Large Scale Dynamic Molecular Modelling of Metal Oxide Nanoparticles in Engineering and Biological Fluids
Nanoparticles (NP) offer great merits over controlling thermal, chemical and physical properties when compared to their micro-sized counterparts. The effectiveness of the dispersion of the NP is the key aspect of the applications in nanotechnology. The project studies the characterization and modification of functional NPs aided by the means of large scale molecular thermal dynamic computerized dispersing simulations, in the level of Nanoclusters (NC). Carrying out NP functionality characterisation in fluids can be enhanced, and analysed through computational simulation based on their interactions with fluidic media; in terms of thermo-mechanical, dynamic, physical, chemical and rheological properties. From the engineering perspective, effective characterizations of the nanofluids have also been carried out based on the particles sizes and particle-fluids Brownian motion (BM) theory. The study covered firstly, investigation of the pure CuO NP diffusion in water and hydrocarbon fluids, secondly, examination of the modified CuO NP diffusion in water. In both cases the studies were put under experiments and simulations for data collection and comparison. For simulation the COMPASS forcefield, smoothed particle hydrodynamic potential (SPH) and discrete particle dynamics potential (DPD) were implemented through the system. Excellent prediction of BM, Van der Waals interaction, electrostatic interaction and a number of force-fields in the system were exploited. The experimental results trend demonstrated high coherence with the simulation results. At first the diffusion coefficient was found to be 1.7e-8m2/s in the study of CuO NC in water based fluidic system. Secondly highly concurrent simulation results (i.e. data for viscosity and thermal conductivity) have been computed to experimental coherence. The viscosity trend of MD simulation and experimental results show a high level of convergence for temperatures between 303-323K. The simulated thermal conductivity of the water-CuO nanofluid was between 0.6—0.75W•m−1•K−1, showing a slight increase following a rise in temperature from 303 to 323 K. Moreover, the alkane-CuO nanofluid experimental and simulated work was also carried out, for analysing the thermo-physical quantities. The alkane-CuO nanofluid viscosity was found 0.9—2.7mpas and thermal conductivity is between 0.1—0.4W•m−1•K−1. Finally, the successful modification of the NPs on experimental and simulation platform has been analysed using different characterization variables. Experimental modification data has been quantified by using Fourier Transformation Infrared (FTIR) peak response, from particular ranges of interest i.e. 1667-1609cm-1 and 1668-1557cm-1. These FTIR peaks deduced Carboxylate attachment on the surface of NPs. Later, MD simulation was approached to mimic experimental setup of modification chemistry and similar agglomerations were observed as during experimental conditions. However, this approach has not been presented before; therefore this study has a significant impact on describing the agglomeration of modified NPs on simulation and experimental basis. Henceforth, the methodology established for metal oxide nanoparticle dispersion simulation is a novelty of this work.