6 Materialchemie
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Tour de table - BAM
(2021)
Controlling the 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 application-relevant functionality like a high photoluminescence (PL) quantum yield. This calls for a whole nanoobject approach. Moreover, the thickness of the organic coating remains often unclear.
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. The results of the different methods match very well within the different measurement uncertainties. Additionally, results obtained with energy-resolved XPS using excitation energies between 200 eV and 800 eV are discussed with respect to a potential core/shell intermixing.
Moreover, the future application potential of this approach correlating different sizing and structural methods is discussed considering the method-inherent uncertainties and other core/multi-shell nanostructures.
Quaternary semiconductor nanocrystals like AgInS2-ZnS solid solution quantum dots (QDs) are a highly promising material for material science and biomedical applications due to their tunable photoluminescence (PL), their high quantum yields (QY), and their low cytotoxicity1. A red shift of the PL into the NIR and SWIR region could further increase their application potential. Copper doping has been proven to be a suitable approach for bathochromically shifting the PL of QDs2. The synthesis of copper doped AgInS2-ZnS QDs from a single-source-precursor should enable an easily scalable synthesis with high reproducibility.
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.
A brief perspective of BAM on nanocarriers is presented including examples with special emphasis on the characterization of such materials and underlying challenges. In this respect, also ongoing activities at BAM on different types of core/shell nanomaterials and related systems are briefly summarized.
The use of inorganic lanthanide-doped upconversion nanoparticles (UCNP) in bioimaging and cellular studies requires biocompatible particles. One possible cause of UCNP toxicity is the release of potentially harmful fluoride and lanthanide ions as revealed by dilution studies in aqueous environments, particularly under high dilution conditions. To address this issue, suitable surface coatings preventing such effects in combination with fast screening methods suited for online monitoring and in situ analyses are desired.
Here we present systematic studies of differently sized β-NaYF4:Yb,Er UCNP stabilized with different surface coatings and hydrophilic ligands varying in binding strength to the particle surface in various aqueous environments at different temperatures and UCNP concentrations. The concentration of the fluoride and lanthanide ions released upon particle dissolution was quantified electrochemically with a fluoride ion-sensitive electrode and inductively coupled plasma optical emission spectrometry (ICP-OES) and monitored fluorometrically, thereby exploiting the sensitivity of the upconversion luminescence to changes in size and surface chemistry. Moreover, changes in surface chemistry were determined with X-Ray photoelectron spectroscopy (XPS). Based upon our results, we could derive optimum screening parameters for UCNP stability studies and determine conditions and coating procedures and ligands for enhancing UCNP stability in aqueous environments.
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
We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds, and the segmented images can be used for automatically extracting and calculating various other particle size and shape descriptors.