Boiling Heat Transfer Evaluation in Nanoporous Surface Coatings

The present study develops a deep learning method for predicting the boiling heat transfer coefficient (HTC) of nanoporous coated surfaces. Nanoporous coated surfaces have been used extensively over the years to improve the performance of the boiling process. Despite the large amount of experimental data on pool boiling of coated nanoporous surfaces, precise mathematical-empirical approaches have not been developed to estimate the HTC. The proposed method is able to cope with the complex nature of the boiling of nanoporous surfaces with different working fluids with completely different thermophysical properties. The proposed deep learning method is applicable to a wide variety of substrates and coating materials manufactured by various manufacturing processes. The analysis of the correlation matrix confirms that the pore diameter, the thermal conductivity of the substrate, the heat flow, and the thermophysical properties of the working fluids are the most important independent variable parameters estimation under consideration. Several deep neural networks are designed and evaluated to find the optimized model with respect to its prediction accuracy using experimental data (1042 points). The best model could assess the HTC with an R2 = 0.998 and (mean absolute error) MAE% = 1.94.

Feasibility of Using H3PO4/H2O2 in the Synthesis of Antimicrobial TiO2 Nanoporous Surfaces

Ti6Al4V alloys are the primary materials used for clinical bone regeneration and restoration; however, they are substantially susceptible to biomaterial-related infections. Therefore, in the present work, we applied a controllable and stable oxidative nanopatterning strategy by applying H3PO4, a weaker dissociating acid, as a substitute for H2SO4 in the classical piranha reaction. The results suggest that our method acted as a concomitant platform to develop reproducible diameter-controlled TiO2 nanopores (NPs). Interestingly, our procedure illustrated stable temperature reactions without exothermic responses since the addition of mixture preparation to the nanopatterning reactions. The reactions were carried out for 30 min (NP14), 1 h (NP7), and 2 h (NP36), suggesting the formation of a thin nanopore layer as observed by Raman spectroscopy. Moreover, the antimicrobial activity revealed that NP7 could disrupt active microbial colonization for 2 h and 6 h. The phenotype configuration strikingly showed that NP7 does not alter the cell morphology, thus proposing a disruptive adhesion pathway instead of cellular lysis. Furthermore, preliminary assays suggested an early promoted osteoblasts viability in comparison to the control material. Our work opens a new path for the rationale design of nanobiomaterials with “intelligent surfaces” capable of decreasing microbial adhesion, increasing osteoblast viability, and being scalable for industrial transfer.

Separating Wickability and Wetting Effects During Water Droplet Evaporation on Superhydrophilic Nanoporous Surfaces

The dynamic behavior of impinging water droplets is studied in the context of varying surface wettability and wickability on smooth and nanostructured superhydrophilic surfaces. This study distinguishes the separate effects of wetting (contact angle), wickability, and inertia on the spreading and vaporization of water droplets deposited on nanoporous surfaces by considering experimental results in tandem with axisymmetric, volume of fluid (VOF) simulations of droplet spreading. High speed videos were obtained for water droplets spreading on nanoporous surfaces which exhibit very low (< 15°) contact angle and high wickability. In this study, the effect of wickability was assessed by comparing the experimental results, which include the low contact angle and high wickability effects, to predictions of the VOF model, which include only the ultralow contact angle. While a droplet touched to the nanostructured surface demonstrates spreading driven by wicking, droplets which hit the surface with a non-zero impact velocity demonstrate spreading characteristics similar to the smooth surface, which are driven by inertia and ultra-low contact angle. The presence of the nanoporous layer impacts the equilibrium position of the contact line and the final spread radius changes with impact velocity on the nanostructured surface. These results provide fundamental input for modeling of spray cooling systems with nanostructured surfaces.