Analytische Chemie
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Under the auspices of the Protein Analysis Working Group (PAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) a pilot study, CCQM-P216, was coordinated by the Chinese National Institute of Metrology (NIM), National Research Council of Canada (NRC) and the Bureau International des Poids et Mesures (BIPM). Eleven Metrology Institutes or Designated Institutes and the BIPM participated in the first phase of the pilot study (Part 1). The purpose of this pilot study was to develop measurement capabilities for larger proteins using a recombinant humanized IgG monoclonal antibody against Spike glycoprotein of SARS-CoV-2 (Anti-S IgG mAb) in solution. The first phase of the study was designed to employ established methods that had been previously studies by the CCQM Protein Analysis Working Group, involving the digestion of protein down to the peptide or amino acid level. The global coronavirus pandemic has also led to increased focus on antibody quantitation methods. IgG are among the immunoglobulins produced by the immune system to provide protection against SARS-CoV-2. Anti-SARS-CoV-2 IgG can therefore be detected in samples from affected patients. Antibody tests can show whether a person has been exposed to the SARS-CoV-2, and whether or not they potentially show lasting immunity to the disease. With the constant spread of the virus and the high pressure of re-opening economies, antibody testing plays a critical role in the fight against COVID-19 by helping healthcare professionals to identify individuals who have developed an immune response, either via vaccination or exposure to the virus. Many countries have launched large-scale antibody testing for COVID-19. The development of measurement standards for the antibody detection of SARS-CoV-2 is critically important to deal with the challenges of the COVID-19 pandemic. In this study, the SARS-CoV-2 monoclonal antibody is being used as a model system to build capacity in methods that can be used in antibody quantification. Amino acid reference values with corresponding expanded uncertainty of 36.10 ± 1.55 mg/kg, 38.75 ± 1.45 mg/kg, 18.46 ± 0.78 mg/kg, 16.20 ± 0.67 mg/kg and 30.61 ± 1.30 mg/kg have been established for leucine, valine, phenylalanine, isoleucine and proline, respectively. Agreement between nearly all laboratories was achieved for the amino acid analysis within 2 to 2.5 %, with one participant achieving markedly higher results due to a technical issue found in their procedure; this result was thus excluded from the reference value calculations. The relatively good agreement within a laboratory between different amino acids was not dissimilar to previous results for peptides or small proteins, indicating that factors such as hydrolysis conditions and calibration procedures could be the largest sources of variability. Peptide reference values with corresponding expanded uncertainty of 4.99 ± 0.28 mg/kg and 6.83 ± 0.65 mg/kg have been established for ALPAPIEK and GPSVFPLAPSSK, respectively. Not surprisingly due to prior knowledge from previous studies on peptide quantitation, agreement between laboratories for the peptide-based analysis was slightly poorer at 3 to 5 %, with one laboratory's result excluded for the peptide GPSVFPLAPSSK. Again, this level of agreement was not significantly poorer than that achieved in previous studies with smaller or less complex proteins. To reach the main text of this paper, click on Final Report.
Mit der Bezeichnung Hinterglasmalerei wird allgemein der Begriff der Glasmalerei assoziiert. Auch wenn in beiden Fällen Glas das Trägermaterial ist, bezeichnet Hinterglasmalerei jedoch eine völlig andere Technik. Während bei der Glasmalerei die Farben auf den Bildträger eingebrannt werden, handelt es sich bei der Hinterglasmalerei um eine Kaltmalerei. Selbsttrocknende Farben werden auf die Rückseite der Glastafel aufgetragen, zuweilen wird die Malweise durch aufwendige Veredelungstechniken ergänzt. Mehr und mehr rückt diese Technik, die materialtechnologisch zwischen Tafelmalerei und Glasmalerei zu verorten ist, in den Blickwinkel einer interessierten Öffentlichkeit, wie dies eine zunehmende Anzahl verschiedener Ausstellungen zur Hinterglasmalerei belegen. Die vorliegende Publikation beschäftigt sich in erster Linie mit kunsttechnologischen und materialanalytischen Aspekten der Hinterglasmalerei und ermöglicht tiefe Einblicke in die künstlerische Arbeitsweise und in die Verwendung unterschiedlichster Materialien.
Optical Stability Studies of Hexagonal Upconverting Nanocrystals and Development of Monitoring Tools
(2021)
We demonstrate the potential of time-resolved luminesence spectroscopy for the straightforward assessment and in situ monitoring of the stabilty of UCNPs. Different analytical methods were used to assess the dissolution behaviour of UCNPs in varuous media. Potentiometric and optical data were correlated to develop a new non-invasive monitoring tool for particle dissolution
Assessing dissolution of upconverting nanoparticles by TEM, EDXS, potentiometry and fluorometry
(2021)
Inorganic lanthanide-doped upconversion nanoparticles (UCNP) constitute an emerging class of near-infrared (NIR)-excitable luminescent reporters for bioimaging, fluorescence assays, sensors in bioanalysis, and optical thermometry as well as phosphors for photovoltaic and security applications.1 However, the use of UCNPs in bioimaging and cellular studies requires biocompatible particles. One possible cause of UCNP toxicity is the release of potentially harmful fluoride fluoride and lanthanide ions as revealed by dilution studies in aqueous environments, particularly under high dilution conditions.2-5 To address this issue, suitable surface coatings preventing such effects in combination with fast screening methods suited for online in situ analysis are desired.
Here we present a systematic study of differently sized β-NaYF4:Yb,Er nanocrystals stabilized with different surface coatings and different hydrophilic ligands varying in binding strength to the surface atoms in various aqueous environments at different temperatures.
Time resolved in situ monitoring of mechanochemical transformations by X-ray spectroscopy (XAS)
(2021)
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
Time resolved in situ monitoring of mechanochemical transformations by X-ray spectroscopy (XAS)
(2021)
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
Understanding on how a machine learning model interprets data is a crucial step to verify its reliability and avoid overfitting. While the focus of the scientific community is nowadays orientated towards deep learning approaches, which are considered as black box approaches, this work presents a toolbox that is based on complementary methods of feature extraction and selection, where the classification decisions of the model are transparent and can be physically interpreted. On the example of guided wave benchmark data from the open guided waves platform, where delamination defects were simulated at multiple positions on a carbon fiber reinforced plastic plate under varying temperature conditions, the authors could identify suitable frequencies for further investigations and experiments. Furthermore, the authors presented a realistic validation scenario which ensures that the machine learning model learns global damage characteristics rather than position specific characteristics.
Due to the ageing of the infrastructure facilities, a reliable assessment of the condition of concrete structures is of great interest to plan timely and appropriate measures. In concrete structures, pittingcorrosion of the reinforcement is the predominant deterioration mechanism affecting serviceability and eventually structural performance. Determination of quantitative chloride ingress is not only necessary to obtain valuable information on the current condition of a structure, but the data obtained can also be used to predict future developments and the associated risks. An overview of the progress and the possibilities of the application of laser-induced breakdown spectroscopy for concrete analysis in daily civil engineering practice is given. High-resolution 2D measurements of drill cores to determine the penetration of harmful species into concrete is presented. Furthermore, the application of a mobile LIBS system in a parking garage is shown. The system consists of a diode-pumped low-energy laser (3 mJ, 1.5 ns, 100 Hz) and a compact NIR spectrometer. A scanner allows two-dimensional element mapping. Progress towards the establishment of LIBS in a leaflet for the analysis of chlorine ingress into concrete in civil engineering is presented.
Understanding on how a machine learning model interprets data is a crucial step to verify its reliability and avoid overfitting. While the focus of the scientific community is nowadays orientated towards deep learning approaches, which are considered as black box approaches, this work presents a toolbox that is based on complementary methods of feature extraction and selection, where the classification decisions of the model are transparent and can be physically interpreted. On the example of guided wave benchmark data from the open guided waves platform, where delamination defects were simulated at multiple positions on a carbon fiber reinforced plastic plate under varying temperature conditions, the authors could identify suitable frequencies for further investigations and experiments. Furthermore, the authors presented a realistic validation scenario which ensures that the machine learning model learns global damage characteristics rather than position specific characteristics.