Counting multiplicities of a particle lattice

In summary, the entropy of mixing is the number of configurations, W_{a}, of a system, in state A, after all of the N+M sites are available to all the particles. The total number of configurations, W_{b}, of the system, is the sum of the number of configurations, W_{a}, for each of the populations of red balls, green balls, and empty spaces, after the particles remain distinguishable by color. The ratio of W_{a} to W_{b} is the same for both systems, but the entropy of mixing is greater for the system with more indistinguishable balls.
  • #1
E'lir Kramer
74
0
This is from Molecular Driving Forces, 2nd Ed.

5.3: Calculating the entropy of mixing. Consider a lattice with N sites and n green particles, and another lattice with M sites and m red particles. These lattices cannot exchange particles. This is state A.

(a) What is the total number of configurations, [itex]W_{a}[/itex] of the system in state A?

[itex]{{N}\choose{n}}{{M}\choose{m}}[/itex]

(b) Now assume that all of the N+M sites are available to all the green and red particles. The particles remain distinguishable by their color. This is state B. What is the total configurations [itex]W_{b}[/itex] of the system?

I'm counting it like this: we have three species: red balls, green balls, and empty spaces, with a population of n, m, and (N+M-n-m) respectively. There are N+M total sites, so we have

[itex]\frac{(N+M)!}{n!m!(N+M-n-m)!}[/itex]

Now take N =M and n =m for the following two problems:
(c) Using Stirling's approximation, what is the ratio of [itex]\frac{W_{a}}{W_{b}}[/itex]?

For [itex]W_{a} = {{N}\choose{n}}{{N}\choose{n}} \\
= \left(\frac{N!}{n!(N-n)!}\right)^{2} \\
≈ \left(\frac{\left(\frac{N}{e}\right)^{N}}{\left( \frac{n}{e}\right)^{n}\left(\frac{N-n}{e}\right)^{(N-n)}}\right)^{2} \\
= \left(\frac{N^{N}}{n^{n} (N-n)^{(N-n)}}\right)^{2} \\
= \frac{N^{2N}}{n^{2n} (N-n)^{2(N-n)}} \\
[/itex]

[itex]
W_{b} = \frac{(2N)!}{n!n!((2(N-n))!} \\
≈ \frac{(2N)^{2N}}{n^{2n}(2(N-n))^{2(N-n)}} \\
= \frac{2^{2N}N^{2N}}{2^{2(N-n)}n^{2n}(N-n)^{2(N-n)}} \\
= \frac{2^{2n}N^{2N}}{n^{2n}(N-n)^{2(N-n)}} \\
[/itex]

These are the same except for a factor of [itex]2^{2n}[/itex] in the numerator of [itex]W_{b}[/itex], so [itex]\frac{W_{a}}{W_{b}} = \frac{1}{2^{2n}}[/itex]


Now while I was trying to figure out how to count a system of red balls and green balls, I started by trying to count a simpler model: a system of size 2N with 2n indistinguishable balls. I assumed that this system would have a higher multiplicity than two systems of size N with n balls each.

In other words, I assumed that [itex]{{N}\choose{n}}^{2} < {{2N}\choose{2n}}[/itex].

I reasoned that the multiplicity of my new system of 2n indistinguishable balls, call it state C, would be approximated by Sterling's approximation like this:

[itex]W_{c} ≈ \frac{(2N)^{2N}}{(2n)^{2n}(2(N-n))^{2(N-n)}}[/itex]

But after manipulation, I found that:

[itex]
W_{c} ≈ \frac{(2N)^{2N}}{(2n)^{2n}(2(N-n))^{2(N-n)}} \\
= \frac{2^{2N}N^{2N}}{2^{2n}2^{2(N-n)}n^{2n}(N-n)^{2(N-n)}} \\
= \frac{N^{2N}}{n^{2n}(N-n)^{2(N-n)}} \\
= W_{a}
[/itex]

But since [itex]W_{a} = {{N}\choose{n}}^{2} \\
W_{c} = {{2N}\choose{2n}} \\
[/itex]
We have [itex] {{N}\choose{n}}^{2} = {{2N}\choose{2n}} [/itex] for N sufficiently large.

I have confirmed with code that [itex] \frac{lim}{N \to ∞} ({{N}\choose{\frac{N}{2}}}^{2} / {{2N}\choose{N}} ) = 0 [/itex], so [itex] {{N}\choose{\frac{N}{2}}}^{2} ≠ {{2N}\choose{N}} [/itex]

This implies that I've miscounted either [itex]W_{a}[/itex] or [itex]W_{c}[/itex] - could someone show me the way?
 
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  • #2
You have to use a more accurate approximation for n!. You left out the √(2πn) part.
Suppose we write p = n/N. Then ##{{N}\choose{n}} ≈ \left(p^p\left(1-p\right)^{1-p}\right)^{-N-\frac12} \left(2\pi N\right)^{-\frac12}##
Writing ##r = p^p\left(1-p\right)^{1-p}##, ##{{N}\choose{n}} ≈ r^{-N} \left(2\pi r N\right)^{-\frac12}##
So ##{{N}\choose{n}}^2 ≈ r^{-2N} \left(2\pi r N\right)^{-1}##, ##{{2N}\choose{2n}} ≈ r^{-2N} \left(4\pi r N\right)^{-\frac12}##. The ratio of these is ##\left(\pi r N\right)^{\frac12}##
 
  • #3
Thank you!
 

What is a particle lattice?

A particle lattice is a regular arrangement of identical particles in a crystal structure. These particles can be atoms, molecules, or ions.

Why is it important to count multiplicities of a particle lattice?

Counting multiplicities allows us to understand the different ways that particles can be arranged in a lattice, which can provide insights into the physical properties of the material.

How is the multiplicity of a particle lattice calculated?

The multiplicity of a particle lattice is calculated by considering the number of ways that the particles can be arranged while still maintaining the same crystal structure. This involves calculating the number of lattice points, the number of particles per lattice point, and the number of symmetry operations that can be applied to the lattice.

What factors can affect the multiplicity of a particle lattice?

The multiplicity of a particle lattice can be affected by the size and shape of the particles, the type of lattice structure, and any external influences such as temperature or pressure.

How is the multiplicity of a particle lattice used in materials science?

The multiplicity of a particle lattice is used in materials science to predict and understand the physical and chemical properties of materials. This information can also be used in the development of new materials with specific properties for various applications.

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