The Classical Ideal Gas and Molecular Speeds
~8 min read · Tier toggle changes depth (T1 plain · T2 standard · T3 rigour)
You should be comfortable with the canonical ensemble formalism, specifically the definition of the partition function \( Z \) and its relationship to the Helmholtz free energy \( F \). Familiarity with basic multivariable calculus, particularly partial derivatives and Gaussian integrals, is assumed.
Why this matters
The ideal gas is the Rosetta Stone of statistical mechanics, translating microscopic chaos into macroscopic pressure.
While the previous lecture established that different ensembles yield the same thermodynamics in the limit of large \( N \), we now apply this machinery to the simplest non-trivial system: a classical ideal gas. By calculating the partition function for a single particle and then for \( N \) indistinguishable particles, we derive the Maxwell-Boltzmann speed distribution. This distribution is not merely a mathematical curiosity; it is the direct statistical origin of temperature, pressure, and the equipartition of energy. Understanding how the "average" speed emerges from the probability density function provides the critical bridge between the abstract counting of microstates and the tangible properties of matter we measure in the laboratory.
The Physical Picture
Imagine a box filled with a vast number of tiny, hard spheres bouncing around randomly. In the classical picture, these particles do not interact with each other except during instantaneous, elastic collisions. Because they are classical, they can occupy any position and have any velocity, provided the total energy is conserved. However, when this gas is in contact with a heat reservoir at temperature \( T \), the system does not have a fixed total energy; instead, it samples different energy states according to the Boltzmann factor. The key insight is that while the individual speeds of the molecules vary wildly, the distribution of these speeds is fixed by the temperature. There is no single "speed of the gas," but there is a most probable speed, an average speed, and a root-mean-square speed. These three distinct measures of speed all scale with the square root of temperature and inversely with the square root of mass. This statistical spread is what gives rise to the pressure exerted on the walls of the container: it is the cumulative effect of countless microscopic impacts, each carrying a momentum change determined by the molecule's velocity.
Single-Particle Partition Function
To begin, we consider a single particle of mass \( m \) confined to a volume \( V \). The energy of this particle is purely kinetic, given by \( E = \frac{1}{2}m v^2 = \frac{\mathbf{p}^2}{2m} \), where \( \mathbf{p} \) is the momentum vector. The canonical partition function \( Z_1 \) for this single particle is defined as the sum (or integral, in the classical limit) over all possible microstates. In phase space, a microstate is specified by a position \( \mathbf{r} \) and a momentum \( \mathbf{p} \). The integral over position simply yields the volume \( V \). The integral over momentum is a three-dimensional Gaussian integral.
Here, \( h \) is Planck's constant, introduced to make the partition function dimensionless and to account for the quantum nature of phase space cells, even in this classical approximation. The momentum integral separates into three identical one-dimensional integrals of the form \( \int_{-\infty}^{\infty} e^{-\beta p_x^2 / 2m} dp_x \). Using the standard Gaussian result \( \int_{-\infty}^{\infty} e^{-ax^2} dx = \sqrt{\frac{\pi}{a}} \), with \( a = \frac{\beta}{2m} \), we find that each component contributes \( \sqrt{\frac{2\pi m}{\beta}} \). Multiplying the three components and the volume \( V \), we obtain:
This result can be written \( Z_1 = V/\lambda_{\mathrm{th}}^3 \), with thermal de Broglie wavelength \( \lambda_{\mathrm{th}} = h/\sqrt{2\pi m k_B T} \): the number of thermal-wavelength cells that fit in the box. It encapsulates the available phase space for a single particle at temperature \( T \).
Many-Particle System and Gibbs Correction
For \( N \) non-interacting particles, the total energy is the sum of individual energies. If the particles were distinguishable, the total partition function would simply be \( Z_N = (Z_1)^N \). However, in classical statistical mechanics, particles of the same species are indistinguishable. Counting permutations of identical particles leads to the Gibbs paradox, where entropy is not extensive. To correct for this overcounting, we divide by \( N! \). Thus, the canonical partition function for the ideal gas is:
Using Stirling's approximation \( \ln N! \approx N \ln N - N \) for large \( N \), we can calculate the Helmholtz free energy \( F = -k_B T \ln Z_N \). This yields the Sackur-Tetrode equation, which correctly predicts the extensive nature of entropy. More importantly for this lecture, the probability distribution of the momentum of any single particle is derived from the Boltzmann factor \( e^{-\beta p^2/2m} \). Since the momentum components \( p_x, p_y, p_z \) are independent, the joint probability density for the momentum vector is a product of three Gaussian distributions.
Deriving the Speed Distribution
We are interested in the speed \( v = |\mathbf{v}| \), not the velocity vector. The probability density for the velocity vector \( \mathbf{v} \) is proportional to \( e^{-\frac{1}{2}m v^2 / k_B T} \). To find the distribution of the scalar speed \( v \), we must integrate over the angular variables in velocity space. The volume element in spherical coordinates in velocity space is \( v^2 \sin\theta \, dv \, d\theta \, d\phi \). Integrating over the angles \( \theta \) and \( \phi \) gives a factor of \( 4\pi \). Therefore, the probability density function \( f(v) \) for the speed is proportional to \( v^2 e^{-\frac{m v^2}{2 k_B T}} \). Normalizing this distribution such that \( \int_0^\infty f(v) dv = 1 \) yields the Maxwell-Boltzmann speed distribution:
This function has a characteristic shape: it starts at zero for \( v=0 \) (because the volume of velocity space at low speeds is small), rises to a peak at the most probable speed \( v_p = \sqrt{\frac{2 k_B T}{m}} \), and then decays exponentially. The factor \( v^2 \) represents the increasing number of velocity states available at higher speeds, while the exponential term represents the decreasing probability of finding a particle with high kinetic energy. This distribution is universal for any classical ideal gas, depending only on the mass \( m \) and temperature \( T \).
The derivations
The Maxwell-Boltzmann Speed Distribution
Applying the Boltzmann factor to a molecule's kinetic energy and integrating over direction gives the distribution of molecular speeds and its moments.
The Partition Function and F = -kT ln Z
For a system in thermal contact with a reservoir at temperature T, normalizing the Boltzmann distribution pi ∝ e−βEi over microstates i forces the introduction of the canonical partition function Z = ∑i e−βEi (with β = 1/kT). The Helmholtz free energy is then F = −kT ln Z, and the internal energy, entropy, and every thermodynamic quantity follow as derivatives of ln Z.
A common misconception is that the "average speed" is the same as the most probable speed. In fact, the distribution is skewed to the right (positive skewness). The most probable speed \( v_p \) is where the PDF peaks. The mean speed \( \langle v \rangle \) is the first moment of the distribution, and the root-mean-square speed \( v_{\mathrm{rms}} \) is the square root of the second moment. They are related by \( v_p < \langle v \rangle < v_{\mathrm{rms}} \). Specifically, \( \langle v \rangle = \sqrt{\frac{8 k_B T}{\pi m}} \) and \( v_{\mathrm{rms}} = \sqrt{\frac{3 k_B T}{m}} \). Using \( v_p \) for calculations involving average kinetic energy or pressure will lead to errors of order 10-20%. C
Worked example
Problem. Calculate the most probable speed \( v_p \) and the root-mean-square speed \( v_{\mathrm{rms}} \) for Nitrogen gas (\( \mathrm{N_2} \)) at a temperature of \( 300\ \mathrm{K} \). The molar mass of Nitrogen is \( 28.0\ \mathrm{g/mol} \). Use \( R = 8.314\ \mathrm{J/(mol \cdot K)} \) and \( N_A = 6.022 \times 10^{23}\ \mathrm{mol^{-1}} \).
- Determine the mass of a single Nitrogen molecule. The molar mass is \( M = 28.0 \times 10^{-3}\ \mathrm{kg/mol} \). The mass per molecule is \( m = \frac{M}{N_A} \).
- Calculate \( v_p \) using the formula \( v_p = \sqrt{\frac{2 k_B T}{m}} \). Note that \( k_B = \frac{R}{N_A} \), so \( \frac{k_B}{m} = \frac{R/N_A}{M/N_A} = \frac{R}{M} \). Thus, \( v_p = \sqrt{\frac{2 R T}{M}} \).
- Calculate \( v_{\mathrm{rms}} \) using the formula \( v_{\mathrm{rms}} = \sqrt{\frac{3 k_B T}{m}} = \sqrt{\frac{3 R T}{M}} \).
- Substitute the numerical values: \( T = 300\ \mathrm{K} \), \( R = 8.314\ \mathrm{J/(mol \cdot K)} \), \( M = 0.028\ \mathrm{kg/mol} \).
Units check. The term inside the square root is \( \frac{\mathrm{J}}{\mathrm{kg}} = \frac{\mathrm{kg \cdot m^2/s^2}}{\mathrm{kg}} = \mathrm{m^2/s^2} \). The square root yields \( \mathrm{m/s} \), which is correct for speed.
For comparison, the mean speed is \( \sqrt{8RT/\pi M} = 476\ \mathrm{m\,s^{-1}} \), so \( v_p : \langle v \rangle : v_{\mathrm{rms}} = 422 : 476 : 517 = 1 : 1.128 : 1.225 \).
Three quick tests
- Why does the Maxwell-Boltzmann speed distribution \( f(v) \) go to zero as \( v \to 0 \)?
Answer
The probability density is proportional to the volume of the spherical shell in velocity space, which scales as \( v^2 \). As \( v \) approaches zero, the available phase space volume shrinks to zero, making it unlikely to find particles with exactly zero speed. - If the temperature of an ideal gas is doubled, by what factor does the root-mean-square speed increase?
Answer
The root-mean-square speed is proportional to \( \sqrt{T} \). Therefore, doubling \( T \) increases \( v_{\mathrm{rms}} \) by a factor of \( \sqrt{2} \approx 1.414 \). - Which is larger for a given gas at a given temperature: the most probable speed or the mean speed?
Answer
The mean speed is larger. The distribution is skewed to the right, so the average value is pulled higher than the peak of the distribution. Specifically, \( \langle v \rangle = \sqrt{\frac{8}{\pi}} v_p \approx 1.13 v_p \).
Problem set for PU-203 →
Each derivation in this unit ends with five graded problems with full solutions.
Lecture notes checked line by line by the editor; every number in the worked example was recomputed.
Derivations cited: D-014 · D-156 · Threads: energy, matter, chance