Analytische Chemie
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- 8.1 Sensorik, mess- und prüftechnische Verfahren (31) (entfernen)
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In this study, nanoscopic particles of magnesium Fluoride (MgF2) and calcium fluoride (CaF2) also known as nano metal fluorides (NMFs), were evaluated for their potential to improve wood durability. Even though these fluorides are sparingly soluble, their synthesis in the form of nano-sized particles turns them into promising candidates for wood preservation. Their distinct property of low-water solubility is proposed to maintain long-lasting protection of treated wood by reducing the leaching of fluoride. Analytical methods were used to characterize the synthesized NMFs and their distribution in treated wood specimens. Transmission electron microscopy images showed that these fluoride particles are smaller than 10 nm. In nano metal fluoride (NMF) treated specimens, aggregates of these particles are uniformly distributed in the wood matrix as confirmed with scanning electron microscopy images and their corresponding energy-dispersive X-ray spectroscopy maps. The fluoride aggregates form a protective layer around the tracheid walls and block the bordered pits, thus reducing the possible flow path for water absorption into wood. This is reflected in the reduced swelling and increased hydrophobicity of wood treated with NMFs. The biocidal efficacy of NMFs was tested against brown-rot fungi (Coniophora puteanaand Rhodonia placenta), white-rot fungus (Trametes versicolor), and termites (Coptotermes formosanus). The fungal and termite tests were performed in accordance with the EN 113 (1996) and EN 117 (2012) standards, respectively. Prior to fungal tests, the NMF treated wood specimens were leached according to the EN 84 (1997)standard. Compared to untreated specimens, the NMF treated wood specimens have a higher resistance to decay caused by brown-rot fungi, white-rot fungus, and termites. Although all NMF treatments in wood reduce the mass loss caused by fungal decay, only the combined treatment of MgF2 and CaF2 has efficacy against both brown-rot fungi and white-rot fungus. Similarly, wood treated with the combined NMF formulation is the least susceptible to attack by C. formosanus.It is proposed that combining MgF2 and CaF2changes their overall solubility to promote the release of fluoride ions at the optimal concentration needed for biocidal efficacy against fungi and termites. In this thesis, it was proven that even after leaching, sufficient fluoride was present to protect NMF treated wood from fungal decay. This shows that NMFs are robust enough for above ground contact outdoor applications of wood, where permanent wetness cannot be avoided according to Use Class 3.2, as per the EN 335 (2013) standard. Also, they pose a low risk to human health and the environment because they are sparingly soluble. Since NMFs significantly reduce the decay of wood, the CO2 fixed in it will be retained for longer than in unpreserved wood. Overall, the novel results of this study show the potential of NMFs to increase the service life of building materials made from non-durable wood.
The presence of wastewater and air pollution has become an important risk factor for citizens, not only in terms of problems related to health risks, but also because of its negative impact on the country's image. For this reason, malodorous emission monitoring and control techniques are in high demand in urban areas and industries. The aim of this work is first to build an electronic nose (e-nose) and a Voltammetric Electronic tongue (VE-tongue) in order to study their ability to discriminate between polluted and clean environmental samples. Secondly, Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS), and Solid Phase Micro Extraction-Gas Chromatography–Mass Spectrometry (SPME-GC-MS) are utilized to explain this discrimination by identifying specific compounds from these samples. Indeed, the e-nose, consisted of metal oxide semiconductor gas sensors, is used for the assessment of the studied odorous air and headspace samples from water and wastewater sites. Moreover, the VE-tongue, based on metal electrodes, is utilized to determine the patterns of the sensor array responses, which serve as fingerprints profiles of the analyzed liquid samples. Chemometric tools, such as Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Support Vector Machines (SVMs) are operated for the processing of data from the e-nose and the VE-tongue. By using the both systems, the analyses of headspace and liquid samples from the seven sites allow better discrimination. To explain the cause of the obtained discrimination, TD-GC-MS and SPME-GC-MS analyses are well performed to identify compounds related sites. According to these outcomes, the proposed e-nose and VE-tongue are proved to be rapid and valuable tools for analysis of environmental polluted matrices.
Wireless sensor networks provide occupational health experts with valuable information about the distribution of air pollutants in an environment. However, especially low-cost sensors may produce faulty measurements or fail completely. Consequently, not only spatial coverage but also redundancy should be a design criterion for the deployment of a sensor network. For a sensor network deployed in a steel factory, we analyze the correlations between sensors and build machine learning forecasting models, to investigate how well the sensor network can compensate for the outage of sensors. While our results show promising prediction quality of the models, they also indicate the presence of spatially very limited events. We, therefore, conclude that initial measurements with, e.g., mobile units, could help to identify important locations to design redundant sensor networks.
Sensors can fail. Redundancy should therefore be a design driver of wireless sensor networks. For a sensor network deployed in a steel factory, we analyze the correlations between sensors and build machine learning forecasting models, to investigate how well the network can compensate for the outage of sensors.
The applicability of three methods developed by finite element analysis (FEM) and proposed in the literature are studied on steel S355. Instrumented indentation tests using spherical indenters of radius 200 and 500 μ m are performed in the macro range at depths of more than 6 μ m. The results of the selected methods are compared with the tensile test. To evaluate the partially strongly varying results, the uncertainties of the calculated strain hardening exponent, n, and yield stress, Y, are estimated. Recommendations for an appropriated procedure of the indentation test are given. The machine compliance and the determination of the zero point of Depth play an essential role. If the certain conditions are considered, the instrumented indentation Tests can be used, in particular for investigations of specimens with inhomogeneous elastoplasticity.
The best-known discretization methods for solving engineering problems formulated as partial differential equations are finite difference method (FDM), finite element method (FEM) and finite volume method (FVM). While the finite volume method is used in fluid mechanics, the finite element method is predominant in solid state mechanics. At first glance, FVM and FEM are two highly specialized methods. However, both methods can solve problems of both solid mechanics and fluid mechanics well. Since experimental mechanics deals not only with solid state physics but also with fluid mechanics problems, we want to understand FVM in the sense of FEM in this work. In the long term, we want to use the variational calculus to unify many important numerical methods in engineering science into a common framework. In this way, we expect that experiences can be better exchanged between different engineering sciences and thus innovations in the field of experimental mechanics can be advanced. But in this work, we limit ourselves to the understanding of the FVM with the help of the variational calculus already known in FEM. We use a simple 1D Poisson equation to clarify the point. First, we briefly summarize the FVM and FEM. Then we will deal with the actual topic of this paper, as we establish the FEM and the FVM on a common basis by variation formulation. It is shown here that the FVM can be understood in terms of the finite element method with the so-called Galerkin-Petrov approach.
The best-known discretization methods for solving engineering problems formulated as partial differential equations are finite difference method (FDM), finite element method (FEM) and finite volume method (FVM). While the finite volume method is used in fluid mechanics, the finite element method is predominant in solid state mechanics. At first glance, FVM and FEM are two highly specialized methods. However, both methods can solve problems of both solid mechanics and fluid mechanics well. Since experimental mechanics deals not only with solid state physics but also with fluid mechanics problems, we want to understand FVM in the sense of FEM in this work. In the long term, we want to use the variational calculus to unify many important numerical methods in engineering science into a common framework. In this way, we expect that experiences can be better exchanged between different engineering sciences and thus innovations in the field of experimental mechanics can be advanced. But in this work, we limit ourselves to the understanding of the FVM with the help of the variational calculus already known in FEM. We use a simple 1D Poisson equation to clarify the point. First, we briefly summarize the FVM and FEM. Then we will deal with the actual topic of this paper, as we establish the FEM and the FVM on a common basis by variation formulation. It is shown here that the FVM can be understood in terms of the finite element method with the so-called Galerkin-Petrov approach.
The testing of gas and humidity sensors is essential for the application of sensing devices. The testing determines properties of an investigated humidity sensor or gas sensor. In testing, the sensor property is the observed response of a sensing system to an input stimulus in comparison to a reference within a test procedure. This tutorial is structured into six chapters. The first chapter is about basics of hygrometry and gas sensing. It includes definitions, sensor classification, overview of application categories, as well as construction and functional principles. The chapter on requirements of deployed sensors focus on stability, response time, cross-sensitivity, electrical and mechanical requirements, and other. The sensing performance is characterised by determinations of parameters like accuracy, repeatability, detection limits (low and high), and response/recovery time. The description of testing signals on specified qualitative and quantitative characteristics, and the adequately estimated measurement uncertainty is the content of the analysis chapter. All chapters contain examples of testing procedures from testing/calibration labs for hygrometers and gas sensors which are essential for implementation into quality management systems.
The determination of the measurement uncertainty of quantitative and qualitative results is an important quality management tool, for example to describe measuring equipment, procedures, measurement results and the quality of products. The lecture presents the process description for the determination of the measurement uncertainty according to GUM, the determination of uncertainties in qualitative measurement results and the application of the measurement uncertainty for conformity assessment.
Sensor systems are widely used in hydrogen technologies. The lecture presents requirements and properties of sensor systems and shows application examples of these technologies for safety and process control for hydrogen technologies. The focus is on gas sensors as well as sensors for pressure, temperature and gas flow. These systems are applied, among other things, for monitoring and control of operating conditions, indication of hazardous conditions and triggering of alarms.