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Electron microscopy applied in different operating modes, e.g., SEM, TEM or STEM-in-SEM, is the gold standard method to investigate the exact size and shape of individual nanoparticles. However, when fine nanoparticles with a non-monodisperse size distribution and non-spherical shapes are analysed, achieving an accurate result is challenging. Deviations in size measurements of more than 10% may occur. Understanding of the contrasts and sensitivities characteristic to the individual operating modes of an electron microscope is key in interpreting and evaluating quantitatively the measurement uncertainties needed for an eventual certification of specific nanoparticles via traceable results. Further, beyond the pure measurement, the other components in the analysis workflow with significant impact on the overall measurement uncertainties are the sample preparation and the image segmentation. In the present study the same areas of selected iron oxide fine nanoparticles (<25 nm) as reference nanomaterial (candidate) prepared on substrate for electron microscopy imaging are analysed correlatively with SEM, STEM-in-SEM and TEM with respect to their size and shape distribution. Individual significant measurement uncertainties are discussed, e.g., the sensitivity of secondary electron detectors of InLens-type to the surface morphology, particularly to the presence of an ultrathin organic coating or signal saturation effects on the particle edges, to electron beam exposure, to surface contamination, or the selection of the threshold for image segmentation. Another goal of this study is to establish a basis of analysis conditions which shall guarantee accurate results when both manual and particularly (semi-)automated segmentation approaches are applied. Advantages as well as limitations of the use of different electron microscopy operating modes, applied individually and correlatively, are highlighted.
Society is currently confronted with two global challenges, climate change and sustainable development. This reality reverberates amongst the leading nations of the world and is articulated as a priority by the United Nations through the Framework Convention on Climate Change and its seventeen Sustainable Development Goals. In 2016, under the Paris Accord, Mission Innovation, MI, emerged as a global response to climate change and developed eight innovation challenges to mitigate its effect, including Clean Energy Materials, IC6. This innovation challenge focused its efforts on accelerating the development and deployment of clean energy materials by more than a factor of ten through Materials Acceleration Platforms, MAPs – autonomous, self-driving materials laboratories and renewed itself under the current mandate as Materials for Energy, M4E.
Self-driving labs deploy artificial intelligence, robotic automation and high-performance simulation and modeling in a closed loop system of material synthesis and characterization. An international ecosystem for accelerated materials discovery has been established and finds applications in many enabling materials technologies, including nanomaterials. The importance of nanomaterials to catalysis for hydrogen production and carbon dioxide conversion as well as energy storage in batteries is well known. In this work, the international efforts under Materials for Energy will be elaborated including the development of MINERVA - MAP for Intelligent Nanomaterial synthesis Enabled by Robotics for Versatile Applications. MINERVA was specifically built to include the specialized equipment required for the synthesis, characterization and closed-loop optimization of various nano- and advanced materials, ranging from simple inorganic (silica, metal, metal oxide) or polymeric nanoparticles to more complex core-shell architectures and materials with well-defined porosity or surface chemistry. Currently, we are investigating materials for applications in antimicrobial and antibiofouling surface coatings, sensor materials, as well as the reproducible synthesis of reference materials with this platform.
Material Acceleration Platforms (MAPs) represent a transformative approach to the development of resilient and sustainable technology value chains. These platforms can identify candidate chemistries and structures via simulations, and database searches and leverage machine learning-based rapid screening to accelerate the discovery and deployment of novel materials, thereby addressing critical challenges in modern technology sectors.
Incorporating high-fidelity advanced characterization in the early phases of material development is crucial for early de-risking. Advanced characterization techniques, such as X-ray diffraction, advanced electrochemical and spectroscopic techniques provide comprehensive insights into the structural, chemical, and physical properties of materials. Long-term testing further contributes to the de-risking process by evaluating the durability and stability of materials under various environmental and operational conditions. Early identification of potential degradation mechanisms enables the refinement of material compositions and processing methods, ultimately leading to the development of more resilient materials.
Early upscaling attempts are integral to assessing the feasibility of material leads generated through machine learning-based rapid screening to evaluate the scalability of synthesis and processing techniques. This step is critical for identifying potential challenges in manufacturing, such as issues related to reproducibility, yield, and cost-effectiveness. Process design has to be a major part of the MAP-based material design to cope with the increasing share of secondary raw materials in supply chains.
This presentation will briefly summarize possible strategies to address these issues and provide deep-dives on best practices. As the demand for advanced materials continues to grow, MAPs will play an increasingly vital role in driving technological advancements and addressing global challenges.
In this work, the electrochemical behavior of 4-phenylurazole (Ph-Ur) was studied and the latter was used as a molecular anchor for the electrochemical bioconjugation of tyrosine (Y). Cyclic voltammetry (CV) and controlled potential coulometry (CPC) allowed the in-situ generation of the PTAD (4-phenyl-3 H-1,2,4-triazole-3,5(4 H)-dione) species from phenylurazole on demand for tyrosine electrolabeling. The chemoselectivity of the reaction was studied with another amino acid (lysine, Lys) and no changes in Lys were observed. To evaluate the performance of tyrosine electrolabeling, coulometric analyses at controlled potentials were performed on solutions of phenylurazole and the phenylurazole-tyrosine mixture in different proportions (2:1, 1:1, and 1:2). The electrolysis of the phenylurazole-tyrosine mixture in the ratio (1:2) produced a charge of 2.07 C, very close to the theoretical value (1.93 C), with high reaction kinetics, a result obtained here for the first time. The products obtained were identified and characterized by liquid chromatography coupled to high-resolution electrospray ionization mass spectrometry (LC-HRMS and LC- HRMS2). Two products were formed from the click reactions, one of which was the majority. Another part of this work was to study the electrochemical degradation of the molecular anchor 4-phenylazole (Ph-Ur). Four stable degradation products of phenylurazole were identified (C7H9N2O, C6H8N, C6H8NO, C14H13N4O2) based on chromatographic profiles and mass spectrometry results. The charge generated during the electrolysis of phenylurazole (two-electron process) (2.85 C) is inconsistent with the theoretical or calculated charge (1.93 C), indicating that secondary/parasitic reactions occurred during the electrolysis of the latter. In conclusion, the electrochemically promoted click phenylurazole-tyrosine reactions give rise to click products with high reaction kinetics and yields in the (1:2) phenylurazole-tyrosine ratios, and the presence of side reactions is likely to affect the yield of the click phenylurazole-tyrosine reaction.
Angesichts der zunehmenden Digitalisierung und dem Einsatz datenintensiver Methodiken in der Wissenschaft stehen Forschende vor der Herausforderung, stetig wachsende Datenmengen nachvollziehbar zu dokumentieren, langfristig zu speichern und für Dritte nachnutzbar zu machen. Um diesen Anforderungen gerecht zu werden, bietet sich die Nutzung von Software-Lösungen an, welche Forschungsdatenmanagement mit der digitalen Dokumentation von Laborinventar und Experimenten in elektronischen Laborbüchern (engl. electronic lab notebooks (ELN)) verknüpfen.
Reliable measurement of the size of polydisperse, complex-shaped commercial nanopowders is a difficult but necessary task, e.g., for regulatory requirements and toxicity risk assessment. Suitable methods exist for the accurate characterization of the size of non-aggregated, stabilized, spherical and monodisperse nanoparticles. In contrast, industrial nanoscale powders usually require dedicated sample preparation procedures developed for the analysis method of choice. These nano-powders tend to agglomerate and/or aggregate, a behavior which in combination with an innate broad particle size distribution and irregular shape often significantly alters the achievable accuracy of the measured size parameters. The present study systematically tests two commercially available nanoscale powders using different sample preparation methods for correlative analysis by scanning electron microscopy, dynamic light scattering, Brunauer–Emmet–Teller method and differential mobility analysis. One focus was set on the sample preparation by embedding nanoparticles in carbon-based hot-mounting resin. Literature on this topic is scarce and the accuracy of the data extracted from cross sections of these particles is unclearly stated. In this paper systematic simulations on the deviation of the size parameters of well-defined series of nanoparticles with different shapes from the nominal value were carried out and the contributing factors are discussed.
ADAMTS4-specific MR-probe to assess aortic aneurysms in vivo using synthetic peptide libraries
(2022)
The incidence of abdominal aortic aneurysms (AAAs) has substantially increased during the last 20 years and their rupture remains the third most common cause of sudden death in the cardiovascular field after myocardial infarction and stroke. The only established clinical parameter to assess AAAs is based on the aneurysm size. Novel biomarkers are needed to improve the assessment of the risk of rupture. ADAMTS4 (A Disintegrin And Metalloproteinase with ThromboSpondin motifs 4) is a strongly upregulated proteoglycan cleaving enzyme in the unstable course of AAAs. In the screening of a one-bead-one-compound library against ADAMTS4, a low-molecular-weight cyclic peptide is discovered with favorable properties for in vivo molecular magnetic resonance imaging applications. After identification and characterization, it’s potential is evaluated in an AAA mouse model. The ADAMTS4-specific probe enables the in vivo imaging-based prediction of aneurysm expansion and rupture.
In dieser Arbeit werden die Grundlagen der Normung, die Entstehung einer Norm und die für die Gasanalytik relevanten Normungsgremien kurz dargestellt. Dazu werden die wichtigsten Normen zur Gasanalytik entlang des analytischen Prozesses gruppiert und aufgeführt. Schließlich wird als Anwendungsbeispiel aus der eigenen Praxis der Prozess von der Herstellung bis zur Zertifizierung eines Kalibriergases beschrieben.
BAM is currently building up a platform of novel nanoRMs relying on iron oxide nanoparticles of different shape, size and surface chemistry. Iron oxide was chosen as a core material because of its relevance to the material and life sciences.
As a first candidate of this series, we present cubic iron oxide nanoparticles with a nominal edge length of 8 nm. These particles were synthesized by thermal decomposition of iron oleate in high boiling organic solvents adapting well-known literature procedures. After dilution to a concentration suitable for electron microscopy (TEM and SEM) as well as for small-angle X-ray scattering (SAXS) measurements, the candidate nanoRM was bottled and assessed for homogeneity and stability by both methods following the guidelines of ISO 17034 and ISO Guide 35.
The particle sizes obtained by both STEM-in-SEM and TEM are in excellent agreement with a minimum Feret of 8.3 nm ± 0.7 nm. The aspect ratio (AR) of the iron oxide cubes were extracted from the images as the ratio of minimum Feret to Feret resulting in an AR of 1.18 for TEM to 1.25 for SEM. Alternatively, a rectangular bounding box was fitted originating from the minimum Feret and the longest distance through the particle in perpendicular direction. This led to AR values of 1.05 for TEM and 1.12 for SEM, respectively. The results confirm the almost ideal cubic shape.