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Eingeladener Vortrag
- nein (29)
Acoustic levitators generate acoustic standing waves between a transducer and a concave reflector. These acoustic waves are separated by multiple integer numbers of half wavelengths. Thus, acoustic levitation is the effect that a small volume (5 nL-10 μL) of sample can be levitated in a contact-free manner. Until now, levitation in analytical chemistry has primarily been associated with optical techniques such as Raman, X-Ray or UV/Vis spectroscopy. Less common applications are combinations of acoustic levitation with mass spectrometry. One reason for this being that the acoustic field surrounding the droplet effectively shields the sample, thus making it inaccessible to most ambient ionization techniques. Any effective investigation of acoustically-levitated droplets therefore requires the physical removal of some of the sample from the confine region of the acoustic trap before analysis.
Die gemeinsame Forschungsstrategie der Bundesoberbehörden zur Nanotechnologie wurde 2016 veröffentlicht. Die darin enthaltenen Aufgaben wurden von den Bundesoberbehörden vielfältig bearbeitet. Diese Präsentation gibt einen Überblick über die Projekte, die von der BAM bis 2019 bearbeitet wurden/werden und sich in den Rahmen der Forschungsstrategie einordnen.
Monodisperse iron oxide nanoparticles as reference material candidate for particle size measurements
(2020)
In order to utilize and rationally design materials at the nanoscale the reliable characterization of their physico-chemical properties is highly important, especially with respect to the assessment of their environmental or biological impact. Furthermore, the European Commission’s REACH Regulations require the registration of nanomaterials traded in quantities of at least 1 ton. Powders or dispersions where 50% (number distribution) of the constituent particles have sizes ≤ 100 nm in at least one dimension are defined as nanomaterials. This creates a need for industrial manufacturers and research or analytical service facilities to reliably characterize potential nanomaterials. Currently, BAM is developing reference nanoparticles, which shall expand the scarce list of worldwide available nano reference materials certified for particle size distribution and will also target other key parameters like shape, structure, porosity or functional properties. In this respect, materials like iron oxide or titanium dioxide are considered as candidates to complement the already available silica, Au, Ag, and polystyrene reference nanoparticles.
The thermal decomposition of iron oleate precursors in high boiling organic solvents can provide large quantities of iron oxide nanoparticles that can be varied in size and shape.[1, 2] The presence of oleic acid or other hydrophobic ligands as capping agents ensures stable dispersion in nonpolar solvents. Such monodisperse, spherical particles were synthesized at BAM and pre-characterized by electron microscopy (TEM, SEM including the transmission mode STEM-in-SEM) and dynamic light scattering comparing cumulants analysis and frequency power spectrum.
1. REACH regulations and nanosafety concerns create a strong need for nano reference materials with diverse properties.
2. Iron oxide nanoparticles are under development as new candidate reference material at BAM.
3. Narrow particle size distribution confirmed by light scattering and electron microscopy.
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.
Background, Motivation and Objective
Nanomaterials are at the core of some of the 21st century’s most promising technologies. In order to utilize and rationally design materials at the nanoscale the reliable characterization of their physico-chemical properties is highly important. Furthermore, the European Commission has taken measures via the REACH Regulations to control the classification of nanomaterials. REACH Annexes which entered into force in January 2020 require manufacturers to register nanomaterials that are traded in larger quantities (at least 1 ton). Every powder or dispersion where 50% (number distribution) of the constituent particles have sizes ≤ 100 nm in at least one dimension are defined as a nanomaterial. This creates a need for both industrial manufacturers and research and analytical service facilities to reliably characterize potential nanomaterials. Currently, BAM is working on developing reference nanoparticles, which shall expand the scarce list of worldwide available nano reference materials certified for particle size distribution, but also targeting other key parameters such as shape, structure (including porosity) and functional properties. Thus, candidate materials are considered to complement the already available spherical and monodisperse silica, Au and polystyrene reference nanoparticles, e.g. iron oxide and titanium oxide, with an average atomic number between those of silica and gold. Particularly for the imaging by electron microscopies, new nanoparticles of well-defined size in the range of 10 nm are decisive for the accurate particle segmentation by setting precise thresholds.
Statement of Contribution/Methods
Synthesis: Highly monodisperse iron oxide nanoparticles can be synthesized in large quantities by thermal decomposition of iron oleate or iron acetylacetonate precursors in high boiling solvents such as octadecene or dioctyl ether in the presence of oleic acid and oleylamine as capping agents.
Scanning Electron Microscope: An SEM of type Supra 40 from Zeiss has been used including the dedicated measurement mode transmission in SEM (STEM-in-SEM) with a superior material contrast for the nanoparticle analysis. The software package ImageJ has been used for the analysis of the STEM-in-SEM images and to determine the particle size distribution.
Dynamic Light scattering (DLS): Particles in suspension were measured in comparison by means of Zetasizer Nano (Malvern Panalytical; cumulants analysis) and NanoFlex (Microtrac; frequency power spectrum).
Results/Discussion
In this study iron oxide nanoparticles synthesized at BAM and pre-characterized by DLS, SEM (including the transmission mode STEM-in-SEM) are presented. The particles are spherical and highly monodisperse with sizes slightly larger than 10 nm.
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.
It is a well-known story that copolymers beside their molar mass distribution (MMD) can exhibit a functionality type distribution (FTD), a copolymer composition distribution (CCD), a monomer sequence distribution (MSD) and additionally different topologies within one sample. Small, often isobaric heterogeneities in topology or microstructure can usually not be simply separated chromatographically or distinguished by any common detector. Nowadays a wide range of different analytical separation techniques and multi-detection possibilities are available. The challenge consists in a clever combination of these techniques with a specific approach of data analysis. In this presentation different liquid chromatographic separation modes were combined with Electrospray Time-of-Flight mass spectrometry.
The online coupling allows the analysis of reconstructed ion chromatograms (RIC) of each degree of polymerization. While a complete separation often cannot be achieved, the derived retention times and peak widths lead to information on the existence and dispersity of heterogeneities in microstructure or topology, that are otherwise inaccessible This method is suitable to detect small differences in e. g. branching, topology, monomer sequence or tacticity and could potentially be used in production control of oligomeric products or other routinely done analyses to quickly indicate deviations from set parameters. Based on a variety of examples e.g. the topology elucidation of branched EO-PO copolymers, the possibilities and limitations of this approach were demonstrated.
The increasing enrichment of water bodies and soils with plastic waste leads to the accumulation of microscopic plastic particles, so-called microplastics (MP). There is an urgent need for analytical methods that help to identify and quantify MP. At present, mainly thermo-analytical and microscopic methods such as micro-infrared spectroscopy or micro-Raman are used for this purpose. The latter are usually tied to time-consuming sample enrichment and preparation, only small sample quantities (micrograms) can be examined and the evaluation of the obtained spectra can be demanding. In the context of this presentation, two approaches are presented which, via the multi-variate analysis of spectroscopic data, allow i) a new methodological approach to screening MP in contaminated soils and ii) an alternative evaluation of large (micro)-spectroscopic data sets.
First, a NIR spectroscopic method is presented which allows MP consisting of polyethylene, polyethylene terephthalate, polypropylene and polystyrene to be detected in the range of up to 0.5 mass percent. Due to short measurement times and robust technology, this approach has the potential, in contrast to thermo-analytical and micro-spectroscopic methods, to examine larger sample quantities with minimal pre-treatment.
The second approach deals with the evaluation of large data sets, as typically obtained as a result of micro-FTIR using modern FPA detectors. The micro-FTIR technique is based on the spectral recording, imaging and subsequent identification of vibration bands typical of synthetic polymers. The image data sets are large and contain spectra of numerous particles of natural and synthetic origin. Exploratory multivariate data analysis has been tested to complement existing approaches based on e.g. spectrum library searches. The core concept used was dimensionality reduction. The results not only represent an orthogonal method for checking the results obtained by an automated library search, but also revealed a group of spectra that were not recorded in the existing spectrum libraries.
Up to now, different analytical methods for single cell analysis exist focusing on key features such as size, shape, morphology and elemental composition. The combination of the latest ICP-MS techniques - ICP-ToF-MS - together with the latest developments in the field of sample delivery - micro droplet generator (MDG) – will allow a Deep insight into the composition and size of cells.
Microbiologically influenced corrosion (MIC) is an oxidation of metals affected by the presence or activity (or both) of microorganisms e.g. Shewanella Putrefaciens in biofilms on the surface of the corroding material. As this can happen for example in the soil on iron pipes of water pipes, in oil tanks or on steel sheet piling, there is great interest in MIC research, not only from various industrial sectors, but also from the environmental aspect.
Simultaneous characterization of poly(acrylic acid) andpolysaccharide polymers and copolymers
(2020)
Copolymer products that result from grafting acrylic acid and other hydrophilicmonomers onto polysaccharides have recently gained significant interest in researchand industry. Originating from renewable sources, these biodegradable, low toxicity,and polar copolymer products exhibit potential to replace polymers from fossil sourcesin several applications and industries. The methods usually employed to character-ize these copolymers are, however, quite limited, especially for the measurement ofbulk properties. With more sophisticated applications, for example, in pharmaceu-tics requiring a more detailed analysis of the chemical structure, we describe a newapproach for this kind of complex polymers. Our approach utilizes chromatographyin combination with several detection methods to separate and characterize reactionproducts of the copolymerization of acrylic acid and chemically hydrolyzed starch.These samples consisted of a mixture of homopolymer poly (acrylic acid), homopoly-mer hydrolyzed starch, and – in a lower amount – the formed copolymers. Several chro-matographic methods exist that are capable of characterizing either poly (acrylic acid)or hydrolyzed starch. In contrast, our approach offers simultaneous characterization ofboth polymers. The combination of LC and UV/RI offered insight into the compositionand copolymer content of the samples. Size exclusion chromatography experimentsrevealed the molar mass distribution of homopolymers and copolymers. FTIR inves-tigations confirmed the formation of copolymers while ESI-MS gave more details onthe end groups of hydrolyzed starches and poly (acrylic acids). Evidence of copolymerstructures was obtained through NMR measurements. Finally, two-dimensional chro-matography led to the separation of the copolymers from both homopolymers as wellas the additional separation of sodium clusters. The methods described in this work area powerful toolset to characterize copolymerization products of hydrolyzed starch andpoly(acrylic acid). Together, our approach successfully correlates the physicochemicalproperties of such complex mixtures with their actual composition.
Tour de table - BAM
(2021)
A particle roughness analysis tool, based on electron microscopy (EM) images. The influence of various parameters on the calculated roughness was also investigated: the setting of the proper threshold, accelerating voltage, etc. The samples were gradually tilted to extend imaging information of more than only one projection. Furthermore, the measurement uncertainty of the profile roughness of particles associated to various orientations was estimated.
A novel stationary phase for affinity separations is presented. This material is based on sintered borosilicate glass readily available as semi-finished filter plates with defined porosity and surface area. The material shows fast binding kinetics and excellent long-term stability under real application conditions due to lacking macropores and high mechanical rigidity. The glass surface can be easily modified with standard organosilane chemistry to immobilize selective binders or other molecules used for biointeraction. In this paper, the manufacturing of the columns and their respective column holders by 3D printing is shown in detail. The model system protein A/IgG was chosen as an example to examine the properties of such monolithic columns under realistic application conditions. Several specifications, such as (dynamic) IgG capacity, pressure stability, long-term performance, productivity, non-specific binding, and peak shape, are presented. It could be shown that due to the very high separation speed, 250 mg antibody per hour and column can be collected, which surpasses the productivity of most standard columns of the same size. The total IgG capacity of the shown columns is around 4 mg (5.5 mg/mL), which is sufficient for most tasks in research laboratories. The cycle time of an IgG separation can be less than 1 minute. Due to the glass material's excellent pressure resistance, these columns are compatible with standard HPLC systems. This is usually not the case with standard affinity columns, limited to manual use or application in low-pressure systems. The use of a standard HPLC system also improves the ability for automation, which enables the purification of hundreds of cell supernatants in one day. The sharp peak shape of the elution leads to an enrichment effect, which might increase the concentration of IgG by a factor of 3. The final concentration of IgG can be around 7.5 mg/mL without the need for an additional nanofiltration step. The purity of the IgG was > 95% in one step and nearly 99% with a second polishing run.
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.
A particle roughness analysis tool, based on electron microscopy images (SEM and TEM). The influence of various parameters on the calculated roughness was also investigated: the setting of the proper threshold, accelerating voltage, etc. The samples were gradually tilted to extend imaging information of more than only one projection. Furthermore, the measurement uncertainty of the profile roughness of particles associated to various orientations was estimated.
This dataset accompanies the following publication, first published in Scientific Reports (www.nature.com/articles/s41598-021-84287-6):
B. Ruehle, J. Krumrey, V.-D. Hodoroaba, Scientific Reports, Workflow towards Automated Segmentation of Agglomerated, Non-Spherical Particles from Electron Microscopy Images using Artificial Neural Networks, DOI: 10.1038/s41598-021-84287-6
It contains electron microscopy micrographs of TiO2 particles, the corresponding segmentation masks, and their classifications into different categories depending on their visibility/occlusion. Please refer to the publication and its supporting information for more details on the acquisition and contents of the dataset, as well as the GitHub repository at https://github.com/BAMresearch/automatic-sem-image-segmentation
ICP-ToF (Flugzeitanalysator, engl. time of flight)-MS ermöglicht den Multielement Fingerabdruck einzelner Zellen (single cell) zu analysieren. Die single cell-ICP-ToF-MS kommt bei dem vorgestellten Poster bei der Analyse von Archaeen, die an mikrobiell beeinflusster Korrosion (engl. microbiologically influenced corrosion, MIC) von Stahl eine Rolle spielen, zum Einsatz. Mittels sc-ICP-ToF-MS wird die mögliche Aufnahme von einzelnen Elementen aus dem jeweiligen Stahl untersucht – die erhaltenen Informationen fließen zukünftig in die Aufklärung zugrunde liegender Mechanismen sowie Entwicklung möglicher Materialschutzkonzepte ein. Die Arbeiten Verknüpfen moderne Methoden der Analytical Sciences mit Materialien.
The publicly available document encapsulates the first version of the Catalogue of Services of the future EC4Safenano Centre (CoS 2019).
The CoS 2019 is structured in 12 Service Categories and 27 Service Topics, for each of the 12 categories considered. This architecture configures a 12 x 27 matrix that allows ordering the potential EC4Safenano offer in 324 types of services/groups of services.
Each type of service/group of services is described, in a simple and friendly way, by means of a specific service sheet: the EC4Safenano - Service Data Sheet (EC4-SDS). These EC4-SDSs allow structuring and summarizing the information of each service, providing the customer with a concise view of characteristics of the service and also the contact details with the service provider.
The CoS 2019 deploys a map of services consisting of a set of 100 EC4-SDSs, covering 7 of the 12 Service Categories and 17 of the 27 Service Topics.
The harmonization of services is visualized as a future necessary step in EC4Safenano, in order to strengthen the offer and provide added value to customers with a growing offer of harmonized services in future versions of the CoS.
The information contained in this document is structured in 3 main sections, as follows:
• Catalogue structure. This section describes in short the main characteristics of the CoS 2019.
• Catalogue content. This section represents the core part of the document and encapsulates the set of 100 SDSs displaying the offer proposed by the CoS 2019.
• Online Catalogue. This section describes the resources implemented by EC4Safenano to facilitate the on-line consultation of the CoS 2019 by customers and other interested parties.