A technique for characterizing microsegregation in multicomponent alloys and its application to single-crystal superalloy castings

Instrumental errors in microsegregation measurements multicomponent alloys complicate the treatment of randomly sampled data. In this article, two new alloy-independent data treatment algorithms are presented that are capable of separating the effects of scatter in the data from the underlying segregation trends, assigning each measurement location a unique fraction solid. These new methods are physically reasonable and result in improved estimates of segregation parameters, particularly the solute partitioning at the dendrite tip. This is demonstrated by determining the microsegregation in four successive generations of single-crystal (SX) nickel-based superalloys. Artificial, noise-induced, tails commonly seen in the microsegregation profiles are also minimized. A methodology for evaluating sorting schemes is introduced that does not depend upon a priori knowledge of the partitioning direction. Comparison is made to both other sorting methods and CALPHAD predicted partition coefficients. Implications for alloy design are reported, illustrating the interaction between solute species such as Ru, Re, Co, and W.