Artificial neural network approach for microhardness prediction of eight component FeCoNiCrMnVAlNb eutectic high entropy alloys

Abstract For the first time, we report here that higher-order eight component Fe32.5-xCo10Ni25Cr15Mn5V10Al2.5Nbx (x = 5, 7.5, 10, and 12.5 at. %) eutectic high entropy alloys (EHEAs) are designed and developed by integrating thermodynamic simulation approach and non-equilibrium solidification processing technique. The developed EHEAs consist of FeCoNiCr-rich FCC solid solution phase and eutectics mixture between FCC solid solution phase and the Co2Nb-type Laves phase. The predicted microhardness of EHEAs for x = 7.5% and x = 10% by using artificial neural networks (ANNs) modeling is 501 H V and 618 H V, respectively, which is in good agreement with experimentally measured values having less than 5% error.