Isothermal–isobaric ensemble

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The isothermal–isobaric ensemble (constant temperature and constant pressure ensemble) is a statistical mechanical ensemble that maintains constant temperature T and constant pressure P applied. It is also called the NpT-ensemble, where the number of particles 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.[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 i is Z1eβ(E(i)+pV(i)), where Z is the partition function, E(i) is the internal energy of the system in microstate i, and V(i) is the volume of the system in microstate i. The probability of a macrostate is Z1eβ(E+pVTS)=Z1eβG, where G is the Gibbs free energy.

Derivation of key properties

The partition function for the NpT-ensemble can be derived from statistical mechanics by beginning with a system of N identical atoms described by a Hamiltonian of the form p2/2m+U(rn) and contained within a box of volume V=L3. This system is described by the partition function of the canonical ensemble in 3 dimensions:

Zsys(N,V,T)=1Λ3NN!0L...0LdrNexp(βU(rN)),

where Λ=h2β/(2πm), the thermal de Broglie wavelength (β=1/kBT and kB is the Boltzmann constant), and the factor 1/N! (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 Lsi=ri such that the partition function becomes

Zsys(N,V,T)=VNΛ3NN!01...01dsNexp(βU(sN)).

If this system is then brought into contact with a bath of volume V0 at constant temperature and pressure containing an ideal gas with total particle number M such that MNN, the partition function of the whole system is simply the product of the partition functions of the subsystems:

Zsys+bath(N,V,T)=VN(V0V)MNΛ3MN!(MN)!dsMNdsNexp(βU(sN)).
File:Constant pressure system immersed in a constant temperature bath.png
The system (volume V) 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 sMN coordinates is simply 1. In the limit that V0, M while (MN)/V0=ρ stays constant, a change in volume of the system under study will not change the pressure p of the whole system. Taking V/V00 allows for the approximation (V0V)MN=V0MN(1V/V0)MNV0MNexp((MN)V/V0). For an ideal gas, (MN)/V0=ρ=βP gives a relationship between density and pressure. Substituting this into the above expression for the partition function, multiplying by a factor βP (see below for justification for this step), and integrating over the volume V then gives

Δsys+bath(N,P,T)=βPV0MNΛ3MN!(MN)!dVVNexp(βPV)dsNexp(βU(s)).

The partition function for the bath is simply Δbath=V0MN/[(MN)!Λ3(MN). Separating this term out of the overall expression gives the partition function for the NpT-ensemble:

Δsys(N,P,T)=βPΛ3NN!dVVNexp(βPV)dsNexp(βU(s)).

Using the above definition of Zsys(N,V,T), the partition function can be rewritten as

Δsys(N,P,T)=βPdVexp(βPV)Zsys(N,V,T),

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

Δ(N,P,T)=Z(N,V,T)exp(βPV)CdV.

The quantity C is simply some constant with units of inverse volume, which is necessary to make the integral dimensionless. In this case, C=βP, 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 C becomes arbitrary) in the thermodynamic limit, where the number of particles goes to infinity.[5] The 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 T and external forces acting on the system J. Consider such a system containing N particles. The Hamiltonian of the system is then given by Jx where is the system's Hamiltonian in the absence of external forces and x are the conjugate variables of J. The microstates μ of the system then occur with probability defined by [6]

p(μ,x)=exp[β(μ)+βJx]/𝒵

where the normalization factor 𝒵 is defined by

𝒵(N,J,T)=μ,xexp[βJxβ(μ)].

This distribution is called generalized Boltzmann distribution by some authors.[7] The NpT-ensemble can be found by taking J=P and x=V. Then the normalization factor becomes

𝒵(N,J,T)=μ,{ri}Vexp[βPVβ(p2/2m+U(rN))],

where the Hamiltonian has been written in terms of the particle momenta pi and positions ri. This sum can be taken to an integral over both V and the microstates μ. The measure for the latter integral is the standard measure of phase space for identical particles: dΓN=1h3N!i=1Nd3pid3ri.[6] The integral over exp(βp2/2m) term is a Gaussian integral, and can be evaluated explicitly as

i=1Nd3pih3exp[βi=1Npi22m]=1Λ3N .

Inserting this result into 𝒵(N,P,T) gives a familiar expression:

𝒵(N,P,T)=1Λ3NN!dVexp(βPV)drNexp(βU(r))=dVexp(βPV)Z(N,V,T).[6]

This is almost the partition function for the NpT-ensemble, but it has units of volume, an unavoidable consequence of taking the above sum over volumes into an integral. Restoring the constant C yields the proper result for Δ(N,P,T). From the preceding analysis it is clear that the characteristic state function of this ensemble is the Gibbs free energy,

G(N,P,T)=kBTlnΔ(N,P,T)

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

G=F+PV.

Applications

  • Constant-pressure simulations are useful for determining the equation of state of a pure system. Monte Carlo simulations using the 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.[2]
  • Zero-pressure NpT-ensemble simulations provide a quick way of estimating vapor-liquid coexistence curves in mixed-phase systems.[2]
  • NpT-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 NpT-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. 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. 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. arXiv:1903.02121. Bibcode:2019JChPh.151c4113G. doi:10.1063/1.5111333. PMID 31325924. S2CID 118981017.
  8. McDonald, I. R. (1972). "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). "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.