Phase Transformation after Heat Treatment of Cr-Ni Stainless Steel Powder for 3D Printing.

Today, Ni-Cr steel is used for advanced applications in the high-temperature and electrical industries, medical equipment, food industry, agriculture and is applied in food and beverage packaging and kitchenware, automotive or mesh. A study of input steel powder from various stages of the recycling process intended for 3D printing was conducted. In addition to the precise evaluation of the morphology, particle size and composition of the powders used for laser 3D printing, special testing and evaluation of the heat-treated powders were carried out. Heat treatment up to 950 °C in an air atmosphere revealed the properties of powders that can appear during laser sintering. The powders in the oxidizing atmosphere change the phase composition and the original FeNiCr stainless steel changes to a two-phase system of Fe3Ni and Cr2O3, as evaluated by X-ray diffraction analysis. Observation of the morphology showed the separation of the oxidic phase in the sense of a brittle shell. The inner part of the powder particle is a porous compact core. The particle size is generally reduced due to the peeling of the oxide shell. This effect can be critical to 3D printing processing, causing defects on the printed parts, as well as reducing the usability of the precursor powder and can also change the properties of the printed part.

Acoustic Emission Signal Characterisation of Failure Mechanisms in CFRP Composites Using Dual-Sensor Approach and Spectral Clustering Technique.

The characterisation of failure mechanisms in carbon fibre-reinforced polymer (CFRP) materials using the acoustic emission (AE) technique has been the topic of a number of publications. However, it is often challenging to obtain comprehensive and reliable information about individual failure mechanisms. This situation was the impetus for elaborating a comprehensive overview that covers all failure mechanisms within the framework of CFRP materials. Thus, we performed tensile and compact tension tests on specimens with various stacking sequences to induce specific failure modes and mechanisms. The AE activity was monitored using two different wideband AE sensors and further analysed using a hybrid AE hit detection process. The datasets received from both sensors were separately subjected to clustering analysis using the spectral clustering technique, which incorporated an unsupervised k-means clustering algorithm. The failure mechanism analysis also included a proposed filtering process based on the power distribution across the considered frequency range, with which it was possible to distinguish between the fibre pull-out and fibre breakage mechanisms. This functionality was particularly useful in cases where it was evident that the above-mentioned damage mechanisms exhibited very similar parametric characteristics. The results of the clustering analysis were compared to those of the scanning electron microscopy analysis, which confirmed the conclusions of the AE data analysis.