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Material defects in fiber reinforced polymers such as delaminations can rapidly degrade the material properties or can lead to the failure of a component. Pulse thermography (PT) has proven to be a valuable tool to identify and quantify such defects in opaque materials. However, quantification of delaminations within semitransparent materials is extremely challenging. We present an approach to quantify delaminations within materials being semitransparent within the wavelength ranges of the optical excitation sources as well as of the infrared (IR) camera. PT experimental data of a glass fiber reinforced polymer with a real delamination within the material were reconstructed by one dimensional (1D) mathematical models. These models describe the heat diffusion within the material and consider semitransparency to the excitation source as well to the IR camera, thermal losses at the samples surfaces and a thermal contact resistance between the two layers describing the delamination. By fitting the models to the PT data, we were able to determine the depth of the delamination very accurately. Additionally, we analyzed synthetic PT data from a 2D simulation with our 1D-models to show how the thermal contact resistance is influenced by lateral heat flow within the material.
Whereas human factors (HF) in the non-destructive testing (NDT) of metallic components are a poorly investigated topic (in comparison to other industrial fields such as aviation), HF in the inspection of concrete components are even less known. Studies have shown that there is always some variability between individuals in their inspection results and that HF affect the reliability of NDT inspections. The aim of the ongoing WIPANO project is to draft a standard for a holistic reliability assessment, with concrete inspection as one case study. This includes also the HF. A human-oriented Failure Modes and Effects Analysis (FMEA) was carried out to do the following: a) identify possible human-related risks in tunnel inspection processes using a laser scan method (including data collection,evaluation, and assessment of tunnel damage) and b) evaluate these human-related risks as regards their possible causes, consequences and probability of occurrence – in addition with respect to existing and possible preventive measures. The results show that the causes for possible failures can lie within people, the physical environment, technology, organisation, and extra-organisational environment. Whereas current preventive measures rely mostly on the individual and quality management practices, there is potential for even larger improvement at the organisational and extra-organisational level. The FMEA results were also used to develop a quantification method to further understand the HF in tunnel inspection, which could possibly be included in the information into the overall reliability assessment. The usage of qualitative and quantitative data collected through the human-FMEA within the proposed quantification method shows promise that HF can be quantified and could offer broader understanding of HF influences on inspection in various industries.
Whereas human factors (HF) in the non-destructive testing (NDT) of metallic components are a poorly investigated topic (in comparison to other industrial fields such as aviation), HF in the inspection of concrete components are even less known. Studies have shown that there is always some variability between individuals in their inspection results and that HF affect the reliability of NDT inspections. The aim of the ongoing WIPANO project is to draft a standard for a holistic reliability assessment, with concrete inspection as one case study. This includes also the HF. A human-oriented Failure Modes and Effects Analysis (FMEA) was carried out to do the following: a) identify possible human-related risks in tunnel inspection processes using a laser scan method (including data collection,evaluation, and assessment of tunnel damage) and b) evaluate these human-related risks as regards their possible causes, consequences and probability of occurrence – in addition with respect to existing and possible preventive measures. The results show that the causes for possible failures can lie within people, the physical environment, technology, organisation, and extra-organisational environment. Whereas current preventive measures rely mostly on the individual and quality management practices, there is potential for even larger improvement at the organisational and extra-organisational level. The FMEA results were also used to develop a quantification method to further understand the HF in tunnel inspection, which could possibly be included in the information into the overall reliability assessment. The usage of qualitative and quantitative data collected through the human-FMEA within the proposed quantification method shows promise that HF can be quantified and could offer broader understanding of HF influences on inspection in various industries
Polymeric nanoparticles (NP) are of increasing importance for a wide range of applications in the material and life sciences, including their use as drug carriers, fluorescent sensors and multimodal reporters in a large variety of bioassays and bioimaging studies. Application-relevant properties of NP include their size (and size distribution), shape, optical properties, and ease of subsequent functionalization, e.g. with linkers, sensor molecules, and bioligands. In this respect, knowledge of the chemical nature, the total number of surface groups and the number of groups accessible for subsequent coupling reactions is mandatory.1 Commercially available polystyrene NP often contain different additives like stabilizers, radical starters and crosslinkers, which can influence the quantification of surface functionalities. Moreover, they often have unknown surface group densities that may vary from batch to batch, which complicates or even hampers their reliable use in many (bio)applications. To circumvent these issues, we synthesized amino- and carboxy-functionalized, monodisperse 100 nm polystyrene NP with three different, well-defined surface group densities. Using a recently developed approach for the quantification of functional groups on nano- and microparticles with cleavable reporters,2 we quantified the assessible functional groups on the self-synthesised PS particles via optical spectroscopy (photometry) and inductively coupled optical emission spectrometry (32S ICP-OES). In addition, we developed a fluorimetric approach for the quantification of surface functional groups on nanoparticles based on the labelling with luminescent lanthanide complexes (LLC). In contrast to common organic dyes, LLC are not prone to photo¬luminescence quenching arising from reabsorption or dye aggregation, and thus, enable a reliable fluorometric quantification of the assessible functional groups on NP surfaces. Moreover, lanthanide tags can be detected with high specificity and sensitivity with analytical techniques such as XPS and ICP-MS, which allow for the multimodal validation of the fluorometric quantification approach.
Human factors (HF) are little understood, and particularly in non-destructive testing (NDT) experimental data is rare, samples are often small, and statistical methods are rarely used to evaluate results. HF have been widely implicated in major occurrences of technical failure, for example at North Anna Power Plant and on United Airlines Flight 232. Understanding HF is vital for reliable detection and prevention of failures. Reliability assessments, though known to be affected by intrinsic capability, application factors, and HF, have thus far only concentrated to a sufficient degree on intrinsic capability. The addition of HF to that assessment has proven difficult due to the lack of a method of quantifying HF. This paper presents the first attempt from a psychological perspective to quantify HF from qualitative data.
HF data was derived from qualitative human-oriented Failure Modes and Effects Analysis (Human-FMEA) workshops for visual inspection of tunnels by laser scanning and for ultrasonic testing of welds. Data was collected on human failure modes, causes, consequences and preventive measures, as well as eliciting a risk priority number (RPN). Using this data, a system of quantitative weightings was created to allocate errors to inductively derived HF categories for further allocation to existing HF categorisation models.
This weighting model proved useful for creating quantitative summaries of HF, informing and validating qualitative FMEA results, and comparing existing HF categorisation models. Further potential lies within a planned interface to quantitative reliability assessment methods such as POD (Probability of Detection). While providing quantifications, the method retains a qualitative and holistic nature, can, thus, bridge the gap between psychological and engineering concerns of HF and reliability, contributing to future interdisciplinary work.
The overall interest in nanotoxicity, triggered by the increasing use of nanomaterials in the material and life sciences, and the synthesis of an ever increasing number of new functional nanoparticles calls for standardized test procedures and for efficient approaches to screen the potential genotoxicity of these materials. Aiming at the development of fast and easy to use, automated microscopic methods for the determination of the genotoxicity of different types of nanoparticles, we assess the potential of the fluorometric γH2AX assay for this purpose. This assay, which can be run on an automated microscopic detection system, relies on the detection of DNA double strand breaks (DSB) as a sign for genotoxicity. Here, we provide first results obtained with broadly used nanomaterials like CdSe/CdS and InP/ZnS quantum dots as well as iron oxide, gold, and polymer particles of different surface chemistry with previously tested colloidal stability and different cell lines like Hep-2 and 8E11 cells, which reveal a dependence of the genotoxicity on the chemical composition as well as the surface chemistry of these nanomaterials. These studies will be also used to establish nanomaterials as positive and negative genotoxicity controls or standards for assay performance validation for users of this fluorometric genotoxicity assay. In the future, after proper validation, this microscopic platform technology will be expanded to other typical toxicity assays.
Risk assessment of nanomaterials requires not only standardized toxicity studies but also validated methods for nanomaterial surface characterization with known uncertainties. In this context, a first bilateral interlaboratory comparison on Surface group quantification of nanomaterials is presented that assesses different reporter-free and labeling methods for the quantification of the total and accessible number of amine functionalities on commercially available silica nanoparticles that are widely used in the life sciences. The overall goal of this comparison is the identification of optimum methods as well as achievable measurement uncertainties and the comparability of the results across laboratories. We also examined the robustness and ease of implementation of the applied analytical methods and discussed method-inherent limitations. In summary, this comparison presents a first step toward the eventually required standardization of methods for surface group quantification.
Inductively coupled plasma mass spectrometry (ICP-MS) is a powerful method for the matrix-independent quantitative analysis of target elements. Developed for the use in inorganic trace analysis, ICP-MS is nowadays a valuable tool for bioanalytical questions. Especially the use of ICP-MS for quantitative proteomics by measuring heteroatoms has gained recognition in the last decade, considering that established quantification methods like organic mass spectrometry depend on labelling of the target protein or the existence of matched protein and peptide standards. The need for reliable quantification of proteins is continuously growing, but only a limited number of well-characterized and quantified protein standards are available so far. Accurately quantified, traceable protein standards are necessary to ensure comparability of measurements between laboratories, not only in basic research but also in a clinical context. One example of this is the Alzheimer’s disease biomarker tau protein. However, existing tau standards lack comparability, emphasizing the need for a well-quantified protein standard.
Therefore, we developed a method for the quantification of pure proteins via sulfur isotope dilution ICP-MS (IDMS). As sulfur is present in two amino acids, cysteine and methionine, it exists in nearly all proteins and can be used for the quantification of proteins of known stoichiometry. We employed simple offline strategies for the separation of non-protein bound sulfur species. Quantification of these contaminations by IDMS allows for correction of the protein content and enables reliable protein quantification. We report the protein mass fractions of a standard reference material and commercially available proteins determined by sulfur IDMS, including the expanded uncertainties. The developed method can be applied for the reliable and traceable quantification of pure proteins for use as in-house standards. Here, we successfully used this method for the quantification of the tau protein.
Inductively coupled plasma mass spectrometry (ICP-MS) is a powerful method for the matrix-independent quantitative analysis of target elements. Developed for the use in inorganic trace analysis, ICP-MS is nowadays emerging as a valuable tool for bioanalytical questions. Especially the use of ICP-MS for quantitative proteomics by measuring heteroatoms has gained popularity in the last decade, considering that established quantification methods like organic mass spectrometry depend on the existence of matched protein and peptide standards or labelling of the target protein. The need for reliable quantification of proteins is constantly growing, but only a limited number of well characterized and quantified protein standards are available so far. Not only in basic research, but also in a clinical context, accurately quantified, traceable protein standards are needed to ensure comparability of measurements between laboratories. One disease with a major impact on our ageing society is Alzheimer’s disease (AD), which is still challenging to diagnose. As this is also due to a lack in comparability and accuracy of existing biomarker assays, the community would greatly benefit from well quantified protein biomarker standards.
In this work, we applied isotope dilution analysis (IDA) using ICP-MS to quantify proteins of known stoichiometry via their sulfur content. Sulfur is present in two amino acids, cysteine and methionine, and hence exists in nearly all proteins. Simple strategies were employed for the detection of low molecular sulfur species to correct for sulfur contaminants and allow for reliable quantification of various proteins. We report the protein mass fractions with expanded uncertainties of a standard reference material and commercially available proteins determined by sulfur IDA. The herein developed method can be applied for the reliable and traceable quantification of pure proteins and will be used for the quantification of an AD biomarker. Our target is the tau protein, as brain load and distribution of tau is highly correlated with the clinical progression of AD.
LA-ICP-MS is increasingly used for single cell analysis in two different detection modes using either the imaging mode with subcellular resolution or alternatively single spot analysis of cells with a larger laser spot size. This study compares the analytical figures of merit of both detection modes (signal to noise, precision, accuracy, throughput), as well as ease of operation and data evaluation. Adherent 3T3 fibroblast cells were stained with two metal dyes (mDOTA-Ho, Ir-DNA-intercalator) and several dozen cells were measured using both modes. We found a ten times higher throughput for single spot analysis, which has as well a straightforward data analysis, shortening the total analysis time further. The signal to noise ratio for single spot analysis was found to be slightly better compared to the signal to noise of pixels in imaging. The mean metal intensity per single cell differed by only 10% between both modes and obtained distributions were found to show no statistically significant differences. Using matrix matched calibration based on standards spotted onto nitrocellulose membrane, we achieved detection limits (10s) of 12 fg for Ir and 30 fg for Ho and quantified 57 +/-35 fg Ir and 1192 +/- 707 fg Ho per single cell.
Compared to a conventional ICP-MS measurement of a digest of about 60000 cells, 54% of Ir content and 358% Ho content was found using quantitative LA-ICP-MS. The difference might be a consequence of the two metal dyes binding to different structures of the cell and therefore might behave differently in sample preparation for conventional and LA-ICP-MS.