High-Frequency Ultrasonic Spectroscopy of Structure Gradients in Injection-Molded PEEK Using a Focusing Transducer.

For high-performance thermoplastic materials, material behavior results from the degree of crystallization and the distribution of crystalline phases. Due to the less stiff amorphous and the stiffer and anisotropic crystalline phases, the microstructural properties are inhomogeneous. Thus, imaging of the microstructure is an important tool to characterize the process-induced morphology and the resulting properties. Using focusing ultrasonic transducers with high frequency (25 MHz nominal center frequency) enables the imaging of specimens with high lateral resolution, while wave propagation is related to the elastic modulus, density and damping of the medium. The present work shows experimental results of high-frequency ultrasonic spectroscopy (HF-US) applied to injection-molded polyether-ether-ketone (PEEK) tensile specimens with different process-related morphologies. This work presents different analysis procedures, e.g., backwall echo, time of flight and Fourier-transformed time signals, facilitating the mapping of gradual mechanical properties and assigning them to different crystalline content and morphological zones.

A FIB-SEM Based Correlative Methodology for X-Ray Nanotomography and Secondary Ion Mass Spectrometry: An Application Example in Lithium Batteries Research.

Correlative microscopy approaches are attracting considerable interest in several research fields such as materials and battery research. Recent developments regarding X-ray computer tomography have made this technique available in a compact module for scanning electron microscopes (SEMs). Nano-computed tomography (nanoCT) allows morphological analysis of samples in a nondestructive way and to generate 2D and 3D overviews. However, morphological analysis alone is not sufficient for advanced studies, and to draw conclusions beyond morphology, chemical analysis is needed. While conventional SEM-based chemical analysis techniques such as energy-dispersive X-ray spectroscopy (EDS) are adequate in many cases, they are not well suited for the analysis of trace elements and low-Z elements such as hydrogen or lithium. Furthermore, the large information depth in typical SEM-EDS imaging conditions limits the lateral resolution to micrometer length scales. In contrast, secondary ion mass spectrometry (SIMS) can perform elemental mapping with good surface sensitivity, nanoscale lateral resolution, and the possibility to analyze even low-Z elements and isotopes. In this study, we demonstrate the feasibility and compatibility of a novel FIB-SEM-based correlative nanoCT-SIMS imaging approach to correlate morphological and chemical data of the exact same sample volume, using a cathode material of a commercial lithium battery as an example.

A Deep Learning Method for the Impact Damage Segmentation of Curve-Shaped CFRP Specimens Inspected by Infrared Thermography.

Advanced materials such as continuous carbon fiber-reinforced thermoplastic (CFRP) laminates are commonly used in many industries, mainly because of their strength, stiffness to weight ratio, toughness, weldability, and repairability. Structural components working in harsh environments such as satellites are permanently exposed to some sort of damage during their lifetimes. To detect and characterize these damages, non-destructive testing and evaluation techniques are essential tools, especially for composite materials. In this study, artificial intelligence was applied in combination with infrared thermography to detected and segment impact damage on curved laminates that were previously submitted to a severe thermal stress cycles and subsequent ballistic impacts. Segmentation was performed on both mid-wave and long-wave infrared sequences obtained simultaneously during pulsed thermography experiments by means of a deep neural network. A deep neural network was trained for each wavelength. Both networks generated satisfactory results. The model trained with mid-wave images achieved an F1-score of 92.74% and the model trained with long-wave images achieved an F1-score of 87.39%.

Target Design in SEM-Based Nano-CT and Its Influence on X-ray Imaging.

Nano-computed tomography (nano-CT) based on scanning electron microscopy (SEM) is utilized for multimodal material characterization in one instrument. Since SEM-based CT uses geometrical magnification, X-ray targets can be adapted without any further changes to the system. This allows for designing targets with varying geometry and chemical composition to influence the X-ray focal spot, intensity and energy distribution with the aim to enhance the image quality. In this paper, three different target geometries with a varying volume are presented: bulk, foil and needle target. Based on the analyzed electron beam properties and X-ray beam path, the influence of the different target designs on X-ray imaging is investigated. With the obtained information, three targets for different applications are recommended. A platinum (Pt) bulk target tilted by 25° as an optimal combination of high photon flux and spatial resolution is used for fast CT scans and the investigation of high-absorbing or large sample volumes. To image low-absorbing materials, e.g., polymers or organic materials, a target material with a characteristic line energy right above the detector energy threshold is recommended. In the case of the observed system, we used a 30° tilted chromium (Cr) target, leading to a higher image contrast. To reach a maximum spatial resolution of about 100 nm, we recommend a tungsten (W) needle target with a tip diameter of about 100 nm.

Material Extrusion of Structural Polymer-Aluminum Joints-Examining Shear Strength, Wetting, Polymer Melt Rheology and Aging.

Generating polymer-metal structures by means of additive manufacturing offers huge potential for customized, sustainable and lightweight solutions. However, challenges exist, primarily with regard to reliability and reproducibility of the additively generated joints. In this study, the polymers ABS, PETG and PLA, which are common in material extrusion, were joined to grit-blasted aluminum substrates. Temperature dependence of polymer melt rheology, wetting and tensile single-lap-shear strength were examined in order to obtain appropriate thermal processing conditions. Joints with high adhesive strength in the fresh state were aged for up to 100 days in two different moderate environments. For the given conditions, PETG was most suitable for generating structural joints. Contrary to PETG, ABS-aluminum joints in the fresh state as well as PLA-aluminum joints in the aged state did not meet the demands of a structural joint. For the considered polymers and processing conditions, this study implies that the suitability of a polymer and a thermal processing condition to form a polymer-aluminum joint by material extrusion can be evaluated based on the polymer's rheological properties. Moreover, wetting experiments improved estimation of the resulting tensile single-lap-shear strength.

Using Quantitative Passive Thermography and Modified Paris-Law for Probabilistic Calculation of the Fatigue Damage Development in a CFRP-Aluminum Hybrid Joint.

Although metal to Carbon-fiber-reinforced-polymer (CFRP) hybrid-joints possess a high lightweight construction potential, their extensive application has to deal with interfacial stress concentrations promoting fatigue damage. Furthermore, the underlying damage processes and their influencing factors are still not completely understood. Besides interfacial property-gradients, generic shapes counteract a precise determination of local stresses or strains, respectively. Hence, new methods are required that combine non-destructive testing and fracture mechanics to account for the fatigue damage. In this work, data of mechanical fatigue testing of an aluminum-CFRP hybrid-structure is presented by means of the dynamic stiffness and the mechanical hysteresis. Additionally, in situ passive thermography allows for capturing the heat development due to delamination growth. Correlating the obtained data implies that faster delamination growth coincides with higher amplitude values of lock-in thermography and higher mechanical hysteresis. Supported by this observation, a model is formulated to calculate the local dissipation per loading cycle. Further integration into a Paris-law like formulation results in a calculation model to account for the mode-I fatigue delamination growth. Additional validation of the model parameters shows good agreement with the experimental data.

Characterisation and Modelling of Moisture Gradients in Polyamide 6.

Polyamide 6 (PA6) is able to absorb water from the surrounding air and bond to it by forming hydrogen bonds between the carbonamide groups of its molecular chains. Diffusion processes cause locally different water concentrations in the (component) cross-section during the sorption process, resulting in locally different mechanical properties due to the water-induced plasticisation effect. However, the water content of PA6 is usually specified as an integral value, so no information about a local water distribution within a component is provided. This paper shows a method to characterise moisture distributions within PA6 samples using low-energy computer tomography (CT) techniques and comparing the reconstructed results with a developed finite elements (FE) modelling method based on Fick's diffusion laws with concentration-dependent diffusion coefficients. For this purpose, the ageing of the samples at two different water bath temperatures as well as at different integral water contents are considered. The results obtained by CT reconstruction and FE modelling are in very good agreement, so that the concentration distributions by water sorption of PA6 calculated by FEM can be regarded as validated.

Estimation of the Adhesion Interface Performance in Aluminum-PLA Joints by Thermographic Monitoring of the Material Extrusion Process.

Using additive manufacturing to generate a polymer-metal structure offers the potential to achieve a complex customized polymer structure joined to a metal base of high stiffness and strength. A tool to evaluate the generated interface during the process is of fundamental interest, as the sequential deposition of the polymer as well as temperature gradients within the substrate lead to local variations in adhesion depending on the local processing conditions. On preheated aluminum substrates, 0.3 and 0.6 mm high traces of polylactic acid (PLA) were deposited. Based on differential scanning calorimetry (DSC) and rheometry measurements, the substrate temperature was varied in between 150 and 200 °C to identify an optimized manufacturing process. Decreasing the layer height and increasing the substrate temperature promoted wetting and improved the adhesion interface performance as measured in a single lap shear test (up to 7 MPa). Thermographic monitoring was conducted at an angle of 25° with respect to the substrate surface and allowed a thermal evaluation of the process at any position on the substrate. Based on the thermographic information acquired during the first second after extrusion and the preset shape of the polymer trace, the resulting wetting and shear strength were estimated.