Diffusion Coefficients for the Ternary System Water + Chloroform + Acetic Acid at 25 °C

Buzatu, Daniela; Buzatu, Florin D.; Paduano, Luigi; Sartorio, Roberto

doi:10.1007/s10953-007-9200-z

Cited by 24 publications

(23 citation statements)

References 21 publications

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“…Volume-based diffusion coefficients, D V ij Â 10 9 m 2 Á s À1 , as functions of composition x i for chloroform(1), acetic acid (2), and water b mixture at T = 298.15 K and p = 0.1 MPa [38,39]. complex k D,i throughout the range of possible D V ij within the reported accuracy.…”

Section: Tablesupporting

confidence: 54%

“…Examination of the reported D shows that in ternary mixtures, nine data points from two mixtures are reported with negative diagonal D V elements: (water + 2-propanol + cyclohexane 2 ) [32]; and, (acetic acid + chloroform + water) [38,39]. Mixture conditions and D V ij are shown in tables 6 and 7.…”

Section: Negative Diagonal Elements Of Fickian Diffusion Coefficientsmentioning

confidence: 99%

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Form of multicomponent Fickian diffusion coefficients matrix

Mutoru

Firoozabadi

2011

The Journal of Chemical Thermodynamics

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Section: Tablesupporting

confidence: 54%

Section: Negative Diagonal Elements Of Fickian Diffusion Coefficientsmentioning

confidence: 99%

Form of multicomponent Fickian diffusion coefficients matrix

Mutoru

Firoozabadi

2011

The Journal of Chemical Thermodynamics

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“…where D ii are the main diffusion coefficients that relate the molar flux of component i to its own concentration gradient and D i j are the cross diffusion coefficients that relate the molar flux of component i to the concentration gradient of component j [9]. The Fick approach involves three independent diffusion fluxes and a 3 × 3 diffusion coefficient matrix, which is generally not symmetric, i.e.…”

Section: Diffusion In Quaternary Liquid Mixturesmentioning

confidence: 99%

Molecular Modeling and Simulation: Model Development, Thermodynamic Properties, Scaling Behavior and Data Management

Heinen

Chatwell

Homes

et al. 2021

High Performance Computing in Science and Engineering '20

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We are outlining our most recent findings, covering: 1) A comparison of a micro-and macroscopic solution of a two-phase Riemann problem obtained from molecular dynamics simulations and finite volume schemes; 2) A novel equation of state for the bulk viscosity of liquid noble gases based on a multi-mode relaxation ansatz; 3) A detailed analysis of the evaporation process of simple fluids; 4) Diffusion coefficients of quaternary liquid mixtures obtained by the Green-Kubo formalism; 5) An analysis of the solid/fluid phase transition for the face centered cubic (fcc) lattice; 6) The relative permittivity of mixtures of water and acetone; 7) An assessment of the reliability and reproducibility of molecular simulation results; 8) Techniques for the data management in simulation workflows, including annotations of simulation outcomes with appropriate metadata standardized by an ontology.

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“…Negative diffusion coefficients violate physical intuition because they indicate that species oppose their dilution. However, there are several ongoing discussions in the literature with regards to the existence of negative diffusion coefficients in [39][40][41][42][43] and references therein. These works give theoretical and experimental evidences supporting the existence of negative diffusion coefficients.…”

Section: Magnetic Field Effect On Diffusion Of Paramagnetic and Diamagnetic Moleculesmentioning

confidence: 99%

Effects of High Magnetic Fields on Diffusion of Biologically Active Molecules

Zablotskii

Polyakova

Dejneka

2020

Preprint

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The diffusion of biologically active molecules is a ubiquitous process, controlling many mechanisms and the characteristic time scales for pivotal processes in living cells. Here, we show how a high static magnetic field (MF) affects the diffusion of paramagnetic and diamagnetic species, including oxygen, hemoglobin, ROS and drugs. We derive and solve the equation describing diffusion of such biologically active molecules in the presence of a MF as well as reveal the underlying mechanism of the MF effect on diffusion. We find that a high MF accelerates diffusion of diamagnetic species while slowing the diffusion of paramagnetic molecules in cell cytoplasm. When applied to oxygen and hemoglobin diffusion in red blood cells, our results suggest that a MF may significantly alter the gas exchange in an erythrocyte and cause swelling. Our prediction that the diffusion rate and characteristic time can be controlled by a MF opens new avenues for experimental studies foreseeing numerous biomedical applications.SignificanceWe show that diffusion processes of biologically active molecules (hemoglobin, oxygen, reactive oxygen species, etc.) and paramagnetic drugs can be remotely controlled by high static magnetic fields. Since diffusion processes determine the reference time scale for all other processes in living cells as well as the propagation speed of signaling molecules during cell-to-cell communication, our results – the magnetic field dependences of the diffusion rate and characteristic time – may serve as an important key for revealing and understanding the mechanisms of magnetic field action on living cells, tissue and organisms.

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Diffusion Coefficients for the Ternary System Water + Chloroform + Acetic Acid at 25 °C

Cited by 24 publications

References 21 publications

Form of multicomponent Fickian diffusion coefficients matrix

Form of multicomponent Fickian diffusion coefficients matrix

Molecular Modeling and Simulation: Model Development, Thermodynamic Properties, Scaling Behavior and Data Management

Effects of High Magnetic Fields on Diffusion of Biologically Active Molecules

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