The Boltzmann distribution describes the probability that a system in thermal equilibrium at temperature T will be in a specific microstate with energy E. This probability is proportional to the Boltzmann factor, [latex]e^{-E / k_B T}[/latex]. It implies that states with lower energy are exponentially more likely to be occupied than states with higher energy, with temperature modulating this preference.
The Boltzmann Distribution
- Ludwig Boltzmann
The Boltzmann distribution is a cornerstone of statistical mecánica and is arguably its most useful result for practical applications. It can be derived by considering a small system in thermal contact with a large heat reservoir. The combined system (system + reservoir) is isolated, and by applying Boltzmann’s entropy principle ([latex]S = k_B \ln W[/latex]) to the reservoir, one can find the most probable energy distribution for the small system. The result is that the probability of the system being in state ‘i’ with energy [latex]E_i[/latex] is [latex]P_i \propto e^{-E_i/k_B T}[/latex].
The term [latex]k_B T[/latex] represents the characteristic thermal energy available at temperature T. The ratio [latex]E/k_B T[/latex] is dimensionless and determines the probability. If a state’s energy E is much less than the thermal energy ([latex]E \ll k_B T[/latex]), the exponential factor is close to 1, and the state is highly probable. If the energy is much greater than the thermal energy ([latex]E \gg k_B T[/latex]), the factor is very small, and the state is very unlikely to be occupied. This exponential dependence is responsible for many phenomena, such as the rapid increase in chemical reaction rates with temperature, as more molecules possess the necessary activation energy.
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Precursors
- James Clerk Maxwell’s distribution of molecular speeds in a gas (a specific case of the Boltzmann distribution)
- The kinetic theory of gases, which linked temperature to average kinetic energy
- Rudolf Clausius’s work on heat and the second law of thermodynamics
- The development of probability theory
Aplicaciones
- semiconductor physics to determine the density of charge carriers
- atmospheric science to model pressure variation with altitude (barometric formula)
- chemical kinetics for the temperature dependence of reaction rates (arrhenius equation)
- espectroscopia for understanding the doppler broadening of spectral lines
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