Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Dimensionless Groups in Fluid Mechanics01:15

Dimensionless Groups in Fluid Mechanics

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...
Characteristics of Fluids01:20

Characteristics of Fluids

When a force is applied parallel to the top surface of a solid, it resists the applied force due to the internal frictional forces between the layers of the solid known as shearing resistance. However, when the force is removed, the shearing forces restore the original shape of the solid. Other deformation forces also cause temporary changes in shape if the forces are not beyond a threshold magnitude. Solids tend to retain their shape, making the study of their rest and motion easier. Beyond...
Characteristics of Fluids01:31

Characteristics of Fluids

Fluids differ from solids primarily in their molecular structure and stress response. Solids have tightly packed molecules with strong intermolecular forces, maintaining their shape and resisting deformation. In contrast, fluids have molecules spaced farther apart with weaker forces, allowing them to flow and deform easily.
Fluids, which include both liquids and gases, are substances that deform continuously under shearing stress. For example, water and oil are liquids with molecules that can...
Surface Tension of Fluid01:22

Surface Tension of Fluid

Surface tension is a fundamental property of fluids, occurring at the boundary between a liquid and a gas or between two immiscible liquids. This phenomenon arises from the cohesive forces between molecules at the fluid's surface, creating an effect similar to a stretched elastic membrane. Inside each fluid, molecules are equally attracted in all directions by neighboring molecules, but surface molecules experience a net inward force, resulting in surface tension.
Surface tension varies with...
Viscosity of Fluid01:19

Viscosity of Fluid

Viscosity measures the resistance a fluid offers to flow and deformation. It results from internal friction between layers of fluid moving relative to one another. Dynamic viscosity, denoted by the Greek letter mu (μ), quantifies the force needed to move one fluid layer over another. For Newtonian fluids like water and air, the relationship between the shearing stress and the rate of shearing strain is linear, meaning their viscosity remains constant regardless of the applied stress.
Gauss's Law: Spherical Symmetry01:26

Gauss's Law: Spherical Symmetry

A charge distribution has spherical symmetry if the density of charge depends only on the distance from a point in space and not on the direction. In other words, if the system is rotated, it doesn't look different. For instance, if a sphere of radius R is uniformly charged with charge density ρ0, then the distribution has spherical symmetry. On the other hand, if a sphere of radius R is charged so that the top half of the sphere has a uniform charge density ρ1 and the bottom half has a uniform...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Orientational ordering and correlations in a quasi-one-dimensional hard-dumbbell fluid.

Physical review. E·2026
Same author

AI for the assessment and discovery of morphological-molecular biomarker relationships in hematologic malignancies.

Blood reviews·2026
Same author

Erratum: Predicting random close packing of binary hard-disk mixtures via third-virial-based parameters [J. Chem. Phys. 164, 124501 (2026)].

The Journal of chemical physics·2026
Same author

Predicting random close packing of binary hard-disk mixtures via third-virial-based parameters.

The Journal of chemical physics·2026
Same author

Persistent T cell activation and cytotoxicity against glioblastoma following single oncolytic virus treatment in a clinical trial.

Cell·2026
Same author

Dynamics of brain connectivity across the Alzheimer's disease spectrum through magnetoencephalography.

Scientific reports·2026

Related Experiment Video

Updated: Jul 7, 2026

Experimental Measurement of Settling Velocity of Spherical Particles in Unconfined and Confined Surfactant-based Shear Thinning Viscoelastic Fluids
10:28

Experimental Measurement of Settling Velocity of Spherical Particles in Unconfined and Confined Surfactant-based Shear Thinning Viscoelastic Fluids

Published on: January 3, 2014

Structure of hard-hypersphere fluids in odd dimensions.

René D Rohrmann1, Andrés Santos

  • 1Departamento de Física, Universidad de Extremadura, E-06071 Badajoz, Spain. rohr@oac.uncor.edu

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|February 1, 2008
PubMed
Summary

This study presents a new analytical method to understand hard hypersphere fluids in odd dimensions. The approach accurately predicts structural properties, offering thermodynamically consistent equations of state.

More Related Videos

Investigating the Three-dimensional Flow Separation Induced by a Model Vocal Fold Polyp
09:58

Investigating the Three-dimensional Flow Separation Induced by a Model Vocal Fold Polyp

Published on: February 3, 2014

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures
10:56

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures

Published on: May 20, 2014

Related Experiment Videos

Last Updated: Jul 7, 2026

Experimental Measurement of Settling Velocity of Spherical Particles in Unconfined and Confined Surfactant-based Shear Thinning Viscoelastic Fluids
10:28

Experimental Measurement of Settling Velocity of Spherical Particles in Unconfined and Confined Surfactant-based Shear Thinning Viscoelastic Fluids

Published on: January 3, 2014

Investigating the Three-dimensional Flow Separation Induced by a Model Vocal Fold Polyp
09:58

Investigating the Three-dimensional Flow Separation Induced by a Model Vocal Fold Polyp

Published on: February 3, 2014

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures
10:56

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures

Published on: May 20, 2014

Area of Science:

  • Statistical Mechanics
  • Fluid Dynamics
  • Materials Science

Background:

  • Understanding the structural properties of hard hypersphere fluids is crucial in statistical mechanics.
  • Existing analytical methods have limitations in higher dimensions.

Purpose of the Study:

  • To develop and validate an analytical approximation method for hard hypersphere fluids in odd space dimensionalities.
  • To generalize the rational function approximation for improved accuracy.

Main Methods:

  • Utilizing the exact radial distribution function to first order in density.
  • Extending to finite density via a rational function in Laplace space.
  • Employing Fourier transforms with reverse Bessel polynomials.

Main Results:

  • An analytical expression for the static structure factor was derived.
  • The method reproduces the Percus-Yevick solution in its basic form.
  • Thermodynamic consistency between virial and compressibility routes was achieved.

Conclusions:

  • The developed method provides accurate predictions for hard hypersphere fluids in odd dimensions.
  • The approach shows excellent agreement with computer simulation data at d=5 and d=7.
  • This formalism offers a pathway to more advanced equations of state.