Perpustakaan Digital ITB

Alloys have evolved to support civilization with improved properties and performance. High-entropy alloys (HEAs), containing at least five elements each ranging from 5 to 35 at.% and a ?Smix ? 1.5R, show promising mechanical properties. CoCrFeMnNi HEA, the first ever found HEA, is known for its excellent mechanical properties, making it suitable for high-temperature aerospace and nuclear applications, room-temperature electronics, biomedic, and coating, and low-temperature LNG storage. Hardness, an essential alloy property, is related to stacking-fault energy (SFE). Optimizing alloy composition based on SFE across wide temperatures demands extensive experimentation, necessitating a more efficient approach. This study aims to provide CoCrFeMnNi HEA design guidelines by analyzing SFE for wide compositions and temperature ranges through thermodynamic calculation and machine learning approaches, which have not been previously conducted. In this study, SFE of CoCrFeMnNi HEAs were thermodynamically calculated using the Olsen-Cohen equation in MATLAB across a compositional range of 5—40 at.% and temperatures from 1 to 1200 K. The results were analyzed to investigate the effect of element composition, temperature, and magnetic contributions on SFE and used as inputs for machine learning models—random forest (RF), support vector machine (SVM), and neural network (ANN)— trained in Google Colaboratory. Root mean square error (RMSE) and accuracy were used to determine the best model, while feature importance and Spearman correlation identified the influence and correlation of temperature and composition on SFE, leading to practical design recommendations for CoCrFeMnNi HEAs. RF, SVM, and ANN were applicable for predicting SFE. Among the models investigated, ANN emerged as the best model, with the lowest RMSE value of 1.02 and the highest accuracy of 98.8%. Overall, SFE increased with increasing temperature. Magnetic contributions are extremely high at low temperatures but decrease significantly as temperature increases. The addition of Fe and Ni elements increases SFE values, while the addition of Co, Cr, and Mn elements decreases SFE values. Therefore, the recommended compositions of CoCrFeMnNi HEA at room temperature (300 K) to achieve twinning deformation consists of 5—40 at.% Co, 5—37 at.% Cr, 13—40 at.% Fe, 5—36 at.% Mn, and 5—40 at.% Ni. The composition of the HEAs can also refer to CrFeNi(100-x-y)CoxMny, FeMnNi(100-x-y)CoxCry, and CoCrFe(100-x-y)NixMny formulas. Co16Cr36Fe16Mn16Ni16 and Co19Cr24Fe19Mn19Ni19 (high Cr), as well as Co19Cr19Fe19Mn24Ni19 and Co18Cr18Fe18Mn28Ni18 (high Mn), are examples of attractive compositions with lower SFEs than the equiatomic composition and deformation by twinning at room temperature.????