No abstract

No abstract

In this study, AlCoCrFeNi-TiCx ([Formula: see text] values in molar ratio, [Formula: see text], 0.1, 0.2, 0.3) high-entropy alloy coatings (HEAcs) were prepared on the surface of H13 steel by laser cladding (LC). The microhardness, corrosion resistance, and wear resistance of the HEAcs were analyzed using a microhardness tester, electrochemical workstation, and friction and wear tester, respectively. The results showed that with an increase in the TiC content of the coatings, the interior of the coatings mainly consisted of disordered body-centered cubic (BCC), ordered BCC (B2), and TiC phases, and lattice distortion occurred inside the coatings. TiC was distributed as white particles at the grain boundaries, and the internal microstructure was mainly composed of equiaxed crystals (EC) and petal-like dendrites. The EC were gradually refined owing to the pinning effect. The spinodal decomposition causes a large number of reticulated microstructures inside the grains, and nanoscale TiC precipitation appears in the reticulated microstructures. Owing to lattice distortion and solid solution strengthening, the microhardness of the TiC[Formula: see text] coating was up to 966 HV[Formula: see text], which was approximately 3.2 times that of the substrate. As the TiC content increases, the friction coefficient and mass loss of the coatings gradually decreased, the self-corrosion current ([Formula: see text] gradually decreased and the self-corrosion potential ([Formula: see text] gradually increased. The coatings exhibited good wear and corrosion resistance.

The relationship between the microstructure and mechanical properties of lightweight Al-containing medium-Mn steel with different annealing times was investigated. The results show that the microstructures of the tested steels treated by the I-Q&P process with varying times of annealing are all composed of martensite, α-ferrite, δ-ferrite, and retained austenite. With extended annealing times, the tested steel's martensite/ferrite microstructure exhibits a variety of size and morphological changes. Simultaneously, retained austenite nucleates and grows at high-angle grain boundaries in ferrite/martensite, exhibiting multi-sized, multi-morphology, and diffuse distribution. With appropriate short annealing times, we achieved improved overall mechanical properties for lightweight Al-containing medium manganese steels than with long annealing times. It allows the tested steel to reach a tensile strength of 1000 MPa, an elongation of 48%, and the product of strength and elongation of 48 GPa•%. At this point, the tested steel shows the best overall mechanical properties.

Alkali metals are widely used as industrial materials in products such as electrochemical cells because of their properties that make them suited to high temperatures. In this study, three computational approaches including gene expression programming (GEP), least squares support vector machine (LSSVM), and adaptive neuro fuzzy inference system (ANFIS) have been suggested to estimate density of different liquid alkali metals in extensive ranges of pressure and temperature. An experimental databank involving 595 experimental alkali metals’ densities has been gathered to prepare and test the models. The mathematical and visual comparisons of these models’ outputs and real density values are used to assess capacities of GEP, LSSVM, and ANFIS models in prediction of alkali metals’ density. The determined R-squared values for GEP, LSSVM, and ANFIS are 0.9999, 1, and 1, respectively. The MSE values are estimated to be 0.9184, 0.815, and 0.154 for GEP, ANFIS, and LSSVM, respectively. According to these results, these models can be suggested as simple and accurate ways for determining alkali metals’ properties. Results showed that LSSVM has the best performance in comparison with GEP and ANFIS. Moreover, the parametric analysis of input parameters is carried out to show the impact of them on alkali metals’ density. According to this analysis, the amount of lithium can be the most effective parameter on the mixture density.