Ingenieurwissenschaften und zugeordnete Tätigkeiten
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Eingeladener Vortrag
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The novel lab-based HAXPES spectrometer (ULVAC-PHI Quantes) gives us the possibility to measure XPS at 1486.6 eV (monochromatic Al Kα source) and HAXPES at 5414.9 eV (monochromatic Cr Kα source) on a sample at the same position. The surface analysis with this spectrometer leads to an information depth of about 10 nm for XPS and in comparison, to an analysis of deeper regions of about 30 nm for HAXPES measurements. This method provides a nondestructive way to distinguish between the near-surface region of the nanoparticles and the whole nanoparticle. Additionally, HAXPES gives access to deeper core levels at higher energy.
An application of this technique is presented using nanoparticles. The results shown were obtained with nanoparticles, that were treated differently by means of sterilization for nanosafety (i.e., before studying their toxicity it is important to establish whether nanomaterials are sterile and, if not, to be treated either via microwave or autoclave sterilisation). As a complementary method, the data is compared with SEM and EDX measurements. All methods demonstrate the influence of sterilization. More specifically, these results show that the sterilization step must be considered in the physical-chemical description of the particles for establishing reliable (quantitative structure-activity) relationships.
In pursuing the automated synthesis of metal nanoparticles (NPs), the capabilities of the “Chemputer” are deployed, for the first time, into the field of inorganic chemistry. Metal NPs have a substantial impact across different fields of science, such as photochemistry, energy conversion, and medicine. Among the commonly used nanoparticles, silver NPs are of special interest due to their antibacterial properties and applications in sensing and catalysis. However, many of the methods used to synthesize Ag NPs often do not result in well-defined products, the main obstacles being high polydispersity or a lack of particle size tunability.
The Chemputer is a modular, automated platform developed by the Cronin group for execution of multi-step, solution based organic synthesis. The machine has been further implemented at BAM, where we used this setup to perform automated organic syntheses, autonomously controlled by feedback derived from online NMR. In the Chemputer liquids can be transferred across a backbone, constructed from HPLC selection valves and syringe pumps. The Chemputer operates in a batch mode, common laboratory devices, such as heaters and glassware like round bottom flasks, are connected to the backbone, forming reaction modules. Solutions can be manipulated in these modules, and as all operations are controlled through a software script, reproducibility among individual syntheses is high. Likewise, any adjustments of the synthesis conditions, if required, are straightforward to implement and are documented in the reaction log file and a code versioning system.
We characterised Chemputer-synthesized nanoparticles using small-angle X-ray scattering, dynamic light scattering and further methods, showing that automated synthesis can yield colloids with reproducible and tuneable properties. The approach is an important first step towards the automation of nanoparticle syntheses in a modular, multipurpose platform. The modularity of the Chemputer opens many possibilities for the synthesis of a variety of different NP morphologies and sizes and potentially more complex structures. These advances and further work can help in the general investigations of silver nanoparticles by supplying a reliable and reproducible method of their synthesis and removing tacit knowledge by significantly reducing the experimental bias.
Nanoparticle Populations
(2022)
Two new projects P15 Measurement of particle size and shape distribution of bipyramidal titania including deposition from liquid suspension and P16 Measurement of (relative) number concentration of bimodal silica nanoparticles including deposition from liquid suspension have been started at VAMAS/TWA 34 under the lead of BAM. First results are presented and discussed.
The main outcomes of the EMPIR project nPSize are presented and the suitability of the new capabilities, e.g. reference materials, sample preparation protocols, measurement procedures, and data analysis, to be standardized and implemented in accredited analytical laboratories is discussed. Complementation and/or filling gaps of published and ongoing standardisation projects on size, shape and number concentration measurements under ISO/TC 229/JWG 2 are offered.
The two VAMAS inter-laboratory comparisons resulted from the nSPize project and just started under TWA 34 Nanoparticle Populations (Projects #15 and #16) of bipyramidal TiO2 anatase and bimodal SiO2 nanoparticles are presented in detail.
Both essential aspects of the surface of solid matter, its morphology and chemistry, are studied traditionally at BAM starting in the 60’s with different cyclical research focus areas, mostly related either to applicative research or method development. In the recent years, the focus has shifted almost exclusively to the nano-analytics of advanced materials such as complex nanoparticles, (ultra)thin films/coatings, nanocomposites, 2D materials, energy materials, etc. This is also the reason why BAM has established recently the new Competence Center nano@BAM (www.bam.de/Navigation/DE/Themen/Material/Nanotechnologie/sichere-nanomaterialien.html) with the five sub-fields nanoCharacterisation, nanoMaterial, nanoSafety, nanoData and nanoTechnology. The link to the BAM central guidelines to the safety in technology and chemistry is given by the development of reference products such as reference measurement procedures, reference (nano)materials, and newly reference data sets. Thus, an internationally well-networked group in surface analysis has been established @BAM, with regular contributions to integral analytical characterization with metrological and standardization background.
Examples of newly developed methodical approaches will be given with an emphasis on correlative nano-analysis of morphology and chemistry of nanomaterials. Correlative imaging by STEM-in-SEM with high-resolution SEM and EDX, and further with AFM or the new technique TKD (Transmission Kikuchi Diffraction) will be explained on various examples of nanostructures, both as starting materials and embedded/functionalized nanoparticles in products. The unique analytical benefits of the Auger electron probe as a veritable nano-tool for surface chemistry will be highlighted. The panoply of advanced surface characterization methods @BAM is completed by discussing examples of hybrid analysis of the bulk of nanomaterials by X-ray Spectroscopy with the highest surface-sensitive methods X-ray Photoelectron Spectroscopy (XPS) and Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS). Particularly for the analysis of the surface chemistry of nanostructures, such as the completeness of the shells of core-shell nanoparticles or in-depth and lateral gradients of chemistry within mesoporous thin layers, the latter methods are inherent.
Other special developments like approaches for the quantitative determination of the roughness of particle surface by electron microscopy or for the quantitative determination of the porosity of thin mesoporous layers by electron probe microanalysis (EPMA) with SEM will be presented.
he main objective of the nPSize project is to improve the measurement capabilities for nanoparticle size based on both measurement methods traceable to SI units and new reference materials. Two basic approaches have been used in order to develop measurement procedures resulting in traceable results of the nanoparticle size distribution: physical modelling for the methods used in the project (TSEM, SEM, AFM and SAXS) and machine learning.
Physical modelling: In this part, the physical models associated with different shape measurements for the techniques TSEM, SEM, AFM and SAXS have been collected and further developed with the aim to simulate the resulting signal as measured by the individual methods. Uncertainties and traceability associated with each model were investigated and evaluated. In the following, the progress on these physical models is reported for each individual method.
Machine Learning modelling: The aim of this part is to use machine learning to enable automatic measurement of nanoparticle shape from expert a-priori information only. No physical model will be used as a-priori information in this task.
The accuracy and traceability of the size results obtained by each technique will be analyzed and compared with the physical modelling. A machine learning database will then be used to create automatic detection algorithms.
Water splitting using semiconductor photo-catalysts is considered a sustainable method to produce clean hydrogen fuel. Nevertheless, H2 photo-production efficiency remains still low, although extensive research works to understand better the mechanisms of the Hydrogen Evolution Reaction (HER) and the Oxygen Evolution Reaction (OER) are being carried out. In this respect, TiO2 is a key photoactive material, usually employed with a co-catalyst deposited onto the surface to enhance charge carriers’ separation and catalyze surface charge transfer reactions. The deposition of a co-catalyst on the TiO2 nanoparticle surface represents one successful way to enhance the activity of the photocatalyst through a modification of its surface and redox properties. In this context, high-resolution scanning electron microscopy (SEM) coupled with elemental analysis by energy-dispersive X-ray spectroscopy (EDS) is fundamental for studying and understanding the effect of the nanoparticle morphology on the functional properties of shape-controlled TiO2 crystals (bipyramides, platelets, and elongated particles). Different types of metal-semiconductor combinations, TiO2 shapes and dopant metals (Ag, Pt, Au, Rh, Pd) and metal concentrations are discussed.
One aim of the EMPIR nPSize project 17NRM04 was to develop and validate three classes of candidate reference (test) materials (RTMs), with i) well-defined non-spherical shape, ii) relatively high polydispersity index, and iii) accurate particle concentrations.
To fulfil the requirements of the project, 11 different types of materials were prepared. Following the initial assessment of the materials suitability, nPSize5_PT_UNITO, nPSize6_AC_UNITO and nPSize7_GN_CEA materials were found unsuitable for the project, due to various reasons. PT material was deemed unsuitable due to its predominantly agglomerated nature. AC material contained relatively high amount of impurities (other particle forms). GN material was found too heterogeneous in both the length and width for the purpose of the project. The remaining 8 candidate RTMs were assessed for their homogeneity and stability and used for successful delivery of the associated activities within the nPSize project.
Nanosafety is becoming increasingly important as nanomaterials are widely used in industrial processes and consumer products. For nanotoxicity measurements prior sterilization of the samples is necessary, but as structure activity relationships are made with properties of pristine particles, the question arises, if the sterilization process has an impact on the physico-chemical properties of nanoparticles and thus on the biological behavior.
This question will be addressed in this talk. For this purpose, results from SEM and EDS measurements are combined with those of a novel lab-based HAXPES spectrometer in order to obtain a more complete picture. At the end, an influence of sterilization will be evident, which indicates a restructuring of the nanoparticles owing to sterilization.