Chemie und Prozesstechnik
Filtern
Dokumenttyp
- Zeitschriftenartikel (1176)
- Vortrag (1068)
- Posterpräsentation (442)
- Beitrag zu einem Tagungsband (175)
- Forschungsdatensatz (56)
- Sonstiges (30)
- Buchkapitel (24)
- Forschungsbericht (23)
- Dissertation (15)
- Beitrag zu einem Sammelband (13)
- Preprint (13)
- Handbuch (5)
- Video (5)
- Zeitschriftenheft (Herausgeberschaft für das komplette Heft) (3)
- Sammelband (Herausgeberschaft für den kompletten Band) (2)
- Tagungsband (Herausgeberschaft für den kompletten Band) (1)
- Newsletter (1)
Sprache
- Englisch (3052) (entfernen)
Schlagworte
- Nanoparticles (114)
- Fluorescence (111)
- Concrete (89)
- LIBS (81)
- Mechanochemistry (72)
- Quantum yield (71)
- Ultrasound (71)
- SAXS (69)
- Non-destructive testing (68)
- XPS (61)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (1086)
- 6 Materialchemie (975)
- 8 Zerstörungsfreie Prüfung (775)
- 6.1 Oberflächen- und Dünnschichtanalyse (348)
- 6.3 Strukturanalytik (323)
- 1.1 Anorganische Spurenanalytik (276)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (232)
- 1.2 Biophotonik (210)
- 4 Material und Umwelt (186)
- 8.5 Röntgenbildgebung (169)
Paper des Monats
- ja (27)
Relaxation phenomena observed in the electrical low-frequency range (approximately 1 mHz-10 kHz) of natural porous media like sandstones is often assumed to be directly related to the dominant (modal) pore throat sizes measured, for instance, with mercury intrusion porosimetry. Attempts to establish a universally valid relationship between pore size and peak Spectral Induced Polarization (SIP) relaxation time have failed, considering sandstones from very different origins and featuring great variations in textural and chemical compositions as well as in geometrical pore space properties. In addition working with characteristic relaxation times determined in Cole-Cole or Debye decomposition fits to build the relationship have not been successful. In particular, samples with narrow pore throats are often characterized by long SIP relaxation times corresponding to long “characteristic length scales” in these media, assuming that the diffusion coefficients along the electrical double layer were constant. Based on these observations, three different types of SIP relaxation can be distinguished. We present a new way of assessing complex pore spaces of very different sandstones in a multi-methodical approach to combine the benefits of mercury intrusion porosimetry, micro-computed tomography, and nuclear magnetic resonance. In this way, we achieve much deeper insight into the pore space due to the different resolutions and sensitivities of the applied methods to both pore constrictions (throats) and wide pores (pore bodies). We experimentally quantify pore aspect ratios and volume distributions within the two pore regions. We clearly observe systematic differences between three SIP relaxation types identified previously and can attribute the SIP peak relaxation times to measured characteristic length scales within our materials. We highlight selected results for a total of nine sandstones. It seems that SIP relaxation behavior depends on the size difference of the narrow pore throats to the wide pore bodies, which increases from SIP Type 1 to Type 3.
Half-Cell-Potential Mapping (HP) is the most popular non-destructive testing (NDT) method for the detection of active corrosion in reinforced concrete. HP is influenced by parameters such as moisture and chloride gradients in the component. The sensitivity to the spatially small, but dangerous pitting is low. In this study we show how additional measurement information can be used with multi-sensor data fusion to improve the detection performance and to automate data evaluation. The fusion is based on supervised machine learning (SML). SML are methods that recognize relationships in (sensor) data based on given labels. We use SML to distinguish "defective" and "intact" labeled areas in our dataset. It consists of 18 measurement - each contains HP, ground radar, microwave moisture and Wenner resistivity data. Exact labels for changing environmental conditions were determined in a laboratory study on a reinforced concrete slab, which deteriorated controlled and accelerated. The deterioration progress was monitored continuously and corrosion was generated targeted at a predefined location. The detection results are quantified and statistically evaluated. The data fusion shows a significant improvement over the best single method (HP). We describe the challenges of data-driven approaches in nondestructive testing and show possible solutions.
Welcome to the poster Towards Determination of Surface Roughness from a SEM Image, a contribution from BAM in Berlin, Germany. This work is part of the MamaLoCA project, which aims to develop a biosensor for the detection of mycotoxins in cereals. Biosensors come in a great variety, one of which makes use of microscopic beads produced by homogenous coating of polystyrene microspheres. The beads are functionalized by decorating them with bioreceptors – in our case antibodies – which then specifically react with the analyte – in our case mycotoxins – and emit an electrical or optical signal. The functionalization of the beads depends on the surface roughness because this determines the amount and orientation of binders. In other words, the surface roughness affects the accessibility to the binding sites and influences device sensitivity, hence its quantitative determination is an important step in evaluating the quality of the biosensor in general.
The presented solution to the problem of the estimation of surface roughness relies in the repetitive characteristics on the surface of the beads. A SEM image of the bead shows a raspberry like microparticle with a variation of grayscale values, which arise from the secondary electron yield. The principle of the measurement measures the variation of grayscale values along a circumference of a circle centred in the centre of the particle and with an arbitrary radius. The grayscale value variation along the given circumference gives the so-called z-modulation or the lateral profile. By performing Fast Fourier Transform on this profile we obtain the power spectrum as a function of the spatial frequencies through which the grayscales vary. The maximal value for spatial frequency then reveals the most common feature along one given circumference. Surface roughness then is the feature frequency in the spatial domain. This calculation is repeated for several concentric circles with different radii over the particle.
The results for the same particle but recorded at two different accelerating voltages show that the applied method has a potential to reveal the roughness. Interpretation of results from an SE InLens SEM image obtained using 3 kV shows that surface roughness is about 21 nm, which is in a good agreement with an alternative method given in a different presentation. The results from the 10 kV are underestimated due to the loss of surface sensitivity on the SE InLens detection at high voltages.
In conclusion, this method shows promise in determining quantitatively the surface roughness from a single SEM image and its validation is being sought using 3D SEM images and AFM methods.
Matrix‐assisted ionization (MAI) mass spectrometry does not require voltages, a laser beam, or added heat to initiate ionization, but it is strongly dependent on the choice of matrix and the vacuum conditions. High charge state distributions of nonvolatile analyte ions produced by MAI suggest that the ionization mechanism may be similar to that of electrospray ionization (ESI), but different from matrix‐assisted laser desorption/ionization (MALDI). While significant information is available for MAI using mass spectrometers operating at atmospheric and intermediate pressure, little is known about the mechanism at high vacuum.
Eleven MAI matrices were studied on a high‐vacuum time‐of‐flight (TOF) mass spectrometer using a 266 nm pulsed laser beam under otherwise typical MALDI conditions. Detailed comparisons with the commonly used MALDI matrices and theoretical prediction were made for 3‐nitrobenzonitrile (3‐NBN), which is the only MAI matrix that works well in high vacuum when irradiated with a laser.
Screening of MAI matrices with good absorption at 266 nm but with various degrees of volatility and laser energies suggests that volatility and absorption at the laser wavelength may be necessary, but not sufficient, criteria to explain the formation of multiply charged analyte ions. 3‐NBN produces intact, highly charged ions of nonvolatile analytes in high‐vacuum TOF with the use of a laser, demonstrating that ESI‐like ions can be produced in high vacuum. Theoretical calculations and mass spectra suggest that thermally induced proton transfer, which is the major ionization mechanism in MALDI, is not important with the 3‐NBN matrix at 266 nm laser wavelength. 3‐NBN:analyte crystal morphology is, however, important in ion generation in high vacuum.
The 3‐NBN MAI matrix produces intact, highly charged ions of nonvolatile compounds in high‐vacuum TOF mass spectrometers with the aid of ablation and/or heating by laser irradiation, and shows a different ionization mechanism from that of typical MALDI matrices.
In this paper one refined approach is applied to determine the exact orientation of bipyramidal TiO2 nanoparticles prepared with good dispersion as almost isolated particles on a carbon TEM grid. The advantages of the recently developed high-throughput Transmission Kikuchi Diffraction (TKD) are used to identify quickly and reliably the geometrical orientation of the crystalline TiO2 nanoparticle bipyramids (anatase) on a statistically relevant number of particles.
In this paper one refined approach is applied to determine the exact orientation of bipyramidal TiO2 nanoparticles prepared with good dispersion as almost isolated particles on a carbon TEM grid. The advantages of the recently developed high-throughput Transmission Kikuchi Diffraction (TKD) are used to identify quickly and reliably the geometrical orientation of the crystalline TiO2 nanoparticle bipyramids (anatase) on a statistically relevant number of particles.
As part of the development of a library of accurate and efficient methods for measurement of nanoparticle properties, we develop and optimize a method for the efficient analysis of nanoparticle size distribution from suspensions via microprinting and digital analysis of electron microscopy (SEM and TEM) images, with the ultimate aim of automated quantitative concentration analysis (calculated from drop volume). A series of different nanoparticle suspensions (gold, latex, and SiO2 in varying sizes and concentrations) were printed onto TEM grids in a 4 x 4 array in the concentration range 7x10^8 to 1x10^11 nanoparticles/mL and imaged with SEM. Concentrations and printing conditions (temperature, relative humidity) were varied in order to minimize the coffee-ring effect.
A series of different nanoparticle suspensions (Gold, Latex, and SiO2 in varying concentrations) were microprinted onto TEM grids in a 4 x 4 array in the concentration range 7x10^8 to 1x10^11 NP/mL and imaged with SEM and TSEM. Concentrations and printing conditions (temperature, relative humidity) were varied in order to minimize the coffee ring effect.
Measurement of nanoparticle size (distribution) becomes a challenging analytical problem when non-spherical nanoparticles must be accurately measured. Most industrial nanoparticles have not only non-spherical shapes but also possess polydisperse size distributions, and due to their agglomeration/aggregation state are difficult (or even impossible) to be addressed individually. Moreover, driven by regulatory purposes related to the identification of a material as a nanomaterial, the accurate measurement of the smallest dimension of a (nano)particulate material makes the analysis even more complex.
In the first phase of the EU Project nPSize - Improved traceability chain of nanoparticle size measurements (https://www.bam.de/Content/DE/Projekte/laufend/nPSize/npsize.html), the efforts are focused on synthesis of nanoparticles of well-defined, non-spherical shape. Following candidates of reference materials (CRM) with certifiable particle size (distribution) are under characterization with respect to their homogeneity and stability: (i) titania nanoplatelets (10-15 nm thickness x 50-60 nm lateral), (ii) titania bipyramides (~60 nm length x 40 nm width), (iii) titania acicular particles (100 nm length x 15-20 nm width; aspect ratio 5.5/6), (iv) gold nanorods (~10 nm width x 30 nm length), and (v) gold nanocubes (~55 nm x 55 nm x 55 nm).
Most industrial nanoparticles have non-spherical shapes and also possess polydisperse size distributions, and due to their agglomeration/ aggregation state are difficult (or even impossible) to be addressed individually. Further, driven by regulatory purposes related to the identification of a material as a nanomaterial, the accurate measurement of the smallest dimension of a (nano)particulate material makes the analysis even more complex.
In the first phase of the EU Project nPSize - Improved traceability chain of nanoparticle size measurements (https://www.bam.de/Content/DE/Projekte/laufend/nPSize/npsize.html), the efforts are focused on synthesis of nanoparticles of well-defined, non-spherical shape. Following candidates of reference materials (CRM) with certifiable particle size (distribution) are under characterization with respect to their homogeneity and stability: (i) titania nanoplatelets (10-15 nm thickness x 50-60 nm lateral), (ii) titania bipyramides (~60 nm length x 40 nm width), (iii) titania acicular particles (100 nm length x 15-20 nm width; aspect ratio 5.5/6), (iv) gold nanorods (~10 nm width x 30 nm length), and (v) gold nanocubes (~55 nm x 55 nm x 55 nm).
The Industrial Internet of Things (IIoT) poses multiple challenges to traditional standardization, due to the complexity, dynamics, and accelerating speed of technological progress. The need for a timely availability of standards calls for new approaches and tools to enhance standardization processes for smart manufacturing. Industry and standards development organizations worldwide are seeking new solutions. Testbeds have been acknowledged in innovation policy as a powerful tool for knowledge transfer and the further development of emerging technologies. Lately, they have also attracted increasing attention from the standardization perspective as a promising tool for a more agile standards development process. Proponents of such testbeds expect them to support standardization by providing validated solutions and accelerating the processes to meet the growing demands for faster standardization without any detriment to quality. In an explorative, qualitative approach this article is the first to investigate the operation and impact of testbeds in standardization processes based on a multiple case study on testbeds implemented worldwide in the context of the IIoT.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
Core-shell (CS) particles have been increasingly used for a wide range of applications due to their unique properties by merging individual characteristics of the core and the shell materials. The functionality of the designed particles is strongly influenced by their surface roughness. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task for Scanning Electron Microscopy (SEM).
The SEM images contain two-dimensional (2D) information providing contour roughness data only from the projection of the particle in the horizontal plane. This study presents a practical procedure to achieve more information by tilting the sample holder, hence allowing images of different areas of a single particle to be recorded at different orientations under the same view angle. From the analysis of these images, quasi three-dimensional (3D) information is obtained.
Three types of home-made particles were investigated: i) bare polystyrene (PS) particles, ii) PS particles decorated with a first magnetic iron oxide (Fe3O4) nanoparticle shell forming CS microbeads, iii) PS/Fe3O4 particles closed with a second silica (SiO2) shell forming core-shell-shell (CSS) microbeads. A series images of a single particle were taken with stepwise tilted sample holder up to 10° by an SEM with high-resolution and surface sensitive SE-InLens® mode.
A reliable analysis tool has been developed by a script in Python to analyze SEM images automatically and to evaluate profile roughness quantitatively, for individual core-shell microparticles. Image analysis consists of segmentation of the images, identifying contour and the centre of the particle, and extracting the root mean squared roughness value (RMS-RQ) of the contour profile from the particle projection within a few seconds.
The variation in roughness from batch-to-batch was determined with the purpose to set the method as a routine quality check procedure. Flow cytometry measurements provided complementary data. Measurement uncertainties associated to various particle orientations were also estimated.
The availability of non-destructive methods is particularly important for composites, e.g., carbon or glass fiber-reinforced polymers because their properties strongly depend on the manufacturing process and in-service conditions. Composites are mostly used in thin-walled components which are perfectly suited for the characterisation with ultrasonic guided waves (UGWs).
In this contribution, we demonstrate sensitivities of UGW to different elastic constants of a composite material. Then we present a characterisation procedure which can be used to in-fer elastic properties. Our approach is based on an inverse procedure in which the numeri-cally calculated dispersion curves are fitted to the measured curves. The acquisition is done by applying a broadband piezoelectric transducer (PZT) to excite various UGW modes and a 3D laser Doppler vibrometer (3D LDV) to record them. Compared to the approaches based on laser excitation, the PZT provides a better signal-to-noise ratio because more energy is brought into the structure. Whereas the 3D LDV compared to a 1D LDV or a PZT allows cap-turing in-plane and out-of-plane components giving more dispersion information for a better characterisation. Since the inverse procedure requires many iterations before elastic prop-erties are retrieved, an efficient tool for the calculation of the dispersion curves is necessary. For this, the Scaled Boundary Finite Element Method is used. All in all, a good agreement be-tween theoretical and experimental curves is demonstrated.
Half-Cell-Potential Mapping (HP) is the most popular non-destructive testing (NDT) method for the detection of active corrosion in reinforced concrete. HP is influenced by parameters such as moisture and chloride gradients in the component. The sensitivity to the spatially small, but dangerous pitting is low. In this study we show how additional measurement information can be used with multi-sensor data fusion to improve the detection performance and to automate data evaluation. The fusion is based on supervised machine learning (SML). SML are methods that recognize relationships in (sensor) data based on given labels. We use SML to distinguish "defective" and "intact" labeled areas in our dataset. It consists of 18 measurement - each contains HP, ground radar, microwave moisture and Wenner resistance data. Exact labels for changing environmental conditions were available in a laboratory study on a reinforced concrete slab, which deteriorated controlled and accelerated. The deterioration progress was monitored continuously and corrosion was generated targeted at a predefined location. The detection results are quantified and statistically evaluated. The SML results shows a significant improvement over the best single method (HP).
In the face of rising energy demand and the impending climate change the development of a sustainable, fossil-free fuel and chemical production is of global importance. One possible goal is the development of electrochemical conversion processes using catalysts. Porous materials play an important role in such energy applications. The key to the development of improved catalysts is a better understanding of the relations between their performance, stability and physico-chemical properties. However, the complex morphology of such catalysts constitutes a challenge even for modern analytical techniques.
Spectroscopic ellipsometry (SE) is a versatile method for studying material properties by using appropriate models (e.g. film thickness, optical and electronic properties). The fact that the material properties cannot be taken directly from the measured spectra, the developed models have to be validated. In a first step, the model for the ellipsometric fit studies of a calcination series of mesoporous iridium oxide films (300 – 600 °C) was investigated and validated with respect to their material properties. Moreover, the electronic structures of the catalysts reveal a direct correlation with electrochemical activities. The development of an environmental cell offers the possibility of investigations under real conditions. This will allow changes in the optical and electronic properties during the electrocatalytic oxygen evolution reaction.
In the face of rising energy demand and the impending climate change the development of a sustainable, fossil-free fuel and chemical production is of global importance. One possible goal is the development of electrochemical conversion processes using catalysts. Porous materials play an important role in such energy applications. The key to the development of improved catalysts is a better understanding of the relations between their performance, stability and physico-chemical properties. However, the complex morphology of such catalysts constitutes a challenge even for modern analytical techniques. Spectroscopic ellipsometry (SE) is a versatile method for studying material properties by using appropriate models (e.g. film thickness, optical and electronic properties). The fact that the material properties cannot be taken directly from the measured spectra, the developed models have to be validated. In a first step, the model for the ellipsometric fit studies of a calcination series of mesoporous iridium oxide films (300 – 600 °C) was investigated and validated with respect to their material properties. Moreover, the electronic structures of the catalysts reveal a direct correlation with electrochemical activities. The development of an environmental cell offers the possibility of investigations under real conditions. This will allow changes in the optical and electronic properties during the electrocatalytic oxygen evolution reaction.
Data-driven analysis for damage assessment has a large potential in structural health monitoring (SHM) systems, where sensors are permanently attached to the structure, enabling continuous and frequent measurements. In this contribution, we propose a machine learning (ML) approach for automated damage detection, based on an ML toolbox for industrial condition monitoring. The toolbox combines multiple complementary algorithms for feature extraction and selection and automatically chooses the best combination of methods for the dataset at hand. Here, this toolbox is applied to a guided wave-based SHM dataset for varying temperatures and damage locations, which is freely available on the Open Guided Waves platform. A classification rate of 96.2% is achieved, demonstrating reliable and automated damage detection. Moreover, the ability of the ML model to identify a damaged structure at untrained damage locations and temperatures is demonstrated.
A major advantage in the reassessment of existing structures is the possibility of including measured data that describe the actual properties and the current condition of the structure to be reassessed. Currently, the incorporation of such measured information is mostly unregulated. However, the use of measurement results is vitally important, since a measured data-based improvement of the computation models level of approximation can lead at least to more meaningful results, possibly to extended remaining life times of the structure and in the best case to a saving of resources. Conversely, not appreciating well measurable and relevant information can be equated with a waste of resources. In this paper, a concept for the comparable use of non-destructively measured data as basic variables in probabilistic reliability assessments is outlined and examined using a typical prestressed concrete road bridge as a case-study. An essential requirement is the calculation of measurement uncertainties in order to evaluate the quality of the measurement results comparably. In conclusion, the example of ultrasonic and radar measurement data is used to demonstrate the effects that the incorporation of the measured information has on the reliability of the structure.
Against the background of sustainable resource management and efficiency, wood-based materials are currently experiencing a revival and, among others, plywood, Laminated Veneer Lumber and glued laminated timber are becoming increasingly more important in the building sector. Even though these materials are so-called engineered products, the element wood is naturally grown with intrinsic variability in mechanical properties and requires professional handling on-site. Otherwise, load-bearing structures made of wood materials may entail certain risks. Critical situations can, in principle, be avoided by implementing a structural health monitoring system into components or structures made from wood material. The aim is to indicate accumulation of mechanical damage and to eliminate or at least significantly reduce the risk of unexpected failure. Toward this purpose, the failure behavior of several layered wood materials under quasi-static tension was investigated in laboratory-scale experiments by means of acoustic emission (AE) measurement. Based on spectral analysis and pattern recognition, two classes of AE signals are identified for each investigated lay-up that are characterized by either low or high frequency contents in the respective power spectra. AE activity and intensity of both signal classes are analyzed, striving for predictors appropriate for AE monitoring concepts.
Against the background of sustainable resource management and efficiency, wood-based materials are currently experiencing a revival and, among others, plywood, Laminated Veneer Lumber and glued laminated timber are becoming increasingly more important in the building sector. Even though these materials are so-called engineered products, the element wood is naturally grown with intrinsic variability in mechanical properties and requires professional handling on-site. Otherwise, load-bearing structures made of wood materials may entail certain risks. Critical situations can, in principle, be avoided by implementing a structural health monitoring system into components or structures made from wood material. The aim is to indicate accumulation of mechanical damage and to eliminate or at least significantly reduce the risk of unexpected failure. Toward this purpose, the failure behavior of several layered wood materials under quasi-static tension was investigated in laboratory-scale experiments by means of acoustic emission (AE) measurement. Based on spectral analysis and pattern recognition, two classes of AE signals are identified for each investigated lay-up that are characterized by either low or high frequency contents in the respective power spectra. AE activity and intensity of both signal classes are analyzed, striving for predictors appropriate for AE monitoring concepts.
Analysis of single cells via LA-ICP-MS is a technique with great potential, however manual targeting of single cells is laborious and therefore microarraying of cells looks promising. In this work, we investigate the potential of a commercial non-contact piezo dispenser arraying system (S3, Scienion AG, Berlin), equipped with a novel technology for single-cell isolation called CellenONE™ (Cellenion, Lyon). Usually if one aims to create a microarray of single cells via spotting a suitably diluted cell suspension, one will observe a Poisson-distributed cell number per spot. CellenONE™ overcomes this problem by controlling the number of cells optically in the piezo dispense capillary (PDC) via image recognition to obtain true single cell arrays. The figures of merit of the customized and optimized setup will be presented. In a proof of concept experiment we investigated the trace elemental fingerprint of THP-1 cells by LA-ICP-TOF-MS (Analyte G2, Teledyne Cetac; icpTOF, TOFWERK) and quantified two metal cell dyes, mDOTA-Ho (CheMatech, Dijon), and Ir-DNA intercalator (Fluidigm, San Francisco). For that, matrix matched calibration standards after Wang et al. were successfully prepared using the same arraying system. We believe that this novel approach opens new ways for automated quantitative single cell LA-ICP-MS.
Nowadays the Instrumented Indentation Testing (IIT) is one of the most commonly used methods to determine the mechanical properties of materials in the nano range. This method is already extensive standardized in EN ISO 14577 part 1-4. Because of the great interest of researchers and industries in investigations of time depending material behavior mostly all suppliers of IIT equipment are offering the possibility of dynamic testing. Realizing this development ISO/TC 164/SC3 Hardness Testing has proposed to start the new standardization project “Linear elastic dynamic instrumented indentation testing DIIT”. The development of this standard is accompanied by the first international intercomparing exercise comparing results of dynamic instrumented indentation testing from testing machines using different hardware solutions and different models for data evaluation.
The draft of part 5 of ISO 14577 “Linear elastic dynamic instrumented indentation testing DIIT” specifies verification and calibration of testing machines for carrying out the measurement of the dynamic material response when an oscillatory force or displacement, with amplitudes small in comparison to the prescribed target values, is imparted to the indenter while the indenter is continuously loaded to a prescribed target load or target depth or while the load or displacement is held constant at a prescribed target value. In case of a material showing plastic-elastic behavior, the measured dynamic response is used for continuous evaluation of the dynamic stiffness of the contact as a function of depth and frequency. Using the dynamic stiffness of the contact a reduced dynamic modulus will be calculated. In case of a material showing visco-elastic behavior from the measured dynamic response also the dynamic contact damping coefficient as function of depth and frequency is evaluated continuously. Using dynamic contact stiffness and dynamic contact damping coefficient reduced lost and storage modulus for visco-elastic materials will be calculated.
The main normative requirements of the draft will be presented and discussed in the light of the first results of the intercomparing excise.
Towards Unbiased Evaluation of Ionization Performance in LC-HRMS Metabolomics Method Development
(2022)
As metabolomics increasingly finds its way from basic science into applied and regulatory environments, analytical demands on nontargeted mass spectrometric detection methods continue to rise. In addition to improved chemical comprehensiveness, current developments aim at enhanced robustness and repeatability to allow long-term, inter-study, and meta-analyses. Comprehensive metabolomics relies on electrospray ionization (ESI) as the most versatile ionization technique, and recent liquid chromatography-high resolution mass spectrometry (LC-HRMS) instrumentation continues to overcome technical limitations that have hindered the adoption of ESI for applications in the past. Still, developing and standardizing nontargeted ESI methods and instrumental setups remains costly in terms of time and required chemicals, as large panels of metabolite standards are needed to reflect biochemical diversity. In this paper, we investigated in how far a nontargeted pilot experiment, consisting only of a few measurements of a test sample dilution series and comprehensive statistical analysis, can replace conventional targeted evaluation procedures. To examine this potential, two instrumental ESI ion source setups were compared, reflecting a common scenario in practical method development. Two types of feature evaluations were performed, (a) summary statistics solely involving feature intensity values, and (b) analyses additionally including chemical interpretation.
Results were compared in detail to a targeted evaluation of a large metabolite standard panel. We reflect on the advantages and shortcomings of both strategies in the context of current harmonization initiatives in the metabolomics field.
To keep pace with the rising number of detected mycotoxins, there is a growing need for fast and reliable toxicity tests to assess the potential threat to food safety. Toxicity tests with the bacterial-feeding nematode Caenorhabditis elegans as model organism are well established. In this study the C. elegans wildtype strain N2 (var. Bristol) was used to investigate the toxic effects of the food-relevant mycotoxins citrinin (CIT) and zearalenone-14-sulfate (ZEA-14-S) and zearalenone (ZEA) on different life cycle parameters including reproduction, thermal and oxidative stress resistance and lifespan. The metabolization of the mycotoxins by the nematodes in vivo was investigated using HPLC-MS/MS. ZEA was metabolized in vivo to the reduced isomers α-zearalenol (α-ZEL) and β-ZEL. ZEA 14-S was reduced to α-/β-ZEL 14-sulfate and CIT was metabolized to mono-hydroxylated CIT. All mycotoxins tested led to a significant decrease in the number of nematode offspring produced. ZEA and CIT displayed negative effects on stress tolerance levels and for CIT an additional shortening of the mean lifespan was observed. In the case of ZEA-14-S, however, the mean lifespan was prolonged. The presented study shows the applicability of C. elegans for toxicity testing of emerging food mycotoxins for the purpose of assigning potential health threats.
Only a few scientific evidences for the use of Egyptian blue in Early Medieval wall paintings in Central and Southern Europe have been reported so far. The monochrome blue fragment discussed here belongs to the second church building of St. Peter above Gratsch (South Tyrol, Northern Italy, fifth/ sixth century A.D.). Beyond cuprorivaite and carbon black (underpainting), 26 accessory minerals down to trace levels were detected by means of Raman microspectroscopy, providing unprecedented insights into the raw materials blend and conversion reactions during preparation, application, and ageing of the pigment. In conjunction with archaeological evidences for the manufacture of Egyptian blue in Cumae and Liternum and the concordant statements of the antique Roman writers Vitruvius and Pliny the Elder, natural impurities of the quartz sand speak for a pigment produced at the northern Phlegrean Fields (Campania, Southern Italy). Chalcocite (and chalcopyrite) suggest the use of a sulphidic copper ore, and water-insoluble salts a mixed-alkaline flux in the form of plant ash. Not fully reacted quartz crystals partly intergrown with cuprorivaite and only minimal traces of silicate glass portend solid-state reactions predominating the chemical reactions during synthesis, while the melting of the raw materials into glass most likely played a negligible role.
Trace elements are chemical elements whose concentration in a material is very low. The exact definition depends on the application and varies for example between 100 micrograms per gram in analytical chemistry and 1000 micrograms per gram in geology. The ability to detect trace elements fast and quantitatively is of great importance in many areas of science and technology. With its high brilliance and flexibility in the excitation conditions, synchrotron radiation is an ideal tool for detecting traces even in small sample quantities. In this contribution I will report about the use of X-ray fluorescence(XRF)for qualitative and quantitative element sensitiveanalysis. In addition to the fundamentals of XRF and its quantification methods, the advantages and problems of different geometries like e.g. microXRF, Total Reflection X-ray Fluorescence (TXRF)or Double Dispersive XRF (D²XRF) will be discussed. Practical examples from BAMline from the research fields of medicine, geology and archaeometry will complete the lecture.
Traceable determination of non-static XCT machine geometry: New developments and case studies
(2022)
It is fundamental to determine the machine geometry accurately for dimensional X-ray computed tomography (XCT) measurements. When performing high-accuracy scans, compensation of a non-static geometry, e.g. due to rotary axis errors or drift, might become necessary. Here we provide an overview of methods to determine and account for such deviations on a per projection basis. They include characterisation of stage error motions, in situ geometry measurements, numerical simulations, and reconstruction-based optimization relying on image quality metrics and will be discussed in terms of their metrological performance. Since a radiographic calibration is always required to provide an initial absolute geometry, this method will be presented as well. The improvements of the XCT geometry correction methods are presented by means of case studies. The methods can be applied individually or in combination and are intended to provide a toolbox for XCT geometry compensation.
Adaptations of animal cells to growth in suspension culture concern in particular viral vaccine production, where very specific aspects of virus-host cell interaction need to be taken into account to achieve high cell specific yields and overall process productivity. So far, the complexity of alterations on the metabolism, enzyme, and proteome level required for adaptation is only poorly understood. In this study, for the first time, we combined several complex analytical approaches with the aim to track cellular changes on different levels and to unravel interconnections and correlations. Therefore, a Madin-Darby canine kidney (MDCK) suspension cell line, adapted earlier to growth in suspension, was cultivated in a 1-L bioreactor. Cell concentrations and cell volumes, extracellular metabolite concentrations, and intracellular enzyme activities were determined. The experimental data set was used as the input for a segregated growth model that was already applied to describe the growth dynamics of the parental adherent cell line. In addition, the cellular proteome was analyzed by liquid chromatography coupled to tandem mass spectrometry using a label-free protein quantification method to unravel altered cellular processes for the suspension and the adherent cell line. Four regulatory mechanisms were identified as a response of the adaptation of adherent MDCK cells to growth in suspension. These regulatory mechanisms were linked to the proteins caveolin, cadherin-1, and pirin. Combining cell, metabolite, enzyme, and protein measurements with mathematical modeling generated a more holistic view on cellular processes involved in the adaptation of an adherent cell line to suspension growth.
Data set of low-field NMR spectra of continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). 1H spectra (43 MHz) were recorded as single scans.
Two different approaches for the generation of artificial neural networks training data for the prediction of reactant concentrations were used: (i) Training data based on combinations of measured pure component spectra and (ii) Training data based on a spectral model.
Synthetic low-field NMR spectra
First 4 columns in MAT-files represent component areas of each reactant within the synthetic mixture spectrum.
Xi (“pure component spectra dataset”)
Xii (“spectral model dataset”)
Experimental low-field NMR spectra from MNDPA-Synthesis
This data set represents low-field NMR-spectra recorded during continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). Reference values from high-field NMR results are included.
Nebivolol (NEB), a β-blocker frequently used to treat cardiovascular diseases, has been widely detected in aquatic environments, and can be degraded under exposure to UV radiation, leading to the formation of certain transformation products (UV-TPs). Thus, the toxic effects of NEB and its UV-TPs on aquatic organisms are of great importance for aquatic ecosystems. In the present study, the degradation pathway of NEB under UV radiation was investigated. Subsequently, zebrafish embryos/larvae were used to assess the median lethal concentration (LC50) of NEB, and to clarify the sub-lethal effects of NEB and its UV-TPs for the first time. It was found that UV radiation could reduce the toxic effects of NEB on the early development of zebrafish. Transcriptomic analysis identified the top 20 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in zebrafish larvae exposed to NEB, most of which were associated with the antioxidant, nervous, and immune systems. The number of differentially expressed genes (DEGs) in the pathways were reduced after UV radiation. Furthermore, the analysis of protein biomarkers, including CAT and GST (antioxidant response), AChE and ACh (neurotoxicity), CRP and LYS (immune response), revealed that NEB exposure reduced the activity of these biomarkers, whereas UV radiation could alleviate the effects. The present study provides initial insights into the mechanisms underlying toxic effects of NEB and the detoxification effects of UV radiation on the early development of zebrafish. It highlights the necessity of considering the toxicity of UV-TPs when evaluating the toxicity of emerging pollutants in aquatic systems.
Thermoresponsive polymer coatings can facilitate cell sheet fabrication under mild conditions by promoting cell adhesion and proliferation at 37 1C. At lower temperatures the detachment of confluent cell sheets is triggered without enzymatic treatment. Thus, confluent cell sheets with intact extracellular matrix for regenerative medicine or tissue engineering applications become available. Herein, we applied the previously identified structural design parameters of functional, thermoresponsive poly(glycidyl ether) brushes on gold to the more application-relevant substrate glass via the self-assembly of a corresponding block copolymer (PGE-AA) with a short surface-reactive, amine-presenting anchor block. Both, physical and covalent immobilization on glass via either multivalent ionic interactions of the anchor block with bare glass or the coupling of the anchor block to a polydopamine (PDA) adhesion layer on glass resulted in stable coatings. Atomic force microscopy revealed a high degree of roughness of covalently attached coatings on the PDA adhesion layer, while physically attached coatings on bare glass were smooth and in the brush-like regime. Cell sheets of primary human dermal fibroblasts detached reliably (86%) and within 20 ± 10 min from physically tethered PGE-AA coatings on glass when prepared under cloud point grafting conditions. The presence of the laterally inhomogeneous PDA adhesion layer, however, hindered the spontaneous temperature-triggered cell detachment from covalently grafted PGE-AA, decreasing both detachment rate and reliability. Despite being only physically attached, self-assembled monolayer brushes of PGE-AA block copolymers on glass are functional and stable thermoresponsive coatings for application in cell sheet fabrication of human fibroblasts as determined by X-ray photoelectron spectroscopy.
A poly(L-lactide) with a trifluoroethyl ester end group and an average degree of polymerization (DP) of 50 was synthesized by ROP of L-lactide initiated with trifluoroethanol. Small-angle X-ray scattering (SAXS) in combination with differential scanning calorimetry (DSC) measurements revealed an average crystal thickness of 13 nm, corresponding to 45 repeat units. This suggests that most crystallites were formed by extended PLA chains, and both flat surfaces were covered by CF3 groups. The crystalline PLAs were annealed at 140 or 160 °C in the presence of two catalysts: tin(II) 2-ethylhexanoate, (SnOct2) or dibutyltin bis(pentafluorophenoxide) (BuSnPhF). The chemical reactions, such as polycondensation and cyclization, proceeded in the solid state and were monitored by matrix-assisted laser desorption/ionization time-offlight (MALDI TOF) mass spectrometry and gel permeation chromatography (GPC) measurements. Under optimal conditions a large fraction of linear chains was transformed into crystallites composed of extended cycles. Additionally, MALDI TOF MS analysis of GPC fractions from samples annealed for 28 or 42 days detected chain elongation of the linear species up to a factor of 20.
For years there have been more and more reports on the presence of drugs in the aquatic environment. Due to the demographic change, the consumption of pharmaceuticals has risen sharply. After taking the drugs, they are partly metabolized in the human body. However, the metabolism is not complete so that both the metabolites and non-metabolized amounts of the parent compounds are excreted. These compounds reach the waste water and afterwards the sewage treatment plants. In sewage treatment plants transformation products can be formed by the oxidative conditions during wastewater treatment processes. The transformation products may have a higher toxicity than the actual environmental pollutants and are often only partly removed during the waste water treatment. Since a lot of these compounds are still unknown, the transformation products are not detected by target analysis used in sewage treatment plants and are often released undetected in the aquatic ecosystems. The released substances may be subject to additional transformation processes in the environment. Pharmaceuticals produced in high amounts can be already detected in the μg/L range in water bodies worldwide.
Metformin and its major transformation product guanylurea are one of the main representatives. Metformin is the drug of choice for treating type 2 diabetes. The drug therapy for diabetes mellitus has increased significantly in recent years. In the year 2015 1500 tons of metformin were prescribed in Germany (for statutory insured persons). Metformin is not metabolized in the human body and is excreted unchanged therefore concentrations between 57 μg/L and 129 μg/L are found in German waste water treatment plants influents.
In this work the transformation of the antidiabetic drug metformin is investigated. The degradation of metformin is initialize by commercial water treatment techniques like UV-radiation or noncommercial techniques like heterogenous photocatalysis based on titanium dioxide. The degradation of metformin and resulting transformation products are analyzed by LC-MS/MS and LC-HRMS.
The formation of transformation products (TPs) from contaminants and residues is becoming an increasing focus of scientific community. All organic compounds can form different TPs, thus demonstrating the complexity and interdisciplinarity of this topic. The properties of TPs could stand in relation to the unchanged substance or be more harmful and persistent. To get important information about the generated TPs, methods are needed to simulate natural and manmade transformation processes. Current tools are based on metabolism studies, photochemical methods, electrochemical methods, and Fenton's reagent. Finally, most transformation processes are based on redox reactions. This review aims to compare these methods for structurally different compounds. The groups of pesticides, pharmaceuticals, brominated flame retardants, and mycotoxins were selected as important residues/contaminants relating to their worldwide occurrence and impact to health, food, and environmental safety issues. Thus, there is an increasing need for investigation of transformation processes and identification of TPs by fast and reliable methods.
The knowledge about energy release and transient behaviour of flash lamps, used as short-term energy source in flash thermography investigations, is essential for a quantitative analysis of the results as well as for simulations regarding such experiments. Usually, only a rectangular pulse shape of a typical duration of a few milliseconds is regarded when flash lamps pulses are described. This note considers the afterglow period of a flash lamp explicitly and shows that negligence of this afterglow effect leads to a systematic underestimation of the pulse length and the related total energy release. In the reported case, the intensity transient recorded by a Silicon photo diode was transformed into a temperature transient, allowing the study of the real energy release. It turns out that approximately only 50% of the entire pulse energy were released during the usually regarded period of 2.8 ms, while the other half was released within a period of 20 ms with an exponential decay.
Explosive spalling is caused by, among others, the thermohydraulic spalling mechanism. During this process, vaporization, dehydration, moisture-transport and condensation processes interact. As a result, a drying and dehydration zone as well as a saturated zone, known as a moisture clog, are observed inside the unilaterally-heated concrete. The presented research is focused on the experimental investigation of the underlying thermohydraulic processes.
To investigate these, a test methodology based on X-ray computed tomography (CT) and nuclear magnetic resonance (NMR) was developed. Thereby, the X-ray CT scans are carried out simultaneously during the application of a defined unilateral-heating regime on a specially-constructed specimen. This miniaturized specimen, equipped with a double-layer casing, reproduces the condition within a planar, unilaterally-heated building component.
A preliminary test methodology and the first experimental results were presented at the 5th International Workshop on Concrete Spalling in Borås, Sweden (2017). The contribution for the upcoming workshop presents an improved version of this test methodology and new results for a high-performance concrete (HPC) mixture exposed to temperatures up to 500 °C. Regarding the CT measurements, a higher time-resolution of 15 min was achieved and a quantification of the moisture changes was implemented. Due to an increase in signal quality of the NMR measurements, a pore-size specific moisture distribution can now be resolved. This allows to conclude about the moisture reconfiguration between small gel pores and larger interhydrate pores. Additionally, the NMR measurement are no longer limited to first 2.5 cm below the heated surface but a one-dimensional moisture distribution can now be estimated over the whole 10 cm long specimen.
The presented results demonstrate that the combination of X-ray CT and NMR measurements enables to image and quantify the thermally-induced moisture transport and reconfiguration from small gel pores up to macro pores. This provides important insights into the thermohydraulic damage mechanism and leads to a better understanding of spalling avoidance strategies, like the addition of polypropylene fibres.
For more than 110 years, BAM has been producing reference materials for a wide range of application fields. With the development of new analytical methods and new applications as well as continuously emerging more stringent requirements of laboratory accreditation with regard to quality control and metrological traceability, the demand and requirements for reference materials are increasing. This trend article gives an overview of general developments in the field of reference materials as well as developments in selected fields of application in which BAM is active. This includes inorganic and metal analysis, gas analysis, food and consumer products, and geological samples. In addition to these more traditional fields of application, developments in the areas of optical spectroscopy, particulary fluorescence methods, and nanomaterials are considered.
Trinamic TMCL IOC is a Python package designed for controlling stepper motors connected to a Trinamic board using the TMCL language (all boards supported by PyTrinamic should now work, has been tested on the TMCM 6110 and the TMCM 6214). Since it is implementing the TMCL protocol, it should be easy to adapt to other Trinamic motor controller boards. This package assumes the motor controller is connected over a machine network via a network-to-serial converter, but the underlying PyTrinamic package allows for other connections too.
This allows the control of attached motors via the EPICS Channel-Access virtual communications bus. If EPICS is not desired, plain Pythonic control via motion_control should also be possible. An example for this will be provided in the example.ipynb Jupyter notebook.
This package leverages Caproto for EPICS IOCs and a modified PyTrinamic library for the motor board control, and interfaces between the two via an internal set of dataclasses. Configuration for the motors and boards are loaded from YAML files (see tests/testdata/example_config.yaml).
The modifications to PyTrinamic involved extending their library with a socket interface. This was a minor modification that should eventually find its way into the official package (a pull request has been submitted).
In most chemical reactions, stable isotopes are fractionated in a mass-dependent manner, yielding correlated isotope ratios in elements with three or more stable isotopes. The proportionality between isotope ratios is set by the triple isotope fractionation exponent θ that can be determined precisely for, e.g., sulfur and oxygen by IRMS, but not for metal(loid) elements due to the lower precision of MC-ICP-MS analysis and smaller isotopic variations. Here, using Mg as a test case, we compute a complete metrologically robust uncertainty budget for apparent θ values and, with reference to this, present a new measurement Approach that reduces uncertainty on θ values by 30%. This approach, namely, direct educt-product bracketing (sample−sample bracketing), allows apparent θ values of metal(loid) isotopes to be determined precisely enough to distinguish slopes in three-isotope space. For the example of Mg, we assess appropriate quality Control standards for interference-to-signal ratios and Report apparent θ values of carbonate−seawater pairs. We determined apparent θ values for marine biogenic carbonates, where the foraminifera Globorotalia menardii yields 0.514 ± 0.005 (2 SD), the coral Porites, 0.515 ± 0.006 (2 SD), and two specimens of the giant clam Tridacna gigas, 0.508 ± 0.007 (2 SD) and 0.509 ± 0.006 (2 SD), documenting differences in the uptake pathway of Mg among marine calcifiers. The capability to measure apparent θ values more precisely adds a new dimension to metal(loid) δ values, with the potential to allow us to resolve different modes of fractionation in industrial and natural processes.
Designing the shape and size of catalyst particles, and their interfacial charge, at the nanometer scale can radically change their performance. We demonstrate this with ceria nanoparticles. In aqueous media, nanoceria is a functional mimic of haloperoxidases, a group of enzymes that oxidize organic substrates, or of peroxidases that can degrade reactive oxygen species (ROS) such as H2O2 by oxidizing an organic substrate. We show that the chemical activity of CeO2−x nanoparticles in haloperoxidase- and peroxidaselike reactions scales with their active surface area, their surface charge, given by the ζ-potential, and their surface defects (via the Ce3+/Ce4+ ratio). Haloperoxidase-like reactions are controlled through the ζ-potential as they involve the adsorption of charged halide anions to the CeO2 surface, whereas peroxidase-like reactions without charged substrates are controlled through the specific surface area SBET. Mesoporous CeO2−x particles, with large surface areas, were prepared via template-free hydrothermal reactions and characterized by small-angle X-ray scattering. Surface area, ζ-potential and the Ce3+/Ce4+ ratio are controlled in a simple and predictable manner by the synthesis time of the hydrothermal reaction as demonstrated by X-ray photoelectron spectroscopy, sorption and ζ-potential measurements. The surface area increased with synthesis time, whilst the Ce3+/Ce4+ ratio scales inversely with decreasing ζ-potential. In this way the catalytic activity of mesoporous CeO2−x particles could be tailored selectively for haloperoxidase- and peroxidase-like reactions. The ease of tuning the surface properties of mesoporous CeO2x particles by varying the synthesis time makes the synthesis a powerful general tool for the preparation of nanocatalysts according to individual needs.
Mechanochemistry has become a valuable method for the synthesis of new materials and molecules, with a particular strength for screening and preparing multicomponent crystals. In this work, two novel cocrystals of pyrazinamide (PZA) with pimelic acid (PA) were prepared mechanochemically. Their formation was monitored in real time by in situ synchrotron powder X-ray diffraction. Control over the polymorphic form was obtained through the selective choice of liquid additive via liquid assisted grinding. Slurry experiments and dispersion-corrected density functional theory calculations suggest that Form I is the thermodynamically stable form under ambient conditions. Upon aging, Form II converts to Form I. The stability of Form II upon aging was found to depend strongly on the milling duration, intensity, and material of the milling vessels. Longer or higher energy milling drastically increased the lifetime of the Form II product. For the first time, this work also demonstrates that the choice of milling jar can have a decisive effect on the aging stability of a bulk polymorphic powder. In contrast to material prepared in steel milling vessels, the preparation of Form II in Perspex (PMMA) vessels increased its lifetime 3-fold. These findings offer a new dimension to garnering control over mechanochemical cocrystallization and demonstrate the critical importance of the careful and timely ex situ screening of ball mill grinding reactions. This will be of importance for potential industrial applications of mechanochemical cocrystallization where understanding polymorph longevity is crucial for the development of a robust preparative protocol.
Analysis of microplastic particles (MP) in environmental samples needs sophisticated techniques and is time intensive due to sample preparation and detection. An alternative to the most common (micro ) spectroscopic techniques, FTIR or Raman spectroscopy, are the thermoanalytical methods, where specific decomposition products can be analyzed as marker compounds for different kind of plastics types and mass contents. Thermal extraction desorption gas chromatography mass spectrometry (TED-GC-MS) allows the fast identification and quantification of MP in environmental samples without sample preparation. Whereas up to now only the analysis of thermoplastic polymers was realized, this is the first time that even the analysis of tire wear (TW) content in environmental samples is possible. Various marker compounds for TW were identified. They include characteristic decomposition products of elastomers, antioxidants and vulcanization agents. Advantages and drawbacks of these marker substances were evaluated. Environmental samples from street run off were exemplarily investigated and presented.
The Stone Age site Riņņukalns, Latvia, is the only well-stratified shell midden in the Eastern Baltic. In this paper, we present new interdisciplinary results concerning its dating, stratigraphy, features, and finds to shed light on the daily life of a fisher population prior to the introduction of domesticated animals. The undisturbed part of the midden consists of alternating layers of unburnt mussel shell, burnt mussel shell and fish bone, containing artefacts, some mammal and bird bones, and human burials. Two of them, an adult man and a baby, are discovered recently and date to the calibration plateau between 3350 and 3100 cal BC, and to the later 4th millennium, respectively. Stable isotopes suggest a diet based heavily on freshwater fish, and this is supported not only by ten thousands of identified fish remains, but also by a fish bone concentration nearby the skull of the man, which is interpreted as remain of a grave gift (possible fish soup). Of special interest are the baby’s stable isotope values. It shows that the mother’s diet was atypical (perhaps because she was non-local), and/or that dietary stress during pregnancy increased fractionation between the mother’s diet and her bloodstream
Two new approaches towards an emission reference material for use in quality assurance measures for materials emissions testing were developed and intensively tested. The overall goal was to obtain solid materials with homogenous and reproducible (S)VOC release. Since the application in inter-laboratory comparisons is aimed at, it should furthermore be long-term stable to ensure safe shipment to the customer without sustaining compound losses. In the first approach, thermoplastic polyurethane (TPU) was impregnated with the VOC texanol under high-pressure with liquid CO2 as solvent. In the second, styrene (VOC) and the SVOC 2,6-diisopropylnaphthalene (DIPN) were spiked into vacuum grease (VG) and a mixture of paraf-fin/squalane (P/S). For the prediction of the emission rates a finite element model (FEM) was developed for the VG and P/S type materials. All requirements for reference materials were fulfilled, whereas the TPU samples need to be aged for about 10 days until repeatable and re-producible emission rates were obtained.
Two new approaches towards an emission reference material for use in quality assurance measures for materials emissions testing were developed and intensively tested. The overall goal was to obtain solid materials with homogenous and reproducible (S)VOC release. Since the application in inter-laboratory comparisons is aimed at, it should furthermore be long-term stable to ensure safe shipment to the customer without sustaining compound losses. In the first approach, thermoplastic polyurethane (TPU) was impregnated with the VOC texanol under high-pressure with liquid CO2 as solvent. In the second, styrene (VOC) and the SVOC 2,6-diisopropylnaphthalene (DIPN) were spiked into vacuum grease (VG) and a mixture of paraf-fin/squalane (P/S). For the prediction of the emission rates a finite element model (FEM) was developed for the VG and P/S type materials. All requirements for reference materials were fulfilled, whereas the TPU samples need to be aged for about 10 days until repeatable and reproducible emission rates were obtained.
Structured illumination using high-power diode lasers generates a two-dimensional interference of thermal waves. In addition, the sources and the sample are moving relative to each other. Using different configurations, we investigate the validity of the temporal and spatial superposition principle of the heat diffusion equation for these cases both experimentally and by numerical-analytical modelling. Furthermore, we investigate the potential of this approach for non-destructive testing.