Thermodiffusion phenomenon in fluid mixtures has been investigated by several scientists in theoretical as well as experimental fields for decades. Nevertheless, due to shortcomings of both methods, interest in searching for alternative approaches to shed some light on molecular scale of the phenomenon has spurred. The objective of this thesis is to develop an accurate molecular dynamics (MD) algorithm that can predict thermodiffusive separation in binary and ternary fluid mixtures. More importantly, the proposed algorithm should be computationally efficient in order to be suitable for integration into multi-scale computational models to simulate thermodiffusion in a large system such as an oil reservoir. In developing such an effective and efficient computational tool, this thesis introduces a modified heat exchange algorithms, wherein, a new mechanism is introduced to rescale velocities which curbs the energy loss in the system and at the same time minimizes the computational time. The performance of the new algorithm in studying Soret effect for binary and ternary mixtures has been compared with other non-equilibrium molecular dynamics (NEMD) models including regular heat exchange algorithm (HEX) and reverse non-equilibrium molecular dynamics (RNEMD). Different types of binary mixtures were studied including one equimolar mixture of argon (Ar)-krypton (Kr) above its triple point, non-equimolar normal alkane mixtures of hexane (nC6)-decane (nC10) as well as hexane (nC6)-dodecane (nC12) for six compositions, three non-equimolar mixtures of pentane (nC5) decane (nC10) at atmospheric temperature and pressure. Additionally, the new algorithm was validated for different ternary mixtures including ternary normal alkanes methane (nC1)-butane (nC4)- dodecane (nC12) for three compositions, and one composition of different types of alkane mixture of 1,2,3,4-tetrahydronaphthalene (THN)-dodecane (nC12)-sobutylbenzene (IBB). The new algorithm demonstrates a significant improvement in reducing the energy loss by nearly 32%. Additionally, the new algorithm is about 7-9% more computationally efficient than the regular HEX for medium and large systems. In terms of direction of thermodiffusive segregations in binary mixtures, in agreement with the experimental data, the new algorithm shows that the heavier component moves towards the cold region whereas the lighter component accumulates near the hot zone. Additionally, the strength of segregation process diminishes as the concentration of heavy component in the mixture increases. The new algorithm improved the prediction of thermodiffusion factor in binary mixtures by 24% in binary mixtures. With respect to the ternary mixtures, similarly to binary mixtures the heaviest and lightest component in the mixture move towards, cold and hot zones, respectively. While the intermediate component shows the least tendency to segregate. In terms of the strength of Soret effect, the new algorithm is about 17% more accurate than the regular HEX algorithm with respect to experimental data.
Surface tension of O2-Ar, N2-Ar and O2-N2-Ar mixtures
