Physics:Isothermal–isobaric ensemble

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Short description: Ensemble of states at constant pressure

The isothermal–isobaric ensemble (constant temperature and constant pressure ensemble) is a statistical mechanical ensemble that maintains constant temperature [math]\displaystyle{ T \, }[/math] and constant pressure [math]\displaystyle{ P \, }[/math] applied. It is also called the [math]\displaystyle{ NpT }[/math]-ensemble, where the number of particles [math]\displaystyle{ N \, }[/math] 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.[1] 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.[2]

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

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

Derivation of key properties

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

[math]\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)) }[/math],

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

[math]\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)) }[/math].

If this system is then brought into contact with a bath of volume [math]\displaystyle{ V_0 }[/math] at constant temperature and pressure containing an ideal gas with total particle number [math]\displaystyle{ M }[/math] such that [math]\displaystyle{ M-N \gg N }[/math], the partition function of the whole system is simply the product of the partition functions of the subsystems:

[math]\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)) }[/math].
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The system (volume [math]\displaystyle{ V }[/math]) is immersed in a much larger bath of constant temperature, and closed off such that particle number remains fixed. The system is separated from the bath by a piston that is free to move, such that its volume can change.

The integral over the [math]\displaystyle{ \mathbf{s}^{M-N} }[/math] coordinates is simply [math]\displaystyle{ 1 }[/math]. In the limit that [math]\displaystyle{ V_0 \rightarrow \infty }[/math], [math]\displaystyle{ M \rightarrow \infty }[/math] while [math]\displaystyle{ (M-N)/V_0=\rho }[/math] stays constant, a change in volume of the system under study will not change the pressure [math]\displaystyle{ p }[/math] of the whole system. Taking [math]\displaystyle{ V/V_0 \rightarrow 0 }[/math] allows for the approximation [math]\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) }[/math]. For an ideal gas, [math]\displaystyle{ (M-N)/V_0 = \rho = \beta P }[/math] gives a relationship between density and pressure. Substituting this into the above expression for the partition function, multiplying by a factor [math]\displaystyle{ \beta P }[/math] (see below for justification for this step), and integrating over the volume V then gives

[math]\displaystyle{ \Delta^{sys+bath}(N, P, T) = \frac{\beta P V_0^{M-N}}{\Lambda^{3M}N!(M-N)!}\int dV V^N \exp({-\beta P V}) \int d\mathbf{s}^N \exp(-\beta U(\mathbf{s})) }[/math].

The partition function for the bath is simply [math]\displaystyle{ \Delta^{bath}=V_0^{M-N}/[(M-N)!\Lambda^{3(M-N)} }[/math]. Separating this term out of the overall expression gives the partition function for the [math]\displaystyle{ NpT }[/math]-ensemble:

[math]\displaystyle{ \Delta^{sys}(N, P, T) = \frac{\beta P}{\Lambda^{3N}N!} \int dV V^N \exp(-\beta P V) \int d\mathbf{s}^N \exp(-\beta U(\mathbf{s})) }[/math].

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

[math]\displaystyle{ \Delta^{sys}(N, P, T) = \beta P \int dV \exp(-\beta P V) Z^{sys}(N, V, T) }[/math],

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

[math]\displaystyle{ \Delta(N, P, T) = \int Z(N, V, T) \exp(-\beta PV ) C dV. \,\; }[/math]

The quantity [math]\displaystyle{ C }[/math] is simply some constant with units of inverse volume, which is necessary to make the integral dimensionless. In this case, [math]\displaystyle{ C=\beta P }[/math], 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.[2] This problem has been addressed in multiple ways by various authors,[3][4] leading to values for C with the same units of inverse volume. The differences vanish (i.e. the choice of [math]\displaystyle{ C }[/math] becomes arbitrary) in the thermodynamic limit, where the number of particles goes to infinity.[5]

The [math]\displaystyle{ NpT }[/math]-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 [math]\displaystyle{ T }[/math] and external forces acting on the system [math]\displaystyle{ \mathbf{J} }[/math]. Consider such a system containing [math]\displaystyle{ N }[/math] particles. The Hamiltonian of the system is then given by [math]\displaystyle{ \mathcal{H}-\mathbf{J} \cdot \mathbf{x} }[/math] where [math]\displaystyle{ \mathcal{H} }[/math] is the system's Hamiltonian in the absence of external forces and [math]\displaystyle{ \mathbf{x} }[/math] are the conjugate variables of [math]\displaystyle{ \mathbf{J} }[/math]. The microstates [math]\displaystyle{ \mu }[/math] of the system then occur with probability defined by [6]

[math]\displaystyle{ p(\mu,\mathbf{x})=\exp[-\beta \mathcal{H}(\mu)+\beta \mathbf{J} \cdot \mathbf{x}]/\mathcal{Z} }[/math]

where the normalization factor [math]\displaystyle{ \mathcal{Z} }[/math] is defined by

[math]\displaystyle{ \mathcal{Z}(N, \mathbf{J}, T)=\sum_{\mu,\mathbf{x}} \exp[\beta \mathbf{J} \cdot \mathbf{x} - \beta \mathcal{H}(\mu)] }[/math].

This distribution is called generalized Boltzmann distribution by some authors.[7]

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

[math]\displaystyle{ \mathcal{Z}(N, \mathbf{J}, T)=\sum_{\mu, \{\mathbf{r}_i\} \in V} \exp[-\beta P V - \beta(\mathbf{p}^2/2m+U(\mathbf{r}^N))] }[/math],

where the Hamiltonian has been written in terms of the particle momenta [math]\displaystyle{ \mathbf{p}_i }[/math] and positions [math]\displaystyle{ \mathbf{r}_i }[/math]. This sum can be taken to an integral over both [math]\displaystyle{ V }[/math] and the microstates [math]\displaystyle{ \mu }[/math]. The measure for the latter integral is the standard measure of phase space for identical particles: [math]\displaystyle{ \textrm{d} \Gamma_N = \frac{1}{h^3N!}\prod_{i=1}^N d^3\mathbf{p}_i d^3\mathbf{r}_i }[/math].[6] The integral over [math]\displaystyle{ \exp(-\beta \mathbf{p}^2/2m) }[/math] term is a Gaussian integral, and can be evaluated explicitly as

[math]\displaystyle{ \int \prod_{i=1}^N \frac{d^3\mathbf{p}_i}{h^3}\exp\bigg[-\beta \sum_{i=1}^N \frac{p^2_i}{2m}\bigg] = \frac{1}{\Lambda^{3N}} }[/math] .

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

[math]\displaystyle{ \mathcal{Z}(N, P, T) = \frac{1}{\Lambda^{3N}N!} \int dV \exp(-\beta P V) \int d\mathbf{r}^N \exp(-\beta U(\mathbf{r})) = \int dV \exp(-\beta P V)Z(N, V, T) }[/math].[6]

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

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

[math]\displaystyle{ G(N, P, T) = - k_B T \ln \Delta(N, P, T) \;\, }[/math]

This thermodynamic potential is related to the Helmholtz free energy (logarithm of the canonical partition function), [math]\displaystyle{ F\, }[/math], in the following way:[1]

[math]\displaystyle{ G = F+PV. \;\, }[/math]

Applications

  • Constant-pressure simulations are useful for determining the equation of state of a pure system. Monte Carlo simulations using the [math]\displaystyle{ NpT }[/math]-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.[2]
  • Zero-pressure [math]\displaystyle{ NpT }[/math]-ensemble simulations provide a quick way of estimating vapor-liquid coexistence curves in mixed-phase systems.[2]
  • [math]\displaystyle{ NpT }[/math]-ensemble Monte Carlo simulations have been applied to study the excess properties[8] and equations of state [9] of various models of fluid mixtures.
  • The [math]\displaystyle{ NpT }[/math]-ensemble is also useful in molecular dynamics simulations, e.g. to model the behavior of water at ambient conditions.[10]

References

  1. 1.0 1.1 Dill, Ken A.; Bromberg, Sarina; Stigter, Dirk (2003). Molecular Driving Forces. New York: Garland Science. 
  2. 2.0 2.1 2.2 2.3 2.4 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. doi:10.1063/1.469956. Bibcode1995JChPh.103.9884A. 
  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. 6.0 6.1 6.2 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. doi:10.1063/1.5111333. PMID 31325924. Bibcode2019JChPh.151c4113G. https://aip.scitation.org/doi/abs/10.1063/1.5111333. 
  8. McDonald, I. R. (1972). "[math]\displaystyle{ NpT }[/math]-ensemble Monte Carlo calculations for binary liquid mixtures". Molecular Physics 23 (1): 41–58. doi:10.1080/00268977200100031. Bibcode1972MolPh..23...41M. 
  9. Wood, W. W. (1970). "[math]\displaystyle{ NpT }[/math]-Ensemble Monte Carlo Calculations for the Hard Disk Fluid". Journal of Chemical Physics 52 (2): 729–741. doi:10.1063/1.1673047. Bibcode1970JChPh..52..729W. 
  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. PMID 19663399.