Analytische Chemie
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Organisationseinheit der BAM
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- 4 Material und Umwelt (2)
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- 8.1 Sensorik, mess- und prüftechnische Verfahren (2)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (2)
- 1.1 Anorganische Spurenanalytik (1)
- 1.6 Anorganische Referenzmaterialien (1)
- 4.1 Biologische Materialschädigung und Referenzorganismen (1)
- 4.3 Schadstofftransfer und Umwelttechnologien (1)
- 4.5 Kunst- und Kulturgutanalyse (1)
- 5 Werkstofftechnik (1)
- 5.1 Mikrostruktur Design und Degradation (1)
- 6.6 Physik und chemische Analytik der Polymere (1)
- 8.3 Thermografische Verfahren (1)
- 8.4 Akustische und elektromagnetische Verfahren (1)
- 9 Komponentensicherheit (1)
- 9.0 Abteilungsleitung und andere (1)
The contamination of drinking water with pharmaceuticals represents a severe health risk. In order to monitor the drinking water quality continuously and enable quick countermeasures in case of contamination, novel sensors are required. Here, immunoanalytical methods based on the binding of the analyte to highly selective antibodies can be helpful. In this work, magnetic bead-based immunoassays (MBBAs) have been developed for the detection of two relevant contaminants of drinking water: diclofenac (DCF) and amoxicillin (AMX). In case of the latter, not only the parent drug is of interest in the risk assessment but also its hydrolysis products (HPs). In a comprehensive study, the influence of external factors and intrinsic properties of the water on the rate of hydrolysis was investigated. As the hydrolysis of AMX further impacts the recognition by the antibody, a strategy to analyze samples with unknown hydrolysis degree of AMX was established employing the enzyme β-lactamase in sample preparation. For both analytes, the MBBAs enable the fast quantification with results obtained in less than one hour which represents a major improvement over conventional immunoassays like the enzyme-linked immunosorbent assay (ELISA). Compared to the respective ELISAs with the same antibodies, the MBBAs further exhibit improved analytical parameters such as a broader measurement range and lower limits of detection. Due to the magnetic properties of the beads that serve as a platform for the assays, they are suitable for the mobile and automated detection at the point-of-care. An integrated diagnostic system was designed in which electrochemical detection with chronoamperometry on a microfluidic chip allows for further miniaturization of the system to enable monitoring of the drinking water quality online in water supply pipes at waterworks.
Development of electrochemical antibody-based and enzymatic assays for mycotoxin analysis in food
(2023)
Electrochemical methods are promising to meet the demand for easy-to-use devices monitoring key parameters in the food industry. Many companies run own lab procedures for mycotoxin analysis, but it is a major goal to simplify the analysis. The enzyme-linked immunosorbent assay using horseradish peroxidase as enzymatic label, together with 3,3',5,5' tetramethylbenzidine (TMB)/H2O2 as substrates allows sensitive mycotoxin detection with optical detection methods. For the miniaturization of the detection step, an electrochemical system for mycotoxin analysis was developed. To this end, the electrochemical detection of TMB was studied by cyclic voltammetry on different screen-printed electrodes (carbon and gold) and at different pH values (pH 1 and pH 4). A stable electrode reaction, which is the basis for the further construction of the electrochemical detection system, could be achieved at pH 1 on gold electrodes. An amperometric detection method for oxidized TMB, using a custom-made flow cell for screen-printed electrodes, was established and applied for a competitive magnetic bead-based immunoassay for the mycotoxin ochratoxin A. A limit of detection of 150 pM (60 ng/L) could be obtained and the results were verified with optical detection. The applicability of the magnetic bead-based immunoassay was tested in spiked beer using a handheld potentiostat connected via Bluetooth to a smartphone for amperometric detection allowing to quantify ochratoxin A down to 1.2 nM (0.5 µg/L). Based on the developed electrochemical detection system for TMB, the applicability of the approach was demonstrated with a magnetic bead-based immunoassay for the ergot alkaloid, ergometrine. Under optimized assay conditions a limit of detection of 3 nM (1 µg/L) was achieved and in spiked rye flour samples ergometrine levels in a range from 25 to 250 µg/kg could be quantified. All results were verified with optical detection. The developed electrochemical detection method for TMB gives great promise for the detection of TMB in many other HRP-based assays. A new sensing approach, based on an enzymatic electrochemical detection system for the mycotoxin fumonisin B1 was established using an Aspergillus niger fumonisin amine oxidase (AnFAO). AnFAO was produced recombinantly in E. coli as maltose-binding protein fusion protein and catalyzes the oxidative deamination of fumonisins, producing hydrogen peroxide. It was found that AnFAO has a high storage and temperature stability. The enzyme was coupled covalently to magnetic particles, and the enzymatically produced H2O2 in the reaction with fumonisin B1 was detected amperometrically in a flow injection system using Prussian blue/carbon electrodes and the custom-made wall-jet flow cell. Fumonisin B1 could be quantified down to 1.5 µM (≈ 1 mg/L). The developed system represents a new approach to detect mycotoxins using enzymes and electrochemical methods.
Concrete is the most important human-made material because it serves as the basis of our built environment. Since the properties of concretes are dominated by their key compound, cement, devising a way to determine the cement’s origin, known as provenancing, is of great importance for answering different provenance-related questions. These questions range from liability issues when damage occurs to concrete-made structures, to forensic investigations where cement particles are found at crime scenes. This thesis showcases the use of isotope techniques to answer these provenance-related questions. Conventional 87Sr/86Sr and 143Nd/144Nd isotope and elemental ratios consisting of Ca, Sr, K, Mn, Mg, and Ti are used as fingerprints for ordinary Portland cement (OPC) provenancing. The first part of this thesis describes research previously conducted in fingerprinting cementitious materials, providing an overview of provenance studies of cement and the main approaches commonly used. In several studies, the origin of clinker for certain locations was determined via different approaches. However, clinker is an intermediate product, which is available only at the production site and therefore, the practical relevance is rather limited. Furthermore, the use of Sr and Nd isotope systems, together with elemental fingerprints are presented as state of the art in the field. Therein, the principal approach for the overall study is sketched. For the second part of the study, a sample preparation technique for Sr isotopes in Portland cement was developed. The aim was to find the most appropriate sample preparation procedure for cement provenancing and selection was realised by comparing the 87Sr/86Sr isotope ratios of differently treated OPCs with those of the corresponding clinkers. Based on these findings, the third part of the study focused on the measurements of Sr and Nd isotope ratios, together with elemental ratios, to establish a reliable technique for OPC provenancing. The outcomes of this final stage are then used to establish a procedure for fingerprinting cements. This becomes possible with the use of Sr and Nd isotope ratios and geochemical profiles. To perform isotope ratio measurements and obtain reliable data, it was necessary to establish a quality control procedure. Thus, an interlaboratory comparison (ILC) was organised to characterise 87Sr/86Sr isotope ratios in geological and industrial reference materials by applying the conventional method for 87Sr/86Sr isotope ratios. As reference material, four cements (VDZ 100a, VDZ 200a, VDZ 300a, IAG OPC-1), one limestone (IAG/CGL ML-3) and one slate (IAG OU-6) were selected, thus covering a wide range of Sr isotope signatures.
In the event of moisture deterioration, rapid detection and localization is particularly important to prevent further deterioration and costs. For building floors, the layered structure poses a challenging obstacle for most moisture measurement methods. But especially here, layer-specific information on the depth of the water is crucial for efficient and effective repairs. Ground Penetrating Radar (GPR) shows the potential to generate such depth information. Therefore, the present work investigates the suitability of GPR in combination with machine learning methods for the automated classification of the typical deterioration cases (i) dry, (ii) wet insulation, and (iii) wet screed.
First, a literature review was conducted to identify the most common methods for detecting moisture in building materials using GPR. Here, it especially became clear that all publications only investigated individual time-, amplitude- or frequency features separately, without combining them. This was seen as a potential aspect for innovation, as the multivariate application of several signal features can help to overcome individual weaknesses and limitations.
Preliminary investigations carried out on drying screed samples confirmed the profitable use of multivariate evaluations. In addition to the general suitability and dependencies of various features, first limitations due to possible interference between the direct wave and the reflection wave could be identified. This is particularly evident with thin or dry materials, for which the two-way travel times of the reflected radar signals become shorter.
An extensive laboratory experiment was carried out, for which a modular test specimen was designed to enable the variation of the material type and thickness of screed and insulation, as well as the simulation of moisture deteriorations. The data collected revealed clear differences between dry and deteriored structures within measured B-scans. These deviations were to be detected with the newly introduced B-scan features, which evaluate the statistical deviation of A-scan features within a survey line. In this way, deteriorations to unknown floor structures are recognized, regardless of the material parameters present. In a subsequent training and cross-validation process of different classifiers, accuracies of over 88 \% of the 504 recorded measurements (252 different experimental setups) were achieved. For that, the combination of amplitude and frequency features, which covered all relevant reflections of the radar signals, was particularly beneficial. Furthermore, the data set showed only small differences between dry floors and deteriored screeds for the B-scan features, which could be attributed to a homogeneous distribution of the added water in the screeds. The successfully separation of these similar feature distributions raised the suspicion of overfitting, which was examined in more detail by means of a validation with on-site data.
For this purpose, investigations were carried out at five different locations in Germany, using the identical measurement method like in the laboratory. By extracting drilling cores, it was possible to determine the deterioration case for each measurement point and thus generate a corresponding reference. However, numerous data had to be sorted out before classification, since disturbances due to underfloor heating, screed reinforcements, steel beams or missing insulation prevented comparability with the laboratory experiments. Validation of the remaining data (72 B-scans) achieved only low accuracy with 53 \% correctly classified deterioration cases. Here, the previously suspected overfitting of the small decision boundary between dry setups and deteriored screeds within the laboratory proved to be a problem. The generally larger deviations within (also dry) on-site B-scans were thus frequently misclassified as screed deterioration. In addition, there were sometimes strongly varying layer thicknesses or changing cases of deterioration within a survey line, which caused additional errors due to the local limitation of the drilling core reference. Nevertheless, individual on-site examples also showed the promising potential of the applied signal features and the GPR method in general, which partly allowed a profound interpretation of the measurements. However, this interpretation still requires the experience of trained personnel and could not be automated using machine learning with the available database. Nevertheless, such experience and knowledge can be enriched by the findings of this work, which provide the basis for further research.
Future work should aim at building an open GPR data base of on-site moisture measurements on floors to provide a meaningful basis for applying machine learning. Here, referencing is a crucial point, whose limitations with respect to the moisture present and its distribution can easily reduce the potential of such efforts. The combination of several reference methods might help to overcome such limitations. Similarly, a focus on monitoring approaches can also help to reduce numerous unknown variables in moisture measurements and increase confidence in the detection of different deterioration cases.
Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction.
Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of two-dimensionalROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL).
In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel
patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x).
Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free two-dimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods.
This thesis investigates ultrasonic guided waves (GW) in multi-layered plates with the focus on higher order modes. The aim is to develop techniques for hybrid structures such as of adhesive bonds and composite pressure vessels (COPV) which are widely used in automotive and aerospace industries and are still challenging to inspect non-destructively. To be able to analyse GW, numerical methods and precise material properties are required. For this purpose, an efficient semi-analytical approach, the Scaled Boundary Finite Element Method, is used. The material properties are inferred by a GW-based optimisation procedure and a sensitivity study is performed to demonstrate the influence of properties on GW. Then, an interesting feature, called mode repulsion, is investigated with respect to weak and strong adhesive bonds. The results show that the coupling between two layers influences the distance between coupled modes in a mode repulsion region, thus allowing for the characterisation of adhesive bonds. At next, wave-damage interaction is studied in the hybrid structure as of the COPV. Results show that the wave energy can be concentrated in a certain layer enabling damage localisation within different layers. Further investigations are carried out on the hybrid plate with an impact-induced damage. Two well-known wavenumber mapping techniques, which allow to quantify the damage in three dimensions, are implemented and their comparison is done for the first time.
In X-ray computed tomography (XCT), an X-ray beam of intensity I0 is transmitted through an object and its attenuated intensity I is measured when it exits the object. The attenuation of the beam depends on the attenuation coefficients along its path. The attenuation coefficients provide information about the structure and composition of the object and can be determined through mathematical operations that are referred to as reconstruction. The standard reconstruction algorithms are based on the filtered backprojection (FBP) of the measured data. While these algorithms are fast and relatively simple, they do not always succeed in computing a precise reconstruction, especially from under-sampled data. Alternatively, an image or volume can be reconstructed by solving a system of linear equations. Typically, the system of equations is too large to be solved but its solution can be approximated by iterative methods, such as the Simultaneous Iterative Reconstruction Technique (SIRT) and the Conjugate Gradient Least Squares (CGLS). This dissertation focuses on the development of a novel iterative algorithm, the Direct Iterative Reconstruction of Computed Tomography Trajectories (DIRECTT). After its reconstruction principle is explained, its performance is assessed for real parallel- and cone-beam CT (including under-sampled) data and compared to that of other established algorithms. Finally, it is demonstrated how the shape of the measured object can be modelled into DIRECTT to achieve even better reconstruction results.
Even though we often do not knowingly recognize them, nanoparticles are present these days in most areas of our daily life, including food and its packaging, medicine, pharmaceuticals, cosmetics, pigments as well as electronic products, such as computer screens. The majority of these particles exhibits a core-shell morphology either intendedly or unintendedly. For the purpose of practicability, this core-shell nanoparticle (CSNP) morphology is often assumed to be ideal, namely a spherical core fully encapsulated by a shell of homogeneous thickness with a sharp interface between core and shell material. It is furthermore widely presumed that all nanoparticles in the sample possess the same shell thickness. As a matter of fact, most real CSNPs deviate in several ways from this ideal model with quite often severe impact on how efficiently they perform in a specific application.
The topic of this cumulative PhD thesis is the accurate characterization of the actual morphology of CSNPs by advanced X-ray analytical techniques, namely X-ray photoelectron spectroscopy (XPS) and scanning transmission X-ray microscopy (STXM). A special focus is on CSNPs which deviate from an ideal core-shell morphology. In the paper from 2019 nanoparticle shell thicknesses are extracted from the elastic-peak intensities in an XPS spectrum based on an ideal particle morphology. This happens for a series of CSNP samples comprising a poly(tetrafluoroethylene) (PTFE) core and either a poly(methyl methacrylate) (PMMA) or polystyrene (PS) shell. The same paper as well as the paper from 2020 demonstrate for the first time, that the analysis of the inelastic background in an XPS spectrum of CSNPs can identify and quantify the heterogeneity of the shell and the incomplete encapsulation of the core.
The result from an XPS experiment is always an average across a large nanoparticle ensemble. Deviations from an ideal morphology within a single particle of the sample cannot be assessed separately. As opposed to that, a spatial resolution of 35 nm enables STXM to visualize the interior of single CSNPs which exhibit a sufficient X-ray absorption contrast between core and shell material. In the paper from 2018 a STXM analysis is demonstrated based on the example of the PTFE-PS CSNP samples already mentioned in the previous paragraph.
In the publication from 2021 (Ca/Sr)F₂ core-shell like nanoparticle ensembles for the practical use in, among others, antireflective coatings are investigated. These nanoparticles do not possess a sharp interface between core and shell material, which is why a shell thickness determination as described in the second paragraph is inappropriate. Instead, in-depth profiles of the chemical composition are obtained by XPS experiments based on synchrotron radiation with variable X-ray photon energy to elucidate the internal morphology of the particles. Additionally, theoretical in-depth profiles of Ca and Sr XPS peak intensities are simulated, in order to facilitate the interpretation of the experiments. Thus, an enrichment of CaF₂ at the particle surface was determined, which could hardly have been assessed by any other analytical technique. Because this kind of non-destructive depth profiling by XPS is very demanding, more than usual effort is spent on gapless documentation of the experiments to ensure full reproducibility.
Due to the vast diversity of nanoparticles differing in material, composition and shape, a measurement procedure cannot unalteredly be transferred from one sample to another. Nevertheless, because the papers in this thesis present a greater depth of reporting on the experiments than comparable publications, they constitute an important guidance for other scientists on how to obtain meaningful information about CSNPs from surface analysis.
Die Alterung bestehender Brückenbauwerke fällt mit dem sich verschlechternden Zustand und zunehmenden Anforderungen an die Bausubstanz zusammen, die eine Folge von steigenden Verkehrszahlen und der Zulassung des Schwerlastverkehrs sind. Der daraus erwachsende Bedarf an Beurteilungen von bestehenden Brücken ist national und international fortwährend groß. Die Grundlage für Nachrechnungen sind die über das System verfügbaren Informationen. Sowohl die rechnerische Zuverlässigkeit eines Tragwerks als auch die Validität der Ergebnisse hängen im Wesentlichen vom Zustand, also von der Qualität und der Relevanz dieser Informationen ab. Die gezielte Messung von gütebewerteten, relevanten Informationen kann die Urteilsfähigkeit des Beurteilenden über die Zuverlässigkeit eines Tragwerks signifikant steigern. Wünschenswert ist die Erhebung derartiger Informationen ohne signifikante Eingriffe in die Bausubstanz.
Das Ziel der vorliegenden Arbeit ist die Entwicklung und Erprobung einer Vorgehensweise für die probabilistische Beurteilung von bestehenden Bauwerken mit zerstörungsfrei gemessenen Daten und einer Methodik zum objektiven Nachweis der Eignung von zerstörungsfreien Messverfahren zur Anwendung im Zuge einer Nachrechnung. Herausgestellt wird die Eignung der im Guide to the Expression of Uncertainty in Measurement (GUM) publizierten Regeln zur Bewertung der Qualität der gemessenen Informationen, die später im statischen Nachweis verwendet werden sollen. Die Anforderungen an die Basisvariablen, d. h. an die Eingangsgrößen im probabilistischen Nachweis, werden aus den Vorschriften zur Zuverlässigkeitsanalyse mit dem probabilistischen Näherungsverfahren FORM, der First Order Reliability Method, abgeleitet. Darauf basiert die Entwicklung der Schnittstelle zwischen der Messtechnik und der Nachrechnung. Im Kern werden die messdatenbasierten Basisvariablen explizit als Zufallsgrößen bei der Zuverlässigkeitsanalyse berücksichtigt. Die entwickelte Vorgehensweise wird am Beispiel von zwei Spannbetonbrücken und vier Basisvariablen erprobt. In die Nachweise der Biege- und der Querkrafttragfähigkeit sowie in einen Nachweis der Dekompression fließen geometrische Messergebnisse ein, die mithilfe von Radar- und Ultraschallmessungen generiert werden. Ein wichtiger Bestandteil ist die Bildung von Modellen zur Auswertung der Messungen und zur Berechnung der Messergebnisse.
Es wird gezeigt, dass die Einbeziehung der zerstörungsfrei generierten Messergebnisse die Unsicherheit in den Berechnungsmodellen reduzieren und den Grad der Annäherung der Modelle
an die Realität steigern kann. Die Messergebnisse sind zuverlässig und vergleichbar. Umfassende Sensitivitätsanalysen geben Aufschluss über sinnvollerweise zu messende Bauwerksparameter, die einen maßgeblichen Einfluss auf die Tragwerkszuverlässigkeit ausüben. Auf diese Weise wird die Relevanz der Informationen ermittelt. Das Potential derartiger Analysen für die gezielte Planung und Beauftragung von Messungen sowie für die bedarfsgerechte Zuschärfung von initial unzureichenden Berechnungsmodellen erscheint groß. Die messdatenbasierten Modelle können darüber hinaus die Robustheit einer Tragwerksanalyse steigern. Die Berücksichtigung von Messergebnissen ist dann besonders nützlich, wenn zur Beurteilung erforderliche Informationen fehlen oder Zweifel an den verfügbaren Informationen aufgekommen sind. Im besten Fall resultiert daraus die Verlängerung von rechnerischen Restnutzungsdauern, die Steigerung der Verfügbarkeit der Infrastruktur, die Optimierung des Ressourcenverbrauchs und insgesamt eine realitätsnahe Bauwerksbewertung.
Additive Manufacturing (AM) in terms of laser powder-bed fusion (L-PBF) offers new prospects regarding the design of parts and enables therefore the production of lattice structures. These lattice structures shall be implemented in various industrial applications (e.g. gas turbines) for reasons of material savings or cooling
channels. However, internal defects, residual stress, and structural deviations from the nominal geometry are unavoidable.
In this work, the structural integrity of lattice structures manufactured by means of L-PBF was non-destructively investigated on a multiscale approach.
A workflow for quantitative 3D powder analysis in terms of particle size, particle shape, particle porosity, inter-particle distance and packing density was established.
Synchrotron computed tomography (CT) was used to correlate the packing
density with the particle size and particle shape. It was also observed that at least about 50% of the powder porosity was released during production of the struts.
Struts are the component of lattice structures and were investigated by means of laboratory CT. The focus was on the influence of the build angle on part porosity and surface quality. The surface topography analysis was advanced by the quantitative characterisation of re-entrant surface features. This characterisation was compared with conventional surface parameters showing their complementary
information, but also the need for AM specific surface parameters.
The mechanical behaviour of the lattice structure was investigated with in-situ CT under compression and successive digital volume correlation (DVC). The Deformation was found to be knot-dominated, and therefore the lattice folds unit cell layer wise.
The residual stress was determined experimentally for the first time in such lattice structures. Neutron diffraction was used for the non-destructive 3D stress investigation. The principal stress directions and values were determined in dependence of the number of measured directions. While a significant uni-axial stress state was found in the strut, a more hydrostatic stress state was found in the knot. In both cases, strut and knot, seven directions were at least needed to
find reliable principal stress directions.