  Spinodal decomposition can improve a number of essential properties in
materials, especially hardness. Yet, the theoretical prediction of the onset of
this phenomenon (e.g., temperature) and its microstructure (e.g., wavelength)
often requires input parameters coming from costly and time-consuming
experimental efforts, hindering rational materials optimization. Here, we
present a procedure where such parameters are not derived from experiments.
First, we calculate the spinodal temperature by modeling nucleation in the
solid solution while approaching the spinode boundary. Then, we compute the
spinodal wavelength self-consistently using a few reasonable approximations.
Our results show remarkable agreement with experiments and, for NiRh, the
calculated yield strength due to spinodal microstructures surpasses even those
of Ni-based superalloys. We believe that this procedure will accelerate the
exploration of the complex materials experiencing spinodal decomposition,
critical for their macroscopic properties.
