*7.4. Local Density of Motile Microorganisms*

The effects of (δ), (*Pe*), and (*Lb*) on Local density of motile microorganism's profile *h*(η) appear in Figures 17–19. The impact of bio-convection constant δ on *h*(η) is shown in Figure 17. The higher value of δ reduces *h*(η) for both Maxwell micropolar nanotubes. The influences of *Pe* and *Lb* are presented in Figures 18 and 19. Decreasing behavior are observed for both *Lb* and *Pe*.

**Figure 17.** The variation of the local density of motile microorganisms *h*(η) for the case of SWCNT and MWCNT versus the similarity variable for the distinct values of the bio-convection constant δ.

**Figure 18.** The variation of the local density of motile microorganisms *h*(η) for the case of SWCNT and MWCNT versus the similarity variable for the distinct values of the bio-convection Peclet number *Pe*.

**Figure 19.** The variation of the local density of motile microorganisms *h*(η) for the case of SWCNT and MWCNT versus the similarity variable for the distinct values of the bio-convection Lewis number *Lb*.

## *7.5. Entropy Optimization*

The meddled parameters ξ, λ, α, *Rax*, *K*, and *Br* on *NG* are exposed in Figures 20–25. Figures 20 and 21 illustrate the variation of ξ and λ on *NG*. The increasing value of concentration difference ξ and diffusive constant λ enhances the entropy *NG* of the nanofluid of SWCNTS and MWCNTS. The Significant effects of α on *NG* are illustrated in Figure 22. For a higher value of parameter α the entropy *NG* is found as decreasing function. Figures 23 and 24 show the impact of Reynold number *Rax* and micro rotation parameter *K.* Entropy optimization of CNTs nanofluid increases with increasing of *Rax* and *K*. In Figure 25 the impact of Brinkman number *Br* is introduced. As a matter of fact, Brinkman number is a heat produced source inside the liquid moving district. The heat produced along with the heat moves from the divider and expands the entropy optimization.

**Figure 20.** The variation of the entropy optimization *NG* for the case of SWCNT and MWCNT versus the similarity variable for the distinct values of the concentration difference parameter ξ.

**Figure 21.** The variation of the entropy optimization *NG* for the case of SWCNT and MWCNT versus the similarity variable for the distinct values of the diffusive constant parameter λ.

**Figure 22.** The variation of the entropy optimization *NG* for the case of SWCNT and MWCNT versus the similarity variable for the distinct values of the temperature difference parameter α.

**Figure 23.** The variation of the entropy optimization *NG* for the case of SWCNT and MWCNT versus the similarity variable for the distinct values of the Reynold number *Rax*.

**Figure 24.** The variation of the entropy optimization *NG* for the case of SWCNT and MWCNT versus the similarity variable for the distinct values of the material parameter *K*.

**Figure 25.** The variation of the entropy optimization *NG* for the case of SWCNT and MWCNT versus the similarity variable for the distinct values of the Brinkman number *Br*.

#### *7.6. Engineering Quantities*

Performances of dissimilar engineering parameter on skin friction coefficient *CFx*, temperature gradient *Nux*, mass transfer *Shx*, and local density of motile microorganisms *Nnx* are presented in Tables 2–6. Various Thermal-physical properties of carbon nanotubes are shown in Table 2.

**Table 2.** Thermo-physical properties of base fluid and both type of carbon nanotubes (CNTs) i.e., SWCNTs and MWCNTs.


**Table 3.** Estimations of skin friction *f*(0) versus different evaluations of various parameters.



**Table 4.** Estimations of Nusselt number <sup>−</sup>*kn f <sup>k</sup>* (1 + *Rd*)θ(0) different evaluations of various parameters.

**Table 5.** Estimations of Sherwood number −*g*(0) versus different evaluations of various parameters.


**Table 6.** Values of Motile density number −*h*(0) versus various estimates of different parameters.

