Process–structure–property relationships in bimodal machined microstructures using robust structure descriptors

• Published in: Journal of materials processing technology Vol. 273; no. C; p. 116251
• Main Authors: Fernandez-Zelaia, Patxi, Melkote, Shreyes N.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.11.2019; Elsevier BV; Elsevier
• Subjects: Anisotropy; Cooling rate; Cutting speed; Deformation effects; Ductility; Dynamic recrystallization; Grain refinement; Grain structure; High temperature; Machining; Mapping; Materials informatics; MATERIALS SCIENCE; Microstructure characterization; Microstructure evolution; Nanoindentation; Plastic deformation; Severe plastic deformation; Shear deformation; Temperature effects; Thermal stability; Microstructure characterization; Severe plastic deformation; Materials informatics; Microstructure evolution; Machining; Nanoindentation
• ISSN: 0924-0136; 1873-4774; 1873-4774
• DOI: 10.1016/j.jmatprotec.2019.116251

Machining is a severe plastic deformation process that subjects materials to high rates of deformation and elevated temperatures. Dynamic recrystallization during severe plastic deformation drives grain refinement into the sub-micron range but the ductility and thermal stability of these structures is poor. In contrast, bimodal microstructures consisting of both fine and coarse grains have been shown to exhibit attractive strength and ductility properties at these temperatures. In this paper, we study the process–structure–property relationships for pure copper subject to a machining process where the cutting speeds are varied. Further, we investigate the role of thermal effects by varying the post-deformation cooling rates. Microstructures generated under these deformation conditions are quantified using angularly resolved chord length statistics. The derived metrics are found to be robust descriptors of the studied microstructures as they automatically capture complex features such as unimodal and bimodal distributions of grain structure, grain constituent length scales, and morphological anisotropy induced by shear deformation. The uniaxial equivalent yield strength of the generated structures are estimated using spherical nanoindentation and inverse modeling techniques. Finally, we present a methodology for identifying the constrained property-process inverse mapping for machining using a Bayesian framework and the established forward process–structure–property mapping.