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Thin mesoporous metal oxide films are versatile and attractive candidates for several energy applications like photovoltaics, electrolysis or batteries. Due to their high surface area and ordered pore structure, mesoporous metal oxides demonstrate higher activities. The performance of the porous films is affected by properties like size and shape of the mesopores as well as the crystallinity of the framework. The exact determination and metrological evaluation of the complex morphology of thin mesoporous films requires a new analytical approach employing to combined data of different analytical methods. In this contribution we present a novel evaluation procedure for spectroscopic ellipsometry (SE) to analyse thin mesoporous iridium oxide films.
Mesoporous iridium oxide films were prepared via dip-coating of a solution containing a triblock-copolymer as structure directing agent and an iridium precursor in ethanol. Deposited films were calcined in air at temperatures between 300 and 600 °C. Their morphology was studied with SEM and an electron probe microanalysis (EPMA) and correlated via SE with a Bruggeman effective medium approximation (BEMA). The developed SE model described the film thickness as well as the porosity.
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The contribution will assess in detail the novel approach to analyse the morphology and porosity of thin metal oxide films with spectroscopic ellipsometry. Moreover, the advantages of the new developed approach will be discussed as well as combination of datasets from multiple measurements to development new methods for innovative energy technologies.
Duplex (DSS) and austenitic stainless steels (ASS) are frequently used in many energy related applications. The duplex grade is considered to have outstanding mechanical properties as well as good corrosion resistance. The austenitic phase combines high ductility, even at low temperatures, with sufficient strength, and therefore such materials are applied in storage and transport of high-pressure hydrogen. During service in acidic environments large amounts of hydrogen can ingress into the microstructure and induce many changes in the mechanical properties of the steel. Embrittlement of steels by hydrogen remains unclear even though this topic has been intensively studied for several decades. The reason for that lies in the inability to validate the proposed theoretical models in the sub-micron scale. Among the very few available methods nowadays, Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) enables a highly accurate mapping of hydrogen in the microstructure in a spatial resolution below 100 nm. In the present work ToF-SIMS was used as a main tool in order to investigate the effect of deuterium on a duplex microstructure of lean and standard DSSs during and after the electrochemical charging process. Electrochemical charging simulates the service of a component in acidic environments under conditions of cathodic protection that are commonly applied to prevent corrosion reactions. ToF-SIMS after multivariate data analysis (MVA) was combined with high resolution topographic images and electron back-scattered diffraction (EBSD) data to characterize the structural changes. It was observed that the ferritic phase was affected almost identical in all steels whereas in the austenitic phase significant differences were obtained in the lean duplex in comparison to the standard DSS. The obtained results have been compared to similar investigations on a AISI 304L austenitic stainless steel. The advantage of the combined techniques is reflected by the ability to correlate the hydrogen distribution in the microstructure and the resulted phase transformation.
The interaction of nanoparticles (NPs) with cells has become a major field of interest, ranging from medical applications to nanotoxicology. Size, shape and surface modification of the NPs determine the uptake rate and pathway into the cells, and therefore impact specific cell components and processes.
Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is an established quantitative multi-elemental analysis and mapping technique. In recent years, it was shown that LA-ICP-MS can provide quantitative as well as distribution information of NPs in cell samples.
Here LA-ICP-MS was applied for the imaging of individual cells to study the uptake and intracellular processing of metal-containing nanostructures. Additionally, the local distribution of naturally occurring elements in cells like P was measured to indicate cell morphology. The cells were incubated with different types of NPs under varying experimental conditions. For LA analysis, the cells were fixed and dried.
Our findings show, that LA-ICP-MS is suitable for the localisation of nanoparticle aggregates within cellular compartments. The studied NPs accumulate in the perinuclear region in the course of intracellular processing, but do not enter the cell nucleus. The uptake efficiency depends strongly on the physicochemical properties of the nanostructures as well as on the incubation conditions like concentration and incubation time.
The results demonstrate the potential of LA-ICP-MS providing insight into NP uptake, intracellular distribution and cell-to-cell variation dependent on experimental parameters.
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example.
Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations).
Based on concentration measurements of reagents and products by the NMR analyzer a continuous production and direct loop process control were successfully realized for several validation runs in a modular industrial pilot plant and compared to conventional analytical methods (HPLC, near infrared spectroscopy). The NMR analyser was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (“Integrated CONtrol and SENsing”, www.consens-spire.eu).
Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example.Based on concentration measurements of reagents and products by the NMR analyzer a continuous production and direct loop process control were successfully realized for several validation runs in a modular industrial pilot plant and compared to conventional analytical methods (HPLC, near infrared spectroscopy). The NMR analyser was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme.
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example.
Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations).
Based on concentration measurements of reagents and products by the NMR analyzer a continuous production and direct loop process control were successfully realized for several validation runs in a modular industrial pilot plant and compared to conventional analytical methods (HPLC, near infrared spectroscopy). The NMR analyser was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (“Integrated CONtrol and SENsing”, www.consens-spire.eu).
Following the 2017 meeting, progress with the Key Comparison CCQM-K153 related to the BET specific surface lead by UNIIM and the Pilot Study P-190 “Thickness Measurement of nm HfO2 Films” lead by KRISS will be discussed.
The 16th meeting of SAWG will focus on
•survey on CMC claims submitted with reference to K-129 and K-136.
•the overall and SAWG specific aspects of the CCQM Strategy process,
•a consideration of comparisons on convention methods as recommended by the CCQM Plenary Meeting 2017,
•the 2019 CCQM Workshop and paper(s) for Metrologia’s Special Issue,
•discussion of future comparisons.
Extraction of true, 3D shape (and size) of non-spherical nanoparticles (NPs) is associated with errors by conventional 2D electron microscopy using projection images. Significant efforts within the ISO technical committee TC 229 ‘Nanotechnologies’ are aimed at establishing accurate TEM and SEM measurement of NP size and shape as robust, standard procedures. Study groups have been organizing inter-laboratory comparisons on well-selected NP systems according to the market needs, such as aggregated titania nano-powder for which size and shape distribution of primary crystallites of irregular shape must be measured accurately. To be noticed is e. g. the fact that the measurement procedure allows only manual selection of the particles clearly distinguishable for analysis as well as manual definition of the contour of the imaged NPs.
An inter-laboratory exercise on titania NPs (pure anatase, grown by hydrothermal synthesis) of well-defined non-spherical shape, i.e. bipyramidal has been recently started within ISO/TC 229 under similar conditions as for the irregular shaped titania. Overlapped particles were allowed to be considered, as long as they are clearly distinguishable. One decisive NP selection criterion was to analyze only those NPs with a roundness value below 0.7, i.e. the NPs laying on the support foil and, hence, with projection areas clearly deviating from perfect circles (R=1). The overall evaluation (for 15 labs) of the size descriptors (area, Feret, minFeret, perimeter) and shape descriptors (aspect ratio, roundness, compactness, extent) by analysis of variance is just to be finished and included in ISO/WD 21363 Nanotechnologies -- Protocol for particle size distribution by transmission electron microscopy.
Many applications of nanomaterials in the life sciences require the controlled functionalization of these materials with ligands like polyethylene glycol (PEG) and/or biomolecules such as peptides, proteins, and DNA. This enables to tune their hydrophilicity and biocompatibility, minimize unspecific interactions, improve biofunction-nalization efficiencies, and enhance blood circulation times and is the ultimate prerequisite for their use as reporters in assays or the design of targeted optial probes for bioimaging.
At the core of these functionalization strategies are reliable and validated methods for surface group and ligand quantification that can be preferably performed with routine laboratory instrumentation, require only small amounts of substances, and are suitable for many different types of nanomaterials.
We present here versatile and simple concepts for the quantification of common functional groups, ligands, and biomolecules on different types of organic and inorganic nano-materials, using different types of optical reporters and method validation with the aid of multimodal reporters and mass balances.