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Revealing surface functionalities of micro- and nanoplastic particles’ surface by means of XPS
(2024)
Over the last 20 years, many researchers, politicians, and citizens themselves have become increasingly aware of the growing plastic problem of our time. Inadequate recycling concepts, collection points, and careless dumping of plastic products in the environment lead to an accumulation of plastic. External weather influences can cause these to degrade and fractionate, so that today microplastics (1-1000 µm, ISO/TR 21960:2020) [1] of different polymer materials can be detected in all parts of the world.
The precautionary principle applies to microplastics. The particles can break down further to form nanoplastics (<1 µm, ISO/TR 21960:2020) [1]. Whether microplastics or nanoplastics pose a toxicological hazard is being investigated in a variety of ways. Valid results are still pending, however, investigations into the frequency, transport, possible sinks and entry paths must be taken into account. This is why monitoring of microplastics is already required in the revision of the Drinking Water Framework Directive [2]. The same is still pending in the final version of the revision of the Waste Water Framework Directive this year, but is expected.
Nanoplastics are particularly under discussion for having a toxic effect on humans and animals, as these particles are small enough to be absorbed by cells. For targeted toxicological studies, it is important to have test and reference materials that resemble the particles found in the environment. To mimic environmental samples, these materials should also have an irregular shape and show aging at the surface, which can be detected with XPS or SEM/EDS.
BAM in collaboration with the EMPIR project "PlasticTrace" works on a reference material candidate of nano-sized polypropylene (nano-PP) [3]. The nano-PP vials were tested for homogeneity with PTA and further characterized with bulk and surface-sensitive techniques. An SEM image and a corresponding XPS spectrum are presented in Figure 1. Raman measurements as well as XPS indicate an aged surface.
Hybrid additive manufacturing is becoming increasingly important in the field of additive manufacturing. Hybrid approaches combine at least two different manufacturing processes. The focus of this work is the build-up of geometries onto conventionally manufactured parts using laser-based powder bed fusion of metals (PBF-LB/M). The hybrid build-up requires a precise position detection system inside the PBF-LB/M machines to determine the exact position of the existing component. For this purpose, high-resolution camera systems can be utilized. However, the use of a camera system is associated with several challenges. The captured images are subject to various distortions of the optical path. Due to these distortions, it is not possible to use the images for measurements and, therefore, it is not possible to calculate the positions of objects. In this study a homography matrix is calculated to correct keystone distortion in the images. Different calibration patterns have been tested for the calculation of the homography matrix. The influence of the number of calibration points on the precision of position detection of objects is determined. Furthermore, the influence of an additional camera calibration by using ChArUco boards is evaluated. The result is a camera calibration workflow with associated calibration pattern for a precise position detection of parts inside PBF-LB/M machines allowing a hybrid build-up with minimum physical offset between base component and build-up.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
This poster presents an approach to create and maintain a comprehensive and intuitive MSE-centric terminology by developing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.