Gradient Microstructure and Texture Formation in a Metastable Austenitic Stainless Steel during Cold Rotary Swaging.

The paper aimed to study the evolution of the microstructure and texture gradient of a 321-type metastable austenitic stainless steel during cold rotary swaging. Cold rotary swaging was carried out with a reduction of up to 90% at ambient temperature. Pronounced gradients of the α'-martensite volume fraction, the axial texture of austenite (⟨111⟩ and ⟨001⟩) and α'-martensite (⟨101⟩), and non-uniform microhardness distribution along the rod diameter were obtained after a reduction of 80-90%. According to the finite element analysis, moderate tensile stresses were attained in the center, whereas high compressive stresses operated at the edge. Due to water cooling of the rod surface and heating of the rod center during processing, a temperature gradient was also derived. Features of strain-induced martensitic transformation, microstructure and texture evolution, and non-uniform hardening during cold rotary swaging were discussed.

Effect of Cold Swaging on the Bulk Gradient Structure Formation and Mechanical Properties of a 316-Type Austenitic Stainless Steel.

The present study aimed to discover the effect of cold swaging reduction on the bulk gradient structure formation and mechanical properties of a 316-type austenitic stainless steel. The initial rod was subjected to radial swaging until 20-95% reduction of initial rod diameter, at room temperature. According to finite element simulation, higher plastic strain was accumulated in the surface layer compared to the center region during swaging. Microstructural investigations revealed three-stage gradient structure formation in the center and edge regions of the deformed rod. Meanwhile, cold swaging resulted in the development of strong 111ǁBA, 001ǁBA, and weak 111ǁBA texture components in the center and edge, respectively. Significant tensile strengthening was observed after cold swaging. For instance, the yield strength (YS) increased from 820 MPa to 930 MPa after 40-80% reduction respectively, without the loss of ductility (δ-14%). This unique aspect of the mechanical behavior was attributed to the gradient structure of the cold swaged material and explained in detail.

Machine Learning-Based Strength Prediction for Refractory High-Entropy Alloys of the Al-Cr-Nb-Ti-V-Zr System.

The aim of this work was to provide a guidance to the prediction and design of high-entropy alloys with good performance. New promising compositions of refractory high-entropy alloys with the desired phase composition and mechanical properties (yield strength) have been predicted using a combination of machine learning, phenomenological rules and CALPHAD modeling. The yield strength prediction in a wide range of temperatures (20-800 °C) was made using a surrogate model based on a support-vector machine algorithm. The yield strength at 20 °C and 600 °C was predicted quite precisely (the average prediction error was 11% and 13.5%, respectively) with a decrease in the precision to slightly higher than 20% at 800 °C. An Al13Cr12Nb20Ti20V35 alloy with an excellent combination of ductility and yield strength at 20 °C (16.6% and 1295 MPa, respectively) and at 800 °C (more 50% and 898 MPa, respectively) was produced based on the prediction.