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The Fluid Mosaic Model01:34

The Fluid Mosaic Model

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The fluid mosaic model was first proposed as a visual representation of research observations. The model comprises the composition and dynamics of membranes and serves as a foundation for future membrane-related studies. The model depicts the structure of the plasma membrane with a variety of components, which include phospholipids, proteins, and carbohydrates. These integral molecules are loosely bound, defining the cell’s border and providing fluidity for optimal function.
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Van der Waals Equation01:10

Van der Waals Equation

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The ideal gas law is an approximation that works well at high temperatures and low pressures. The van der Waals equation of state (named after the Dutch physicist Johannes van der Waals, 1837−1923) improves it by considering two factors.
First, the attractive forces between molecules, which are stronger at higher densities and reduce the pressure, are considered by adding to the pressure a term equal to the square of the molar density multiplied by a positive coefficient a. Second, the volume...
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Comparing Intermolecular Forces: Melting Point, Boiling Point, and Miscibility02:34

Comparing Intermolecular Forces: Melting Point, Boiling Point, and Miscibility

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Intermolecular forces are attractive forces that exist between molecules. They dictate several bulk properties, such as melting points, boiling points, and solubilities (miscibilities) of substances. Molar mass, molecular shape, and polarity affect the strength of different intermolecular forces, which influence the magnitude of physical properties across a family of molecules.
Temporary attractive forces like dispersion are present in all molecules, whether they are polar or nonpolar. They...
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Dimensionless Groups in Fluid Mechanics01:15

Dimensionless Groups in Fluid Mechanics

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Dimensionless groups in fluid mechanics provide simplified ratios that help analyze fluid behavior without relying on specific units. The Reynolds number (Re), which represents the ratio of inertial to viscous forces, distinguishes between laminar and turbulent flows, making it essential in the design of pipelines and aerodynamic surfaces. The Froude number (Fr), the ratio of inertial to gravitational forces, is particularly useful in predicting wave formation and hydraulic jumps in...
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Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model01:09

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model

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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...
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Real Gases: Effects of Intermolecular Forces and Molecular Volume Deriving Van der Waals Equation04:01

Real Gases: Effects of Intermolecular Forces and Molecular Volume Deriving Van der Waals Equation

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Thus far, the ideal gas law, PV = nRT, has been applied to a variety of different types of problems, ranging from reaction stoichiometry and empirical and molecular formula problems to determining the density and molar mass of a gas. However, the behavior of a gas is often non-ideal, meaning that the observed relationships between its pressure, volume, and temperature are not accurately described by the gas laws. 
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Video Experimental Relacionado

Updated: Sep 9, 2025

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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Un modelo ML explicable para fluidos LJ binarios

Israrul H Hashmi1, Rahul Karmakar1,2, Marripelli Maniteja1

  • 1Department of Chemical Engineering, Indian Institute of Technology Madras Chennai, TN, 600036, India. tpatra@iitm.ac.in.

Soft matter
|August 29, 2025
PubMed
Resumen
Este resumen es generado por máquina.

El aprendizaje automático predice con precisión las funciones de distribución radial para los fluidos binarios de Lennard-Jones (LJ). El modelo captura efectivamente la microestructura, mostrando que la proporción de tamaño de partícula es clave, pero tiene limitaciones con la nueva física.

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Área de la Ciencia:

  • Física computacional
  • Mecánica estadística
  • Ciencias de los materiales

Sus antecedentes:

  • Los fluidos de Lennard-Jones (LJ) son modelos fundamentales para las interacciones moleculares.
  • Los fluidos LJ binarios ofrecen información sobre mezclas complejas de fluidos y comportamiento de fase.

Objetivo del estudio:

  • Desarrollar y validar un modelo de aprendizaje automático (ML) para predecir las funciones de distribución radial (RDF) en fluidos LJ binarios.
  • Evaluar la precisión y las capacidades de extrapolación del modelo ML en diversas condiciones.

Principales métodos:

  • Se utilizaron simulaciones de dinámica molecular (DM) para generar datos RDF para mezclas binarias de LJ.
  • Se construyó un modelo de aprendizaje automático, discretizando los RDF para reducir la dimensionalidad y mejorar la eficiencia.
  • El modelo ML fue entrenado y validado utilizando datos de simulación en diferentes composiciones y temperaturas.

Principales resultados:

  • El modelo ML predice con precisión RDF para mezclas de fluidos LJ binarios no vistas anteriormente.
  • El modelo demuestra las capacidades de extrapolación dentro del espacio de fase de temperatura de composición.
  • El análisis indica que la proporción de tamaño de partícula influye significativamente en la microestructura de la mezcla.

Conclusiones:

  • El modelo ML desarrollado es eficaz para predecir RDF en fluidos LJ binarios.
  • El estudio pone de relieve la importancia de la proporción de tamaño de partícula en la determinación de la microestructura del fluido.
  • Existen limitaciones cuando el modelo ML encuentra regímenes físicos fuera de sus datos de entrenamiento.