6.1 Oberflächen- und Dünnschichtanalyse
Filtern
Dokumenttyp
- Zeitschriftenartikel (2)
- Vortrag (2)
- Forschungsbericht (1)
Sprache
- Englisch (5) (entfernen)
Schlagworte
- TEM (5) (entfernen)
Organisationseinheit der BAM
Eingeladener Vortrag
- nein (2)
Quantitative Microstructural Analysis - VAMAS TWA 37 & Liaison with ISO/TC 202 Microbeam Analysis
(2023)
The progress in activities on Microbeam Analysis under VAMAS/TWA 37 is reviewed. Particularly the liaison with the new projects within the ISO technical committee TC 202 is presented and discussed with respect to the identification and launching corresponding VAMAS projects. The ongoing project "FIB sample processing for TEM" is presented in detail.
Quantitative Microstructural Analysis - VAMAS TWA 37 & Liaison with ISO/TC 202 Microbeam Analysis
(2022)
The progress in activities on Microbeam Analysis under VAMAS/TWA 37 is reviewed. Particularly the liaison with the new projects within the ISO technical committee TC 202 is presented and discussed with respect to the possibility of identifying and launching related VAMAS projects. The recently started project FIB sample processing for TEM is highlighted. Need of more promotion for the engagement of more participants from industry and academia at national, European and international level is highlighted. Also, the competition with the other technical working areas (on 'nano' or materials-related) is critically discussed. Further, a short overview of the VAMAS areas of activities is given where Germany is involved. Planed regional VAMAS Workshops in Germany in 2023 are announced.
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.
Controlling thickness and tightness of surface passivation shells is crucial for many applications of core–shell nanoparticles (NP). Usually, to determine shell thickness, core and core/shell particle are measured individually requiring the availability of both nanoobjects. This is often not fulfilled for functional nanomaterials such as many photoluminescent semiconductor quantum dots (QD) used for bioimaging, solid state lighting, and display technologies as the core does not show the applicationrelevant functionality like a high photoluminescence (PL) quantum yield, calling for a whole nanoobject approach. By combining high-resolution transmission electron microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS), a novel whole nanoobject approach is developed representatively for an ultrabright oleic acid-stabilized, thick shell CdSe/CdS QD with a PL quantum yield close to unity. The size of this spectroscopically assessed QD, is in the range of the information depth of usual laboratory XPS. Information on particle size and monodispersity were validated with dynamic light scattering (DLS) and small angle X-ray scattering (SAXS) and compared to data derived from optical measurements. In addition to demonstrating the potential of this novel whole nanoobject approach for determining architectures of small nanoparticles, the presented results also highlight challenges faced by different sizing and structural analysis methods and method-inherent uncertainties.
Singlet oxygen generation potential of two novel free-base-porphyrin photocatalysts was investigated. The freebase-porphyrin-sensitized Fe3O4 magnetic nanoparticles (MNPs) were tested for the degradation of the model pollutant Bisphenol A (BPA) in aqueous solution, for the first time. MNPs with either cubic or spherical shape were synthesized using the sonochemical approach, followed by sensitizing with photoactive 4,4′,4′′,4′′′- (Porphine-5,10,15,20-tetrayl)tetrakis(benzoic acid) (TCPP). The resulted photocatalysts were characterized in detail by scanning and transmission electron microscopy, Brunauer–Emmett–Teller analysis, spectral techniques and vibrating sample magnetometry. The electron spin resonance experiments have confirmed the high activity of the photocatalysts through the efficient formation of singlet oxygen in solution. The optimum operational parameters for BPA degradation were established as follows: 1.0 μmol L−1 BPA, 1.0 g L−1 of photocatalyst, 100 μmol L−1 H2O2, under UVA irradiation. In these conditions, the results for both photocatalysts revealed that after only 10 min of reaction, over 64% and ca. 90% of BPA have been removed from solution in the absence and presence of H2O2, respectively. Whereas after 60 minutes of treatment, only 24% of BPA in real wastewater effluent samples were removed under UVA irradiation in the absence of H2O2, showing the high complexity of real wastewater. Moreover, both photocatalysts were successfully used for BPA removal in three consecutive runs, without significant loss of catalytic features.