## 5 Results and Discussion
Figure 6: The coverage speed and maximum coverage after 50 min and 150 min through the microchamber for the original experimental setup (case A-01), thin chamber (series H-02), the thin chamber with half-height (case H-03), second outlet with zero pressure (case S-04), suction (case S-05), and electroosmotic flow (cases E-06 and E-07). All values are calculated based on the original case. For the S series, the pressure at the end of the second outlet is varied from 0 to \(-2\)\(pa\). For the sake of brevity, only cases S-04 and S-05 are presented in this paper. In Figure 5b, by the end of 50 min, cases S-04 and S-05 show 6% and 10% enhancement in the surface coverage, respectively. It is worth noting that the fabrication of the first case would be simple and would not add any extra cost, while in the second case, the device must be equipped with a suction. In the E series, the electroosmotic flow starts with the applied electric field. Diffusion would be sufficient for the rapidly diffusive species. However, other methods could enhance the bio-recognition process for nucleic acids and proteins with high molecular weight. For the first type of species (lightweight), diffusion would occur in a matter of seconds over the microchamber, although for the second type, the required time for equilibration would be from minutes to hours. Hence, active approaches, such as electroosmotic flow, would be beneficial for DNA hybridization. After 5 min, case E-06 has 16% more surface coverage (Figures 5 and 6), while in comparison to E-06, increasing the electric potential in E-07 negatively affects the speed of surface coverage. This might be caused by the position of the electrodes, which is where optimization methods can play a role in improving the outcome. This effect is evident in the results presented in Figure 4. Full surface coverage of one of the functionalized surfaces (number 2 in Table 2), the surface coverage of its front (\(Pt_{f}\)) and its back (\(Pt_{b}\)) are demonstrated in Figure 4a-c, respectively. The effect of electroosmotic flow is almost negligible in \(Pt_{f}\), as it has more distance from the electrodes. Benefit of the electroosmotic flow is more evident in the second part of the test, while the flow has stopped (Figure 4a) since, in other cases, the surface coverage remains almost the same in the second stage. It is also worth mentioning that in order to obtain an optimum design for the biosensors considered here, a full set of parametric studies need to be carried out, similar to those commonly used in conjunction with Computational fluid dynamics (CFD). In recent years, CFD has successfully been applied to numerous biomedical-related projects involving design, validation and proof-of-concept; some examples from the present authors include [32; 33; 34; 35; 36; 37]. Making use of more advanced design optimization techniques is one of the main future works, which the authors are pursuing at the moment. Figure 7: The maximum pressure through the microchamber for the original experimental setup (case A-01), thin chamber (series H-02), the thin chamber with half-height (case H-03), second outlet with zero pressure (case S-04), suction (case S-05), electroosmotic flow (cases E-06 and E-07).