The Importance of CALPHAD-based Scheil Solidification Models
Solidification is an essential part of many manufacturing processes such as casting, welding, and additive manufacturing. Microstructure evolution for a solidifying alloy is generally governed by material chemistry and the transport of mass and heat near the solidification front. For most manufacturing processes that involve solidification, the transition of an alloy from liquid to solid rarely, if ever, occurs under conditions of full diffusional (global) equilibrium. This can result in several issues, such as solute segregation across the solidifying microstructure, stabilization of secondary phases along solidification grain boundaries, and transformation temperatures differing from phase diagram predictions for a given alloy chemistry.
The departure from global equilibrium has implications during both the solidification process and during subsequent manufacturing steps. For example, solute segregation and the formation of secondary phases at the end of solidification often contribute to solidification crack formation. Adjustments to processing conditions and/or alloy chemistry are often needed to establish a suitable process window to avoid such defects. Even when solidification cracks do not form, an as-solidified component may require heat treatment to eliminate residual microsegregation, dissolve undesirable phases, and/or precipitate new phases to meet service requirements. The required heat treatment schedules in these cases are generally dictated by the condition of the as-solidified microstructure.
CALPHAD-based Scheil solidification models are often used to predict the solidification temperature range, segregation profiles, and phase evolution during cellular or dendritic solidification of multicomponent alloy chemistries. While appropriate for many material systems and solidification conditions, situations exist where the underlying assumptions of the original Scheil model do not sufficiently capture actual solidification behavior. As such, derivative models have been developed to address these situations.