A novel equal atomic Ni–Al-Ti-Mn-Co-Fe–Cr high entropy alloy (HEA) was developed via the spark plasma sintering (SPS) process. This study investigates the influence of the sintering parametric processes, which consist of the sintering temperature (ST) and heating rate (HR) at constant pressure and dwelling time (DT) on the Microhardness (MH) and relative density (RD) of the developed HEA. Response surface methodology (RSM) was used to develop a predictive model. The design of experiment (DOE) approach was adopted to reduce the number of experiments and eliminate trial by error. ST and HR were considered model variables in developing the model. The user-defined design (UDD) under RSM was used to predict the optimal sintering parameters, and an experiment was conducted to validate the result. The result indicates that ST and HR play a significant role in achieving high densification and hardness. The developed alloy shows the highest MH value of 136.3 HV at 850 °C and an HR of 100 °C/min. Equally, the least crystallite size of 2.05 µm was realized at the maximum ST. However, the modeling response suggested that full densification of about 99% can be achieved at an ST of 850 °C, a pressure of 50 MPa, a DT of 5 min, and an HR of 100 °C/min.

The effect of mechanical alloying on the development of Ni–Al–Ti–Mn–Co–Fe–Cr high entropy alloys (HEAs) utilizing the spark plasma sintering (SPS) method is the main goal of this study. A bulk sample was fabricated using SPS after the alloys were mixed for 12 h. Thermodynamic simulation, X-ray diffraction, scanning electron microscopy, nanoindentation, and microhardness were used to investigate the microstructure and mechanical properties of the as-mixed powders. The master alloy was made of NiAl and was subsequently alloyed with Ti, Mn, Co, Fe, and Cr at different compositions to develop HEAs at a sintering temperature of 850 °C, a heating rate of 100 °C/min, a pressure of 50 MPa, and a dwelling time of 5 min. A uniform dispersion of the alloying material can be seen in the microstructure of the sintered HEAs with different weight elements. The grain size analysis shows that the Ni₂₅Al₂₅Ti₈Mn₈Co₁₅Fe₁₄Cr₅ alloy exhibited a refined structure with a grain size of 2.36 ± 0.27 µm compared to a coarser grain size of 8.26 ± 0.43 μm attained by the NiAl master alloy. Similarly, the HEAs with the highest alloying content had a greater microstrain value of 0.0449 ± 0.0036, whereas the unalloyed NiAl had 0.00187 ± 0.0005. Maximum microhardness of 139 ± 0.8 HV, nanohardness of 18.8 ± 0.36 GPa, elastic modulus of 207.5 ± 1.65 GPa, elastic recovery (W_e/W_t) of 0.556 ± 0.035, elastic strain to failure (H/E_r) of 0.09.06 ± 0.0027, yield pressure (H³/ $$E_{{\text{r}}}^{2}$$E r 2 ) of 0.154 ± 0.0055 GPa, and the least plasticity index (W_p/W_t) of 0.444 ± 0.039 were attained by Ni₂₅Al₂₅Ti₈Mn₈Co₁₅Fe₁₄Cr₅. A steady movement to the left may be seen in the load–displacement curve. Increased resistance to indentation by the developed HEAs was made possible by the increase in alloying metals, which ultimately led to higher nanohardness and elastic modulus.

In this study, the influence of operating parameters on the mechanical properties of Dual Phase (DP) steels was investigated, using response surface methodology (RSM) to develop a prediction model. In developing the model, temperature and holding time were considered as the model variables. To establish this fact, an experiment based on statistical four-level two factorial design method was carried out. Based on the statistical analysis, surface hardness (SH) shows a correlation coefficient of R2= 0.9607 while Ultimate Tensile strength (UTS) gave R2= 0.9297, this suggests that the proposed quadratic model is suitable for use. The optimum operating parameters were predicted using the user-defined design (UDD) under RSM and the result was confirmed through experiments, which predict at a temperature (T) of 800oC and holding time (HT) of 60 minutes, hardness value was given as 157.798HV and UTS as 553.648Mpa. This result indicates that RSM is a suitable method to optimize the process variables for mechanical properties of DP steels.