The purpose of the research was to obtain an arc welded joint of a preliminary quenched high-carbon wear resistant steel without losing the structure that is previously obtained by heat treatment. 120Mn3Si2 steel was chosen for experiments due to its good resistance to mechanical wear. The fast cooling of welding joints in water was carried out right after welding. The major conclusion is that the soft austenitic layer appears in the vicinity of the fusion line as a result of the fast cooling of the welding joint. The microstructure of the heat affected zone of quenched 120Mn3Si2 steel after welding with rapid cooling in water consists of several subzones. The first one is a purely austenitic subzone, followed by austenite + martensite microstructure, and finally, an almost fully martensitic subzone. The rest of the heat affected zone is tempered material that is heated during welding below A₁ critical temperature. ISO 4136 tensile tests were carried out for the welded joints of 120Mn3Si2 steel and 09Mn2Si low carbon steel (ASTM A516, DIN13Mn6 equivalent) after welding with fast cooling in water. The tests showed that welded joints are stronger than the quenched 120Mn3Si2 steel itself. The results of work can be used in industries where the severe mechanical wear of machine parts is a challenge.

The deposition of a thin (several tens of microns) protective coating in atmospheric conditions is a challenging task for surface engineering. The structural features and tribological properties of a particle-reinforced metal matrix composite coating synthesized on middle-carbon steel by air pulse-plasma treatments were studied in the present work. The 24–31 µm thick coating of “24 vol.% (TiC + WC)/Hardened steel matrix” was produced by 10 plasma pulses generated by an electro-thermal axial plasma accelerator equipped with a consumable cathode of novel design (low-carbon steel tube filled with “TiC/WC + Epoxy resin” mixture). The study included optical microscopy (OM), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD, microhardness measurements, and dry “Ball-on-Plate” testing. The carbides were directly plasma-transferred to the substrate (steel of AISI 4145H grade) from the cathode without substantial melting. The hard (500–1044 HV) coating matrix consisted of 57 vol.% austenite (1.43 wt.% C) and 43 vol.% plate martensite was formed via carbon enrichment of steel from plasma flow. Additionally, a minor amount of oxide phases (TiO₂, WO₂, WO₃) were dispersed in the matrix. As compared to substrate, the coating had a lower coefficient of friction; its volumetric wear was decreased by 4.4 times when sliding against hardened steel ball and by 16 times when sliding against SiC ball.

The structural features and nanoindentation/tribological properties of 316 stainless steel fabricated by conventional rolling and laser-based powder bed fusion (LPBF) were comparatively investigated regarding the effect of surface-pulsed plasma treatment (PPT). PPT was performed using an electrothermal axial plasma accelerator under a discharge voltage of 4.5 kV and a pulse duration of 1 ms. Optical microscopy, scanning electron microscopy, X-ray diffraction, nanoindentation measurements and tribological tests were applied to characterize the alloys. The LPBF steel presented almost the same modulus of elasticity and double the hardness of rolled steel. However, the LPBF steel manifested lower dry-sliding wear resistance compared with its wrought counterpart due to its porous structure and non-metallic inclusions. Conversely, LPBF steel showed three times higher wear resistance under sliding in simulated body fluid (SBF), as compared with wrought steel. PPT led to steel modification through surface melting to a depth of 22–26 μm, which resulted in a fine cellular structure. PPT moderately improved the dry-sliding wear resistance of LPBF steel by fusion of pores on its surface. On the other hand, PPT had almost no effect on the SBF-sliding wear response of the steel. The modification features were analyzed using a computer simulation of plasma-induced heating.

This article aims to discusses machine learning modelling using a dataset provided by the LANL (Los Alamos National Laboratory) earthquake prediction competition hosted by Kaggle. The data were obtained from a laboratory stick-slip friction experiment that mimics real earthquakes. Digitized acoustic signals were recorded against time to failure of a granular layer compressed between steel plates. In this work, machine learning was employed to develop models that could predict earthquakes. The aim is to highlight the importance and potential applicability of machine learning in seismology The XGBoost algorithm was used for modelling combined with 6-fold cross-validation and the mean absolute error (MAE) metric for model quality estimation. The backward feature elimination technique was used followed by the forward feature construction approach to find the best combination of features. The advantage of this feature engineering method is that it enables the best subset to be found from a relatively large set of features in a relatively short time. It was confirmed that the proper combination of statistical characteristics describing acoustic data can be used for effective prediction of time to failure. Additionally, statistical features based on the autocorrelation of acoustic data can also be used for further improvement of model quality. A total of 48 statistical features were considered. The best subset was determined as having 10 features. Its corresponding MAE was 1.913 s, which was stable to the third decimal point. The presented results can be used to develop artificial intelligence algorithms devoted to earthquake prediction.

In the present work, we have used unconventional short-term secondary recrystallization heat treatment employing extraordinary high heating rate to develop coarse-grained microstructure with enhanced intensity of rotating cube texture {100} in semi-finish vacuum degassed non-oriented electrical steels. The soft magnetic properties were improved through the increase of grains size with favourable cube crystallographic orientation. The appropriate final textural state of the treated experimental steels was achieved by strain-induced grain boundary migration mechanism, activated by gradient of accumulated stored deformation energy between neighbouring grains after the application of soft cold work, combined with steep temperature gradient during subsequent heat treatment under dynamic heating conditions. The materials in our experimentally prepared material states were mounted on the stator and rotor segments of electrical motors and examined for their efficiency in real operational conditions. Moreover, conventionally long-term heat treated materials, prepared in industrial conditions, were also tested for reference. The results show that the electrical motor containing the segments treated by our innovative approach, exhibits more than 1.2% higher efficiency, compared to the motor containing conventionally heat treated materials. The obtained efficiency enhancement can be directly related to the improved microstructural and textural characteristics of our unconventionally heat treated materials, specifically the homogenous coarse grained microstructure and the high intensity of cube and Goss crystallographic texture.

The present study deals with the effects of laser surface treatment on microstructure evolution and wear resistance of AISI H11 hot work tool steel in quenched and tempered condition. The most upper laser-affected zone is characterized by re-melted microstructure consisting of dendrite cells with fresh non-tempered martensite, retained austenite and inter-dendritic carbidic network. The subsolidus microstructure just beneath the re-melted zone represents the most laser surface hardened zone consisting of fresh non-tempered martensite with fine and coarse carbides as a result of overheating the original QT substrate microstructure. The highest microhardness values in the range from 775 to 857 HV were measured for the LSH microstructure and the most softened microstructure exhibited the minimum hardness of 530 HV. The laser treated samples showed the improvement of their surface wear resistance by 35%.