DaKS - University of Kassel's research data repository

Polyamides are known for their chemical resistance and are commonly used as matrix materials in glass fiber-reinforced composites (GFC) for automotive applications such as fuel caps and housings. To assess the potential of natural fiber-reinforced composites (NFC) as alternatives, this study investigates the chemical resistance of a bio-based polyamide (PA5.10) reinforced with regenerated cellulose fibers (RCF). Composites containing 20 wt.% RCF were produced using twin-screw extrusion, and standardized type 1A test specimens were injection molded. These were exposed to various fluids (distilled water, salt water, soap water, acid rain, rubbing alcohol, engine oil, ethanol, sodium hydroxide solution, and 2-propanol) for up to 168 hours. Subsequent analyses included tensile testing, FTIR spectroscopy, MVR, moisture measurements, and SEM imaging. Results revealed significant hydrolytic degradation, indicated by FTIR and decreased viscosity. Degradation was especially pronounced in acidic and alkaline media. A strong link was observed between increased moisture uptake and reduced mechanical properties. Chemical exposure led to notable damage in RCF composites, attributed to the moisture absorption of RCF and fiber degradation, as confirmed by SEM images. Loss of fiber-matrix adhesion further contributed to substantial declines in tensile strength and Young’s modulus. These findings highlight limitations in chemical resistance for RCF-reinforced bio-based polyamides, especially under harsh environmental conditions.

This data set consists of the measured data from the conducted experiments as well as the data analysis.
In case you use the data please cite the corresponding article. The corresponding publication is currently in publication process.

Every new material needs to be assessed and qualified for an envisaged application. A steadily increasing number of new alloys, designed to address challenges in terms of reliability and sustainability, poses significant demands on well-known analysis methods in terms of their efficiency, e.g., in X-Ray diffraction analysis. Particularly in laboratory measurements, where the intensities in diffraction experiments tend to be low, a possibility to adapt the exposure time to the prevailing boundary conditions, i.e., the investigated microstructure, is seen to be a very effective approach. The counting time is decisive for, e.g., complex texture, phase, and residual stress measurements. Traditionally, more measurement points and, thus, longer data collection times lead to more accurate information. Here, too short counting times result in poor signal-to-background ratios and dominant signal noise, respectively, rendering subsequent evaluation more difficult or even impossible. Then, it is necessary to repeat experiments with adjusted, usually significantly longer counting time. To prevent redundant measurements, it is state-of-the-art to always consider the entire measurement range, regardless of whether the investigated points are relevant and contribute to the subsequent materials characterization, respectively. Obviously, this kind of approach is extremely time consuming and, eventually, not efficient. All relevant data including the code are carefully assessed and will be the basis for a widely adapted strategy enabling efficient measurements not only in lab environments but also large scale facilities.

This data set consists of the fully measured data from the diffraction experiments as well as the manuscript for data analyzing.

IMPORTANT: In case you use the data please cite our corresponding article: https://doi.org/10.1038/s41598-025-96221-1