Lecture

Kinetic Theory of Gases: Maxwell's Distribution

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In course

PHYS-106(h): 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 prévoir quantitativement les conséquences de ces phénomène ...

Description

This lecture delves into the concept of Maxwell's distribution, which describes the distribution of molecular speeds in gases. The instructor explains how this distribution is crucial for understanding chemical reactions with fixed activation energy and how it varies with temperature. The lecture covers the mathematical definition of the distribution function, the graphical representation of Maxwell's distribution, and the calculation of important velocities such as the most probable speed, average speed, and root-mean-square speed. Through examples with oxygen molecules, the instructor illustrates how these velocities relate to each other.

Instructor

Ivo Furno

Teaching & PhD PhD Students Jules Amédée Aristobule Schadt, Renat Karimov, Amélie Renggli, Yuri Asnis, Michael Goddijn, Vanni Jonas Meier, Cyrille Sepulchre, Francesco D'Angelo Past EPFL PhD Students Federico Nespoli, Oulfa Chellai, Thibaut François Hugo Richard, Fabian Manke, Riccardo Agnello, Alexandra Waskow, Lorenzo Ibba, Agus Rita, Kadi Lyes Roland Past EPFL PhD Students as codirector Davoud Iraji, Christian Gabriel Theiler, Alexandre Dominique Bovet, Fabio Avino Courses General physics : thermodyn

Official source

Related concepts (26)

Normal distribution

In statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution (and also its median and mode), while the parameter is its standard deviation. The variance of the distribution is . A random variable with a Gaussian distribution is said to be normally distributed, and is called a normal deviate.

Cumulative distribution function

In probability theory and statistics, the cumulative distribution function (CDF) of a real-valued random variable , or just distribution function of , evaluated at , is the probability that will take a value less than or equal to . Every probability distribution supported on the real numbers, discrete or "mixed" as well as continuous, is uniquely identified by a right-continuous monotone increasing function (a càdlàg function) satisfying and .

Chemical kinetics

Chemical kinetics, also known as reaction kinetics, is the branch of physical chemistry that is concerned with understanding the rates of chemical reactions. It is different from chemical thermodynamics, which deals with the direction in which a reaction occurs but in itself tells nothing about its rate. Chemical kinetics includes investigations of how experimental conditions influence the speed of a chemical reaction and yield information about the reaction's mechanism and transition states, as well as the construction of mathematical models that also can describe the characteristics of a chemical reaction.

Empirical distribution function

In statistics, an empirical distribution function (commonly also called an empirical cumulative distribution function, eCDF) is the distribution function associated with the empirical measure of a sample. This cumulative distribution function is a step function that jumps up by 1/n at each of the n data points. Its value at any specified value of the measured variable is the fraction of observations of the measured variable that are less than or equal to the specified value.

Quantile function

In probability and statistics, the quantile function outputs the value of a random variable such that its probability is less than or equal to an input probability value. Intuitively, the quantile function associates with a range at and below a probability input the likelihood that a random variable is realized in that range for some probability distribution. It is also called the percentile function (after the percentile), percent-point function or inverse cumulative distribution function (after the cumulative distribution function).

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