Maxwell–Boltzmann distribution

In physics (in particular in statistical mechanics), the Maxwell–Boltzmann distribution, or Maxwell(ian) distribution, is a particular probability distribution named after James Clerk Maxwell and Ludwig Boltzmann. It was first defined and used for describing particle speeds in idealized gases, where the particles move freely inside a stationary container without interacting with one another, except for very brief collisions in which they exchange energy and momentum with each other or with their thermal environment. The term "particle" in this context refers to gaseous particles only (atoms or molecules), and the system of particles is assumed to have reached thermodynamic equilibrium. The energies of such particles follow what is known as Maxwell–Boltzmann statistics, and the statistical distribution of speeds is derived by equating particle energies with kinetic energy. Mathematically, the Maxwell–Boltzmann distribution is the chi distribution with three degrees of freedom (the components of the velocity vector in Euclidean space), with a scale parameter measuring speeds in units proportional to the square root of (the ratio of temperature and particle mass). The Maxwell–Boltzmann distribution is a result of the kinetic theory of gases, which provides a simplified explanation of many fundamental gaseous properties, including pressure and diffusion. The Maxwell–Boltzmann distribution applies fundamentally to particle velocities in three dimensions, but turns out to depend only on the speed (the magnitude of the velocity) of the particles. A particle speed probability distribution indicates which speeds are more likely: a randomly chosen particle will have a speed selected randomly from the distribution, and is more likely to be within one range of speeds than another. The kinetic theory of gases applies to the classical ideal gas, which is an idealization of real gases. In real gases, there are various effects (e.g., van der Waals interactions, vortical flow, relativistic speed limits, and quantum exchange interactions) that can make their speed distribution different from the Maxwell–Boltzmann form.

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (6)

Related people (2)

Related concepts (21)

Related courses (38)

Related lectures (290)

Related MOOCs (7)

CO2-Driven diffusiophoresis and water cleaning: similarity solutions for predicting the exclusion zone in a channel flow

Mrudhula Baskaran

We investigate experimentally and theoretically diffusiophoretic separation of negatively charged particles in a rectangular channel flow, driven by CO2 dissolution from one side-wall. Since the negat

ROYAL SOC CHEMISTRY2021

Evolution of the vorticity distribution in vortex rings

Guillaume de Guyon-Crozier

Vortex rings are very efficient at transporting fluid on long distances and can generate large forces, either thrust or drag. These abilities are influenced by the vorticity distribution within the vo

EPFL2021

Dynamics of Defects in Field-Induced Skyrmion Lattice Melting

Guanghao Li

TP4 project: My work is mainly to achieve the identification, segmentation and tracking of defects and analyze their dynamics. In detail, the positions, the motion tracks, life expectancy, velocity di

2019

Maxwell–Boltzmann distribution

Temperature

Temperature is a physical quantity that expresses quantitatively the perceptions of hotness and coldness. Temperature is measured with a thermometer. Thermometers are calibrated in various temperature scales that historically have relied on various reference points and thermometric substances for definition. The most common scales are the Celsius scale with the unit symbol °C (formerly called centigrade), the Fahrenheit scale (°F), and the Kelvin scale (K), the latter being used predominantly for scientific purposes.

Kinetic theory of gases

The kinetic theory of gases is a simple, historically significant classical model of the thermodynamic behavior of gases, with which many principal concepts of thermodynamics were established. The model describes a gas as a large number of identical submicroscopic particles (atoms or molecules), all of which are in constant, rapid, random motion. Their size is assumed to be much smaller than the average distance between the particles. The particles undergo random elastic collisions between themselves and with the enclosing walls of the container.

CH-351: Molecular dynamics and Monte-Carlo simulations

Introduction to molecular dynamics and Monte-Carlo simulation methods.

PHYS-106(d): General physics : thermodynamics

Le but du cours de Physique générale est de donner à l'étudiant les notions de base nécessaires à la compréhension des phénomènes physiques. L'objectif est atteint lorsque l'étudiant est capable de pr

PHYS-106(a): General physics : thermodynamics

Collision Flux Derivation

Explores collision flux derivation and Knudsen method for measuring vapor pressure.

Plasma State: Properties and Effects

Covers the definition and properties of plasma, including ionization and collective effects.

Thermal Fluctuations: Importance at Cellular Scale

Explores the impact of thermal fluctuations at the cellular scale, emphasizing randomness in biological processes and the distribution of kinetic energy in gas molecules.

Plasma Physics: Introduction

Learn the basics of plasma, one of the fundamental states of matter, and the different types of models used to describe it, including fluid and kinetic.

Plasma Physics: Introduction

Learn the basics of plasma, one of the fundamental states of matter, and the different types of models used to describe it, including fluid and kinetic.

Plasma Physics: Applications

Learn about plasma applications from nuclear fusion powering the sun, to making integrated circuits, to generating electricity.