6 Materialchemie
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L-lactide was polymerized in bulk at 120, 140, 160 and 180°C with neat tin(II) 2-ethylhexanoate (SnOct2) as catalyst. At 180°C the Lac/Cat ratio was varied from 25/1 up to 8 000/1 and at 160°C from 25/1 up to 6 000/1. The vast majority of the resulting polylactides consist of cycles in combination with a small fraction of linear chains having one octanoate and one COOH end group. The linear chains almost vanished at high Lac/Cat ratios, as evidenced by MALDI-TOF mass spectrometry and measurements of intrinsic viscosities and dn/dc values. At Lac/Cat ratios <1000/1 the number average molar masses (Mn) are far higher than expected for stoichiometic initiation, and above 400/1 the molar masses vary relatively little with the Lac/Cat ratio. At 180° slight discoloration even at short times and degradation of the molar masses were observed, but at 160°C or below colorless products with weight average molar masses (Mw) up to 310 000 g mol-1 were obtained. The formation of high molar mass cyclic polylactides is explained by a ROPPOC (Ring-Opening Polymerizatiom with simultaneous Polycondensation) mechanism with intermediate formation of linear chains having one Sn-O-CH end group and one mixed anhydride end group. Additional experiments with tin(II)acetate as catalyst confirm this interpretation. These findings together with the detection of several transesterification mechanisms confirm previous critique of the Jacobson-Stockmayer theory.
The quantitative determination of adhesion and cohesion properties is a key requirement for adhesive-bonded joints and coated components in both R&D and Quality assurance. Because of the huge variety of layer/substrate Systems in terms of materials and large thickness range, adhesion tests display the same diversity as layer/substrate systems. There are only two tensile testing procedures available, that determine adhesive strength in terms of force per area (N/mm²), the single-sample pull-off test in a tensile testing machine and the multiple-sample-test using the Centrifugal Adhesion Testing (CAT) Technology.
The CAT Technology is a testing method which uses centrifugal force as tensile testing force in a multiple-sample arrangement within a drum rotor of a Desktop centrifuge. Hence, the adhesive/bonding strength A/B can be determined on a statistical basis under identical testing conditions for up to eight samples.
A variety of examples for bonding strength of adhesives, adhesive strength of coatings and compound strength of composite materials is discussed such as metalto-metal and glass-to-metal bonding, sputtered SiO2-layers on CR39 Polymer and carbon fiber reinforced polymer.
High-entropy alloys (HEAs) are characterized by a solid solution of minimum five and medium-entropy alloys (MEAs) of minimum three principal alloying elements in equiatomic proportions. They show exceptional application properties, such as high-strength and ductility or corrosion resistance. Future HEA/MEA-components could be exposed to hydrogen containing environments like vessels for cryogenic or high-pressure storage where the hydrogen absorption and diffusion in these materials is of interest. In our study, we investigated the HEA Co20Cr20Fe20Mn20Ni20 and the MEA Co33.3Cr33.3Ni33.3. For hydrogen ingress, cathodic charging was applied and diffusion kinetic was measured by high-resolution thermal desorption spectros-copy using different heating rates up to 0.250 K/s. Peak deconvolution resulted in high-temperature desorption peaks and hydrogen trapping above 280 °C. A total hydrogen concentration > 40 ppm was identified for the MEA and > 100 ppm for HEA. This indicates two important effects: (1) delayed hydrogen diffusion and (2) considerable amount of trapped hydrogen that must be anticipated for hydrogen assisted cracking phenomenon. Local electrochemical Volta potential maps had been measured for the hydrogen free condition by means of high-resolution Scanning Kelvin Probe Force Microscopy (SKPFM).
Inelastic incoherent neutron time-of flight scattering was employed to measure the low frequency density of states for a series of addition polynorbornenes with bulky side groups. The rigid main chain in combination with the bulky side groups give rise to a microporosity of these polymers in the solid state. The microporosity characterized by the BET surfaces area varies systematically in the considered series. Such materials have some possible application as active separation layer in gas separation membranes.
All investigated materials show excess contributions to the Debye type density of states characteristic for glasses known as Boson peak. The maximum position of the Boson peak shifts to lower frequency values with increasing microporosity. Data for PIM-1 and Matrimid included for comparison are in good agreement to this dependency. This result supports the sound wave interpretation of the Boson peak.
Quasielastic neutron scattering by employing a combination of time-of-flight and backscattering techniques is carried out to explore the molecular mobility of a polymer of intrinsic microporosity (PIM-1) at microscopic time scales in comparison with a high-performance polyimide. Molecular fluctuations can change the structure of the temporary network of micropores and open or close pathways for gas molecules. Therefore, the investigation might help to understand the selectivity of PIMs in gas separation processes. The performed neutron scattering experiments provide evidence for a low-temperature relaxation process, which was assigned to methyl group rotation. This methyl group rotation was analyzed in terms of jump diffusion in a three-fold potential. The analysis results in a fraction of methyl groups which are immobilized. For PIM-1 it was found that the fraction of immobilized methyl groups decreases with increasing temperature up to 350 K. At higher temperatures the number of immobilized methyl group increases gain due to an underlying relaxation process. This motional process on a somewhat larger length scale might lead to a reversible structural rearrangement which partially hinders the strongly localized methyl group rotation. In addition, it was found that the activation energy for the methyl group rotation for PIM-1 and the polyimide is significantly higher than for conventional polymers.
Most real core-shell nanoparticle (CSNP) samples deviate from an ideal core-shell structure potentially having significant impact on the particle properties. An ideal structure displays a spherical core fully encapsulated by a shell of homogeneous thickness, and all particles in the sample exhibit the same shell thickness. Therefore,
analytical techniques are required that can identify and characterize such deviations.
This study demonstrates that by analysis of the inelastic background in X-ray photoelectron spectroscopy (XPS) survey spectra, the following types of deviations can be identified and quantified: the nonuniformity of the shell thickness within a nanoparticle sample and the incomplete encapsulation of the cores by the shell material. Furthermore, CSNP shell thicknesses and relative coverages can be obtained. These results allow for a quick and straightforward comparison between several batches of a specific CSNP, different coating approaches, and so forth. The presented XPS methodology requires a submonolayer distribution of CSNPs on a substrate.
Poly(tetrafluoroethylene)-poly(methyl methacrylate) and poly(tetrafluoroethylene)-polystyrene polymer CSNPs serve as model systems to demonstrate the applicability of the approach.
Phage display biopanning with Illumina next-generation sequencing (NGS) is applied to reveal insights into peptide-based adhesion domains for polypropylene (PP). One biopanning round followed by NGS selects robust PP-binding peptides that are not evident by Sanger sequencing. NGS provides a significant statistical base that enables motif analysis, statistics on positional residue depletion/enrichment, and data analysis to suppress false-positive sequences from amplification bias. The selected sequences are employed as water-based primers for PP-metal adhesion to condition PP surfaces and increase adhesive strength by 100% relative to nonprimed PP.
Identifying nanomaterials (NMs) according to European Union Legislation is challenging, as there is an enormous variety of materials, with different physico-chemical properties. The NanoDefiner Framework and its Decision Support Flow Scheme (DSFS) allow choosing the optimal method to measure the particle size distribution by matching the material properties and the performance of the particular measurement techniques. The DSFS leads to a reliable and economic decision whether a material is an NM or not based on scientific criteria and respecting regulatory requirements. The DSFS starts beyond regulatory requirements by identifying non-NMs by a proxy Approach based on their volume-specific surface area. In a second step, it identifies NMs. The DSFS is tested on real-world materials and is implemented in an e-tool. The DSFS is compared with a decision flowchart of the European Commission’s (EC) Joint Research Centre (JRC), which rigorously follows the explicit criteria of the EC NM definition with the focus on identifying NMs, and non-NMs are identified by exclusion. The two approaches build on the same scientific basis and measurement methods, but start from opposite ends: the JRC Flowchart starts by identifying NMs, whereas the NanoDefiner Framework first identifies non-NMs.
In this paper one refined approach is applied to determine the exact orientation of bipyramidal TiO2 nanoparticles prepared with good dispersion as almost isolated particles on a carbon TEM grid. The advantages of the recently developed high-throughput Transmission Kikuchi Diffraction (TKD) are used to identify quickly and reliably the geometrical orientation of the crystalline TiO2 nanoparticle bipyramids (anatase) on a statistically relevant number of particles.
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.