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v t e

The isothermal–isobaric ensemble (constant temperature and constant pressure ensemble) is a statistical mechanical ensemble that maintains constant temperature ${\displaystyle T\,}$ and constant pressure ${\displaystyle P\,}$ applied. It is also called the ${\displaystyle NpT}$-ensemble, where the number of particles ${\displaystyle N\,}$ is also kept as a constant. This ensemble plays an important role in chemistry as chemical reactions are usually carried out under constant pressure condition. The NPT ensemble is also useful for measuring the equation of state of model systems whose virial expansion for pressure cannot be evaluated, or systems near first-order phase transitions.

In the ensemble, the probability of a microstate ${\displaystyle i}$ is ${\displaystyle Z^{-1}e^{-\beta (E(i)+pV(i))}}$, where ${\displaystyle Z}$ is the partition function, ${\displaystyle E(i)}$ is the internal energy of the system in microstate ${\displaystyle i}$, and ${\displaystyle V(i)}$ is the volume of the system in microstate ${\displaystyle i}$.

The probability of a macrostate is ${\displaystyle Z^{-1}e^{-\beta (E+pV-TS)}=Z^{-1}e^{-\beta G}}$, where ${\displaystyle G}$ is the Gibbs free energy.

Derivation of key properties

The partition function for the ${\displaystyle NpT}$-ensemble can be derived from statistical mechanics by beginning with a system of ${\displaystyle N}$ identical atoms described by a Hamiltonian of the form ${\displaystyle \mathbf {p} ^{2}/2m+U(\mathbf {r} ^{n})}$ and contained within a box of volume ${\displaystyle V=L^{3}}$. This system is described by the partition function of the canonical ensemble in 3 dimensions:

${\displaystyle Z^{sys}(N,V,T)={\frac {1}{\Lambda ^{3N}N!}}\int _{0}^{L}...\int _{0}^{L}d\mathbf {r} ^{N}\exp(-\beta U(\mathbf {r} ^{N}))}$,

where ${\displaystyle \Lambda ={\sqrt {h^{2}\beta /(2\pi m)}}}$, the thermal de Broglie wavelength (${\displaystyle \beta =1/k_{B}T\,}$ and ${\displaystyle k_{B}\,}$ is the Boltzmann constant), and the factor ${\displaystyle 1/N!}$ (which accounts for indistinguishability of particles) both ensure normalization of entropy in the quasi-classical limit. It is convenient to adopt a new set of coordinates defined by ${\displaystyle L\mathbf {s} _{i}=\mathbf {r} _{i}}$ such that the partition function becomes

${\displaystyle Z^{sys}(N,V,T)={\frac {V^{N}}{\Lambda ^{3N}N!}}\int _{0}^{1}...\int _{0}^{1}d\mathbf {s} ^{N}\exp(-\beta U(\mathbf {s} ^{N}))}$.

If this system is then brought into contact with a bath of volume ${\displaystyle V_{0}}$ at constant temperature and pressure containing an ideal gas with total particle number ${\displaystyle M}$ such that ${\displaystyle M-N\gg N}$, the partition function of the whole system is simply the product of the partition functions of the subsystems:

${\displaystyle Z^{sys+bath}(N,V,T)={\frac {V^{N}(V_{0}-V)^{M-N}}{\Lambda ^{3M}N!(M-N)!}}\int d\mathbf {s} ^{M-N}\int d\mathbf {s} ^{N}\exp(-\beta U(\mathbf {s} ^{N}))}$.

The integral over the ${\displaystyle \mathbf {s} ^{M-N}}$ coordinates is simply ${\displaystyle 1}$. In the limit that ${\displaystyle V_{0}\rightarrow \infty }$, ${\displaystyle M\rightarrow \infty }$ while ${\displaystyle (M-N)/V_{0}=\rho }$ stays constant, a change in volume of the system under study will not change the pressure ${\displaystyle p}$ of the whole system. Taking ${\displaystyle V/V_{0}\rightarrow 0}$ allows for the approximation ${\displaystyle (V_{0}-V)^{M-N}=V_{0}^{M-N}(1-V/V_{0})^{M-N}\approx V_{0}^{M-N}\exp(-(M-N)V/V_{0})}$. For an ideal gas, ${\displaystyle (M-N)/V_{0}=\rho =\beta P}$ gives a relationship between density and pressure. Substituting this into the above expression for the partition function, multiplying by a factor ${\displaystyle \beta P}$ (see below for justification for this step), and integrating over the volume V then gives

${\displaystyle \Delta ^{sys+bath}(N,P,T)={\frac {\beta PV_{0}^{M-N}}{\Lambda ^{3M}N!(M-N)!}}\int dVV^{N}\exp({-\beta PV})\int d\mathbf {s} ^{N}\exp(-\beta U(\mathbf {s} ))}$.

The partition function for the bath is simply ${\displaystyle \Delta ^{bath}=V_{0}^{M-N}/[(M-N)!\Lambda ^{3(M-N)}}$. Separating this term out of the overall expression gives the partition function for the ${\displaystyle NpT}$-ensemble:

${\displaystyle \Delta ^{sys}(N,P,T)={\frac {\beta P}{\Lambda ^{3N}N!}}\int dVV^{N}\exp(-\beta PV)\int d\mathbf {s} ^{N}\exp(-\beta U(\mathbf {s} ))}$.

Using the above definition of ${\displaystyle Z^{sys}(N,V,T)}$, the partition function can be rewritten as

${\displaystyle \Delta ^{sys}(N,P,T)=\beta P\int dV\exp(-\beta PV)Z^{sys}(N,V,T)}$,

which can be written more generally as a weighted sum over the partition function for the canonical ensemble

${\displaystyle \Delta (N,P,T)=\int Z(N,V,T)\exp(-\beta PV)CdV.\,\;}$

The quantity ${\displaystyle C}$ is simply some constant with units of inverse volume, which is necessary to make the integral dimensionless. In this case, ${\displaystyle C=\beta P}$, but in general it can take on multiple values. The ambiguity in its choice stems from the fact that volume is not a quantity that can be counted (unlike e.g. the number of particles), and so there is no “natural metric” for the final volume integration performed in the above derivation. This problem has been addressed in multiple ways by various authors, leading to values for C with the same units of inverse volume. The differences vanish (i.e. the choice of ${\displaystyle C}$ becomes arbitrary) in the thermodynamic limit, where the number of particles goes to infinity.

The ${\displaystyle NpT}$-ensemble can also be viewed as a special case of the Gibbs canonical ensemble, in which the macrostates of the system are defined according to external temperature ${\displaystyle T}$ and external forces acting on the system ${\displaystyle \mathbf {J} }$. Consider such a system containing ${\displaystyle N}$ particles. The Hamiltonian of the system is then given by ${\displaystyle {\mathcal {H}}-\mathbf {J} \cdot \mathbf {x} }$ where ${\displaystyle {\mathcal {H}}}$ is the system's Hamiltonian in the absence of external forces and ${\displaystyle \mathbf {x} }$ are the conjugate variables of ${\displaystyle \mathbf {J} }$. The microstates ${\displaystyle \mu }$ of the system then occur with probability defined by

${\displaystyle p(\mu ,\mathbf {x} )=\exp/{\mathcal {Z}}}$

where the normalization factor ${\displaystyle {\mathcal {Z}}}$ is defined by

${\displaystyle {\mathcal {Z}}(N,\mathbf {J} ,T)=\sum _{\mu ,\mathbf {x} }\exp}$.

This distribution is called generalized Boltzmann distribution by some authors.

The ${\displaystyle NpT}$-ensemble can be found by taking ${\displaystyle \mathbf {J} =-P}$ and ${\displaystyle \mathbf {x} =V}$. Then the normalization factor becomes

${\displaystyle {\mathcal {Z}}(N,\mathbf {J} ,T)=\sum _{\mu ,\{\mathbf {r} _{i}\}\in V}\exp}$,

where the Hamiltonian has been written in terms of the particle momenta ${\displaystyle \mathbf {p} _{i}}$ and positions ${\displaystyle \mathbf {r} _{i}}$. This sum can be taken to an integral over both ${\displaystyle V}$ and the microstates ${\displaystyle \mu }$. The measure for the latter integral is the standard measure of phase space for identical particles: ${\displaystyle {\textrm {d}}\Gamma _{N}={\frac {1}{h^{3}N!}}\prod _{i=1}^{N}d^{3}\mathbf {p} _{i}d^{3}\mathbf {r} _{i}}$. The integral over ${\displaystyle \exp(-\beta \mathbf {p} ^{2}/2m)}$ term is a Gaussian integral, and can be evaluated explicitly as

${\displaystyle \int \prod _{i=1}^{N}{\frac {d^{3}\mathbf {p} _{i}}{h^{3}}}\exp {\bigg }={\frac {1}{\Lambda ^{3N}}}}$ .

Inserting this result into ${\displaystyle {\mathcal {Z}}(N,P,T)}$ gives a familiar expression:

${\displaystyle {\mathcal {Z}}(N,P,T)={\frac {1}{\Lambda ^{3N}N!}}\int dV\exp(-\beta PV)\int d\mathbf {r} ^{N}\exp(-\beta U(\mathbf {r} ))=\int dV\exp(-\beta PV)Z(N,V,T)}$.

This is almost the partition function for the ${\displaystyle NpT}$-ensemble, but it has units of volume, an unavoidable consequence of taking the above sum over volumes into an integral. Restoring the constant ${\displaystyle C}$ yields the proper result for ${\displaystyle \Delta (N,P,T)}$.

From the preceding analysis it is clear that the characteristic state function of this ensemble is the Gibbs free energy,

${\displaystyle G(N,P,T)=-k_{B}T\ln \Delta (N,P,T)\;\,}$

This thermodynamic potential is related to the Helmholtz free energy (logarithm of the canonical partition function), ${\displaystyle F\,}$, in the following way:

${\displaystyle G=F+PV.\;\,}$

Applications

• Constant-pressure simulations are useful for determining the equation of state of a pure system. Monte Carlo simulations using the ${\displaystyle NpT}$-ensemble are particularly useful for determining the equation of state of fluids at pressures of around 1 atm, where they can achieve accurate results with much less computational time than other ensembles.
• Zero-pressure ${\displaystyle NpT}$-ensemble simulations provide a quick way of estimating vapor-liquid coexistence curves in mixed-phase systems.
• ${\displaystyle NpT}$-ensemble Monte Carlo simulations have been applied to study the excess properties and equations of state of various models of fluid mixtures.
• The ${\displaystyle NpT}$-ensemble is also useful in molecular dynamics simulations, e.g. to model the behavior of water at ambient conditions.

References

1. ^ Dill, Ken A.; Bromberg, Sarina; Stigter, Dirk (2003). Molecular Driving Forces. New York: Garland Science.
2. ^ Frenkel, Daan.; Smit, Berend (2002). Understanding Molecular Simluation. New York: Academic Press.
3. Attard, Phil (1995). "On the density of volume states in the isobaric ensemble". Journal of Chemical Physics. 103 (24): 9884–9885. Bibcode:1995JChPh.103.9884A. doi:10.1063/1.469956.
4. Koper, Ger J. M.; Reiss, Howard (1996). "Length Scale for the Constant Pressure Ensemble: Application to Small Systems and Relation to Einstein Fluctuation Theory". Journal of Physical Chemistry. 100 (1): 422–432. doi:10.1021/jp951819f.
5. Hill, Terrence (1987). Statistical Mechanics: Principles and Selected Applications. New York: Dover.
6. ^ Kardar, Mehran (2007). Statistical Physics of Particles. New York: Cambridge University Press.
7. Gao, Xiang; Gallicchio, Emilio; Roitberg, Adrian (2019). "The generalized Boltzmann distribution is the only distribution in which the Gibbs-Shannon entropy equals the thermodynamic entropy". The Journal of Chemical Physics. 151 (3): 034113. arXiv:1903.02121. Bibcode:2019JChPh.151c4113G. doi:10.1063/1.5111333. PMID 31325924. S2CID 118981017.
8. McDonald, I. R. (1972). "${\displaystyle NpT}$-ensemble Monte Carlo calculations for binary liquid mixtures". Molecular Physics. 23 (1): 41–58. Bibcode:1972MolPh..23...41M. doi:10.1080/00268977200100031.
9. Wood, W. W. (1970). "${\displaystyle NpT}$-Ensemble Monte Carlo Calculations for the Hard Disk Fluid". Journal of Chemical Physics. 52 (2): 729–741. Bibcode:1970JChPh..52..729W. doi:10.1063/1.1673047.
10. Schmidt, Jochen; VandeVondele, Joost; Kuo, I. F. William; Sebastiani, Daniel; Siepmann, J. Ilja; Hutter, Jürg; Mundy, Christopher J. (2009). "Isobaric-Isothermal Molecular Dynamics Simulations Utilizing Density Functional Theory:An Assessment of the Structure and Density of Water at Near-Ambient Conditions". Journal of Physical Chemistry B. 113 (35): 11959–11964. doi:10.1021/jp901990u. OSTI 980890. PMID 19663399.

v t e Statistical mechanics
Theory	Principle of maximum entropy ergodic theory
Statistical thermodynamics	Ensembles partition functions equations of state thermodynamic potential: U H F G Maxwell relations
Models	Ferromagnetism models Ising Potts Heisenberg percolation Particles with force field depletion force Lennard-Jones potential
Mathematical approaches	Boltzmann equation H-theorem Vlasov equation BBGKY hierarchy stochastic process mean-field theory and conformal field theory
Critical phenomena	Phase transition Critical exponents correlation length size scaling
Entropy	Boltzmann Shannon Tsallis Rényi von Neumann
Applications	Statistical field theory elementary particle superfluidity Condensed matter physics Complex system chaos information theory Boltzmann machine

• Statistical ensembles