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Related Concept Videos

Theories of Dissolution: Diffusion Layer Model01:15

Theories of Dissolution: Diffusion Layer Model

Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
This process starts with a thin layer, saturated with the drug, forming at the interface between the solid and liquid. The solute then diffuses from this layer into the main solution. The Noyes-Whitney equation suggests that the rate of dissolution relies on the diffusion...
Debye–Huckel–Onsager Conductance Equation01:28

Debye–Huckel–Onsager Conductance Equation

The Debye-Hückel-Onsager equation is a cornerstone of physical chemistry, providing a method to determine the molar conductance (Λm) and molar conductance at infinite dilution (Λ°m) for uni-univalent electrolytes.Uni-univalent electrolytes are electrolytes that dissociate in solution to produce one cation with a +1 charge and one anion with a –1 charge per formula unit.This equation addresses two crucial phenomena: the asymmetry effect and the electrophoretic effect. According to this equation,...
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Diffusion

Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
Transport Number01:31

Transport Number

The transport number is the fraction of the total current carried by an ion in an electrolyte solution. It is defined as the ratio of the current carried by a specific ion to the total current flowing through the solution. The transport number, t, is central to understanding ionic mobility, which describes how fast an ion moves under the influence of an electric field. This link connects the physical behavior of ions in solution to the chemical processes that occur during electrochemical...
Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model01:09

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Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the concentration...
Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

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Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...

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Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid
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Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid

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A model for self-diffusion of guanidinium-based ionic liquids: a molecular simulation study.

Marco Klähn1, Abirami Seduraman, Ping Wu

  • 1Institute of High Performance Computing, Connexis, Singapore.

The Journal of Physical Chemistry. B
|October 16, 2008
PubMed
Summary

A new atomic-level model explains ionic liquid diffusion, revealing ion movement is driven by electrostatic interactions, not cavities. This model predicts how ion changes affect diffusion characteristics.

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Synthesis of Ionic Liquid Based Electrolytes, Assembly of Li-ion Batteries, and Measurements of Performance at High Temperature

Published on: December 20, 2016

Area of Science:

  • Physical Chemistry
  • Materials Science
  • Computational Chemistry

Background:

  • Ionic liquids (ILs) are salts that are liquid at room temperature, with applications in diverse fields.
  • Understanding the self-diffusion mechanisms of ions in ILs is crucial for optimizing their performance.
  • Previous models often lack atomic-level detail or fail to capture the complex interplay of factors governing IL diffusion.

Purpose of the Study:

  • To develop and validate a novel, atomic-level self-diffusion model for guanidinium-based ionic liquids (GILs).
  • To elucidate the molecular origins of ion diffusion in GILs and establish relationships between energetic and dynamic properties.
  • To provide a predictive tool for understanding how ion modifications influence the diffusive characteristics of ILs.

Main Methods:

  • Molecular dynamics (MD) simulations of guanidinium-based ionic liquids (GILs) using an empirical molecular mechanical force field.
  • Calculation of self-diffusion coefficients at various temperatures to determine diffusive activation energies.
  • Analysis of vaporization enthalpies, cavity formation, and inter-ionic interactions (cation hydrogen-anion oxygen) to understand diffusion mechanisms.

Main Results:

  • Derived diffusive activation energies (32-40 kJ/mol) and vaporization enthalpies (174-212 kJ/mol), demonstrating a strong correlation.
  • Observed cavity formation (up to 6.5%) does not enhance self-diffusion; electrostatic interactions are the primary drivers.
  • Identified a 'brachiation-type' movement where ions cleave contacts, diffuse short distances (~2 Å), and form new contacts, with transition times (58-107 ps) dictating diffusion speed.

Conclusions:

  • The proposed atomic-level self-diffusion model consistently explains energetic and dynamic properties of GILs, linking them to their molecular origins.
  • The model successfully explains measured ratios of cation and anion self-diffusion coefficients across various ILs.
  • This predictive model allows for the a priori estimation of how ionic liquid modifications will impact their diffusive behavior.