KW - RFA KW - PLSR PY - 2019 AN - OPUS4-48283 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Taube, Mareike Carolin A1 - Adamczyk, Burkart A1 - Adam, Christian A1 - Feldmann, Ines A1 - Ostermann, Markus A1 - Reuter, M. A1 - Stelter, M. T1 - Tantalrecycling aus pyrometallurgischen Rückständen N2 - 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. N2 - An existing pyrometallurgical process for tantalum and niobium recovery, mainly from low grade pyrometallurgical residues, was investigated. Melting experiments were carried out in a pilot-scale electric arc furnace to study the material system during the reduction process caused by blowing coke into the liquid mineral melt. During the pyrometallurgical treatment refractory metals such as tantalum and niobium are converted into their carbides and enriched in the molten iron-based metal phase. Titanium is also enriched in the metal phase as an unwanted accompanying element, but most of it remains in oxidic form in the slag and is mainly bound in the mineral perovskite. Cooled down slag samples were analysed using XRF, XRD, SEM and EDX to investigate the formation of mineral phases rich in tantalum during various stages of the reduction process. The results show that the settling of the tantalum-rich iron droplets in the molten slag into the metal phase May play a greater role for the kinetics than the actual reduction reaction caused by blowing in coke. KW - Tantal KW - Recycling KW - Reduktionsprozess KW - Perowskit KW - Elektrolichtbogenofen PY - 2020 SN - 1613-2394 VL - 73 IS - 4 SP - 196 EP - 205 PB - GDMB Verlag GmbH CY - Clausthal-Zellerfeld AN - OPUS4-51064 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Adame, Andressa A1 - Ostermann, Markus T1 - Development of an automatic system for in situ analysis of soil using a handheld Energy Dispersive X-Ray Fluorescence (EDXRF) N2 - 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. T2 - 16. Kolloquium Prozessanalytik CY - Online Meeting DA - 23.11.2020 KW - Röntgenfluoreszenz KW - Boden KW - XRF KW - Soil PY - 2020 AN - OPUS4-51776 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Büchele, Dominique A1 - Chao, Madlen A1 - Ostermann, Markus A1 - Leenen, M. A1 - Bald, Ilko T1 - Multivariate chemometrics as a key tool for prediction of K and Fe in a diverse German agricultural soil-set using EDXRF N2 - 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. KW - XRF KW - Chemometrics KW - Soil KW - Agriculture KW - Multivariate PY - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-498671 VL - 9 SP - 17588 PB - Nature AN - OPUS4-49867 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichhorn, Maria A1 - Eggers, Romina A1 - Ostermann, Markus T1 - Entwicklung einer Online RFA Methode zur Bestimmung von Nährstoffen im Boden N2 - 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. T2 - 15. Herbstkolloquium Arbeitskreis Prozessanalytik CY - Marl, Germany DA - 25.11.2019 KW - RFA KW - Boden KW - Nährstoffe KW - Online PY - 2019 AN - OPUS4-49871 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -