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Boehmite nanoparticles has been successfully functionalized with APTES. After APTES functionalization further modification with tailored molecules e.g. via carboxylic acids is possible. The tailored surface functionalization is strongly enhanced by improved coupling protocols. Arbitrary variation of the functionalization degree is possible. Thereby the temperature stable APTES functionalization enables a wide range of functional groups.
By TGA-MS analysis strong evidence for the bonding situation of the APTES on the boehmite surface has been found. Additionally first experiments has been performed to predict the polymer-particle compatibility enhancement via reverse wetting angle measurements with AFM.
The impact of water released from boehmite nanoparticles during curing in epoxy-based nanocomposites
(2021)
The enhancing effect on mechanical properties of boehmite (γ-AlOOH) nanoparticles (BNP) in epoxy-based nanocomposites on the macroscopic scale encouraged recent research to investigate the micro- and nanoscopic properties. Several studies presented different aspects relatable to an alteration of the epoxy polymer network formation by the BNP with need for further experiments to identify the mode of action.
With FTIR-spectroscopic methods this study identifies interactions of the BNP with the epoxy polymer matrix during the curing process as well as in the cured nanocomposite. The data reveals that not the BNP themselves, but the water released from them strongly influences the curing process by hydrolysis of the anhydride hardener or protonation of the amine accelerator. The changes of the curing processes are discussed in detail.
The changes of the curing processes enable new explanation for the changed material properties by BNP discussed in recent research like a lowered glass transition temperature region (Tg) and an interphase formation.
Reference materials are essential to analyze the impact of micro- and nanoplastics. The particle size D50 has been chosen as property of interest. They can be produced top-down by milling. For size separation down to a particle size D50 of 50 µm sieving is suitable while smaller particle sizes can be obtained by filtration. After production it is important to control the stability because microplastic in the size range below 10 µm tend to agglomerate.
Micro- and nanoplastic particles became a topic of public concern all over the world e.g. in water, soil, sludge and air. For a profound risk assessment, it is necessary to identify the origins, hotspots, or transport between different media. Therefore, a representative repeatable analysis is required and reference materials (RM) to proof and compare methods.
The basis of MNP investigations is a harmonized analysis which includes sampling, sample preparation and detection. In recent years, spectroscopic methods like µRaman and µFTIR for the determination of particle numbers or thermoanalytical methods like Pyrolysis gas chromatography/mass spectrometry (py-GC/MS) and Thermo extraction/ desorption gas chromatography / mass spectrometry (TED-GC/MS) for mass determination have proven to be particularly suitable.
The technical committees (TC) of ISO TC 61 “plastics” and TC 147 “water quality" are working on harmonisation processes on international level. For all standardization approaches, it is necessary that the detection methods and analysis processes can be validated. Therefore, BAM develops reference material for microplastic (MP) analysis for several years with focus on the most common polymers PE, PP, PS, PET and PA.
MP particles with a close to reality fragment shape are obtained by cryomilling and sieving. For sample preparation purposes with mass detection methods MP particles are pressed into pills with a water-soluble matrix. Thereby losses due to sample preparation e.g. filtration are included in the verification of an analysis.
To ensure a constant quality throughout all MP RM batches the homogeneity and stability is controlled according to ISO Guide 35. Next to TED-GC/MS measurements particle size distribution, infrared spectroscopy and differential scanning calorimetry spectra are taken as accompanying parameters.
This presentation aims to introduce into the MP RM production process with ensured quality and special focus on pointing out customized setups for particle comminution, separation, and characterization for standardization.
Water as side effect of reinforcing boehmite filler Local changes in anhydride cured epoxy resin
(2019)
Nanocomposites offer wide opportunities for lightweight constructions and enable reduction of weight and volume. Beside macroscopic toughening nanoparticle reinforced polymers show a soft interface around boehmite (AlOOH) filler nanoparticles. A related strong interaction between boehmite and the anhydride cured resin system is widely suspected in literature but not determined by structural Analysis. Determination of the molecular structure is important to allow simulations approaching the real system and predict future reinforcing effects.
DRIFT (diffuse refletance infrared fourier transformed) spectra of the boehmite reinforced anhydride cured epoxy show significant changes in the molecular structure compared to the neat polymer. Further investigations of the interactions between the single components of the resin system and the boehmite filler pointed out reactions between released water released from the boehmite filler and the anhydride hardener or amine accelerator. This leads to the discussion of competing polymerisation mechanisms that highly influence the polymer properties. Ongoing experiments and literature research approve that this impact of water is able to locally change the stoichiometrie, alter the curing mechanism or support an inhomogeneous crosslink density.
New Focus On Boehmite-Reinforced Nanocomposites Molecular Approach With Advanced FTIR-Techniques
(2019)
By FTIR-study it was possible to proof a chemical reaction between boehmite and the hardener of anhydride cured epoxy resins. Future studies can assume that the chemical environment of the resin system is changed in the surrounding of boehmite nanoparticles. This highly affects especially localized properties.
Assembly of permanently porous metal–organic polyhedra/cages (MOPs) with bifunctional linkers leads to soft supramolecular networks featuring both porosity and processability. However, the amorphous nature of such soft materials complicates their characterization and thus limits rational structural control. Here we demonstrate that aging is an effective strategy to control the hierarchical network of supramolecular gels, which are assembled from organic ligands as linkers and MOPs as junctions. Normally, the initial gel formation by rapid gelation leads to a kinetically trapped structure with low controllability. Through a controlled post-synthetic aging process, we show that it is possible to tune the network of the linked MOP gel over multiple length scales. This process allows control on the molecular-scale rearrangement of interlinking MOPs, mesoscale fusion of colloidal particles and macroscale densification of the whole colloidal network. In this work we elucidate the relationships between the gel properties, such as porosity and rheology, and their hierarchical structures, which suggest that porosity measurement of the dried gels can be used as a powerful tool to characterize the microscale structural transition of their corresponding gels. This aging strategy can be applied in other supramolecular polymer systems particularly containing kinetically controlled structures and shows an opportunity to engineer the structure and the permanent porosity of amorphous materials for further applications.
The effect of spin fluctuations on the α(bcc)-γ(fcc)-δ(bcc) structural phase transitions in iron is investigated with a tight-binding (TB) model. The orthogonal d-valent TB model is combined with thermodynamic integration, spin-space averaging, and Hamiltonian Monte Carlo to compute the temperature-dependent free-energy difference between bcc and fcc iron. We demonstrate that the TB model captures experimentally observed phonon spectra of bcc iron at elevated temperatures. Our calculations show that spin fluctuations are crucial for both the α−γ and γ−δ phase transitions but they enter through different mechanisms. Spin fluctuations impact the α−γ phase transition mainly via the magnetic/electronic free-energy difference between bcc and fcc iron. The γ−δ phase transition, in contrast, is influenced by spin fluctuations only indirectly via the spin-lattice coupling. Combining the two mechanisms, we obtain both the α−γ and γ−δ phase transitions with our TB model. The calculated transition temperatures are in very good agreement with experimental values.
Exploratory analysis of hyperspectral FTIR data obtained from environmental microplastics samples
(2020)
Hyperspectral imaging of environmental samples with infrared microscopes is one of the preferred methods to find and characterize microplastics. Particles can be quantified in terms of number, size and size distribution. Their shape can be studied and the substances can be identified. Interpretation of the collected spectra is a typical problem encountered during the analysis. The image datasets are large and contain spectra of countless particles of natural and synthetic origin. To supplement existing Analysis pipelines, exploratory multivariate data analysis was tested on two independent datasets. Dimensionality reduction with principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) was used as a core concept. It allowed for improved visual accessibility of the data and created a chemical two-dimensional image of the sample. Spectra belonging to particles could be separated from blank spectra, reducing the amount of data significantly. Selected spectra were further studied, also applying PCA and UMAP. Groups of similar spectra were identified by cluster analysis using k-means, density based, and interactive manual clustering. Most clusters could be assigned to chemical species based on reference spectra. While the results support findings obtained with a ‘targeted analysis’ based on automated library search, exploratory analysis points the attention towards the group of unidientified spectra that remained and are otherwise easily overlooked.
µ-FTIR spectroscopy is a widely used technique in microplastics research. It allows to simultaneously characterize the material of the small particles, fibers or fragments, and to specify their size distribution and shape. Modern detectors offer the possibility to perform two-dimensional imaging of the sample providing detailed information. However, datasets are often too large for manual evaluation calling for automated microplastic identification. Library search based on the comparison with known reference spectra has been proposed to solve this problem.
To supplement this ‘targeted analysis’, an exploratory approach was tested. Principal component analysis (PCA) was used to drastically reduce the size of the data set while maintaining the significant information. Groups of similar spectra in the prepared data set were identified with cluster analysis. Members of different clusters could be assigned to different polymer types whereas the variation observed within a cluster gives a hint on the chemical variability of microplastics of the same type. Spectra labeled according to the respective cluster can be used for supervised learning. The obtained classification was tested on an independent data set and results were compared to the spectral library search approach.