scholarly journals Molecular Dynamics Calculation Of Thermodiffusion Coefficients In Binary And Ternary Mixtures

2021 ◽  
Author(s):  
Seyedeh Hoda Mozaffari
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Binary Mixtures ◽  
Soret Effect ◽  
Ternary Mixtures ◽  
Computationally Efficient ◽  
Fluid Mixtures ◽  
Binary And Ternary Mixtures ◽  
Different Types ◽  
Non Equilibrium Molecular Dynamics

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.

scholarly journals Molecular Dynamics Calculation Of Thermodiffusion Coefficients In Binary And Ternary Mixtures

2021 ◽  
Author(s):  
Seyedeh Hoda Mozaffari
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Binary Mixtures ◽  
Soret Effect ◽  
Ternary Mixtures ◽  
Computationally Efficient ◽  
Fluid Mixtures ◽  
Binary And Ternary Mixtures ◽  
Different Types ◽  
Non Equilibrium Molecular Dynamics

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.

Viscosity of binary and tertinary liquid nonelectrolyte mixtures. Comparison of correlation equations and analysis of viscosity curves

1981 ◽  
Vol 46 (2) ◽  
pp. 303-328 ◽  
Author(s):  
Pavol Škubla
Keyword(s):  
Experimental Data ◽  
Binary Mixtures ◽  
Chemical Nature ◽  
Ternary Mixtures ◽  
Correlation Equations ◽  
Binary And Ternary Mixtures

The derived equations for correlation of viscosity of binary and ternary mixtures were tested and compared with those of McAllister, Chandramouli and Laddha. Testing on a large number of experimental data revealed that the equations for correlation of viscosity of binary mixtures are approximately as accurate as the equation of McAllister. On adding another coefficient, the relative deviations are lowered by 26-40%. Equations for correlation of viscosity of ternary mixtures are about as accurate as the equation of Chandramouli and Laddha. Analysis of viscosity curves of binary mixtures revealed a correlation between their form and the chemical nature of the components of the mixture.

Properties of Refrigerants from Cubic Equations of State

2008 ◽  
Vol 59 (5) ◽  
Author(s):  
Viorel Feroiu ◽  
Dan Geana ◽  
Catinca Secuianu
Keyword(s):  
Experimental Data ◽  
Vapor Pressure ◽  
Equations Of State ◽  
Ternary Mixtures ◽  
Volumetric Properties ◽  
Mixing Rules ◽  
Saturation Curve ◽  
Equilibrium Thermodynamic ◽  
Liquid Equilibrium ◽  
Binary And Ternary Mixtures

Vapour � liquid equilibrium, thermodynamic and volumetric properties were predicted for three pure hydrofluorocarbons: difluoromethane (R32), pentafluoroethane (R125) and 1,1,1,2 � tetrafluoroethane (R134a) as well as for binary and ternary mixtures of these refrigerants. Three cubic equations of state GEOS3C, SRK (Soave � Redlich � Kwong) and PR (Peng � Robinson) were used. A wide comparison with literature experimental data was made. For the refrigerant mixtures, classical van der Waals mixing rules without interaction parameters were used. The GEOS3C equation, with three parameters estimated by matching several points on the saturation curve (vapor pressure and corresponding liquid volumes), compares favorably to other equations in literature, being simple enough for applications.

Catalytic hydrogenation of binary and ternary mixtures of unsaturated substances in the liquid phase on platinum

1979 ◽  
Vol 44 (8) ◽  
pp. 2378-2383 ◽  
Author(s):  
Libor Červený ◽  
Radka Junová ◽  
Vlastimil Růžička
Keyword(s):  
Liquid Phase ◽  
Binary Mixtures ◽  
Silica Gel ◽  
Catalytic Hydrogenation ◽  
Ternary Systems ◽  
Ternary Mixtures ◽  
Unsaturated Alcohol ◽  
Solvent Concentration ◽  
Binary And Ternary Mixtures ◽  
Hydrogenation Selectivity

Hydrogenation of olefinic substrates in binary and ternary mixtures using 5% Pt on silica gel as the catalyst was studied in normal conditions in the liquid phase with methanol or cyclohexane or in solvent-free systems. The effect of the solvent concentration on the selectivity of hydrogenation of the unsaturated alcohol-olefin binary mixtures was investigated. In ternary systems of unsaturated substrates, the effect of each of the substrates on the selectivity of hydrogenation of the remaining two substances was examined. Another system was found in which a jump change of the hydrogenation selectivity occurred on the vanishing of the fastest reacting substance.

The Limited Capacity of Humans to Identify the Components of Taste Mixtures and Taste – Odour Mixtures

Perception ◽  
10.1068/p3205 ◽  
2002 ◽  
Vol 31 (5) ◽  
pp. 617-635 ◽  
Author(s):  
David G Laing ◽  
Catherine Link ◽  
Anthony L Jinks ◽  
Ian Hutchinson
Keyword(s):  
Working Memory ◽  
Binary Mixtures ◽  
Temporal Processing ◽  
Olfactory Stimulus ◽  
Ternary Mixtures ◽  
Limited Capacity ◽  
Binary And Ternary Mixtures

The capacity of humans to identify the components of taste mixtures and odour – taste mixtures was investigated in two experiments. Subjects were trained to identify the components presented alone and to use a ‘yes/no’ procedure to identify them in mixtures. All stimuli were presented with a retronasal (by mouth) technique. A maximum of three tastants were identified in both types of mixtures, only one tastant was identified in five-component taste mixtures, and no component was identified in four-component odour – taste mixtures. Importantly, in no instance was the olfactory stimulus identified in any mixture with tastes, including binary mixtures. Loss of identity of the odorant in binary and ternary mixtures may have been due to suppression as a consequence of temporal processing, or to the absence of an association between the odorant and tastants that had established an identifiable percept. In contrast, poor identification of the components of the quaternary odour – taste mixture and quinternary taste mixture is attributed to the limited capacity of working memory. Overall, the poorer ability to identify components in odour–taste mixtures than in taste mixtures indicates that interactions occurred between the two senses, challenging the proposal that odours and tastes are processed independently when present in complex chemosensory stimuli.

scholarly journals Enhanced Molecular Dynamics Approach for Thermal Transport Phenomena in Complex Systems

2021 ◽  
Author(s):  
Sylvie Antoun
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Complex Systems ◽  
Force Field ◽  
Potential Field ◽  
Thermal Transport ◽  
Ternary Mixture ◽  
Soret Effect ◽  
Transport Phenomena ◽  
Integration Scheme

This thesis introduces an enhanced Molecular Dynamics (MD) approach, blended with fine-tuned Force Field (FF) models to reflect more realistic experimental conditions and achieve a precise representation of the atomic interactions in complex systems. Firstly, an enhanced MD algorithm consisting of an upgraded non-equilibrium integration scheme, namely eHEX, coupled with an augmented TraPPE-UA force field, was generated and put to use to predict Soret effect in a binary mixture: n-pentane/n-decane. The results were compared to other MD approaches and validated with respect to benchmarked experimental data. The suggested method showed a closer agreement with experimental data than the previous MD findings. The reinforced potential field (TraPPE-UA) was capable of reflecting the real molecular interactions between the hydrocarbons and reproduce the liquid mixture properties at different conditions. Moreover, the extended HEX method succeeded in conserving the system’s overall energy with minor fluctuations and attaining a stationary state, ensuring the precision of the integration scheme and the satisfaction of local equilibrium. Secondly, the performance of the previously proposed approach was further studied to test its performance on a ternary mixture of methane/n-butane/n-dodecane at five different compositions. Thermodiffusion separation ratio of each component was assessed at 333.15 K and 35 MPa, and compared to the experimental data as well as 3 other MD models from the literature. A good qualitative agreement between the experimental data and the MD model observed in this work was observed, displaying the least deviation when compared to the other MD approaches. The method was capable of adequately representing the physics behind the thermodiffusive separation and deepening the microscopic understanding of the segregation process in a ternary mixture undergoing large thermal gradients. Put differently, the approach elucidates the relative contribution of the cross-interactions found between the unlike species in the mixture and their corresponding composition. Next, an enhanced MD approach was also presented to predict the dynamics and thermophysical properties of suspended γ-alumina nanoparticles (NPs) in acidic aqueous solutions. The previous MD work have unveiled numerous impediments in terms of reproducing the thermal transport phenomena in nanofluids. A hybrid potential field, comprised of refined orce field models (ClayFF and SPC/E), was implemented to allow a precise integration of the nanoscale phenomena into the dynamics and structure of charged alumina NPs, thereby bridging the challenging gap between the solid-liquid interfacial chemistry and the overall thermodynamic properties. The original CLAYFF was augmented to properly account for the energy and momentum transfer between the water molecules and the positively charged NPs, while keeping the number of parameters small enough to allow modeling of a relatively large nanofluidic system.The results were in good agreement with the experimental data. An increase of the NPs volumetric concentration (φ) lead to the enhancement of thermal conductivity along with an increase of viscosity. The results demonstrate the crucial role played by the repulsive electrostatic forces yielding well-dispersed NP suspensions, specially at low φ. The post analysis of Mouromtseff number demonstrated that at lower φ, the system show a higher propensity for stability and enhancement for φ less than 2%, specially at high temperatures. On the contrary, for volumetric concentrations higher than 2%, the system thermal performance deteriorates which is expected due to the fact that the system exhibit a critical condition of aggregation and clogging. With all of the above findings in mind, the MD framework presented in this thesis represents an improved step towards a precise and computationally balanced MD modelling that bridges the relation between molecular signatures and macroscopic features, capable of overcoming the shortcomings present in mainly two emerging thermal applications: 1) Soret effect in hydrocarbon mixture and 2) thermal transport of alumina-water nanofluids.

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