Statistical Mechanics - Change in Entropy

In summary, the conversation discusses a system of N distinguishable particles with two energy states, in contact with a heat bath at temperature T. A quantum process occurs where the populations of the two states change, resulting in a change in entropy for both the two level system and the heat bath. The solution for the change in entropy of the two level system can be simplified using Boltzmann's hypothesis and Stirling's approximation, resulting in the solution \Delta S_{2LS}=k_{B}\, ln(n_{1}/n_{2}).
  • #1
NewtonApple
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Homework Statement



A system of N distinguishable particles is arranged such that each particle can exist in one of the two states: one has energy [itex]\epsilon_{1}[/itex], the other has energy [itex]\epsilon_{2}[/itex]. The populations of these states are [itex]n_{1}[/itex] and [itex]n_{2}[/itex] respectively, ([itex]N = n_{1}+n_{2}[/itex]). The system is placed in contact with a heat bath at temperature T. A simple quantum process occurs in which the populations change: [itex]n_{2}\rightarrow n_{2} - 1[/itex] and [itex]n_{1}\rightarrow n_{1} + 1[/itex] with the energy released going into the heat bath.

(a) Calculate the change in the entropy of the two level system.
(b) Calculate the change in the entropy of the heat bath.
(c) If the process is reversible, what is the ratio of [itex]n_{2}[/itex] to [itex]n_{1}[/itex]?

Homework Equations



Boltzmann's Hypothesis - Entropy (S) is [itex]S=k_{B}ln(W)[/itex]

Stirling's approximation for large factorials [itex] ln N! = N\,ln\,N - N [/itex]

The Attempt at a Solution



The number of ways for initial state

[itex]W_{i}=\frac{N!}{n_{1}!\, n_{2}!}[/itex]​

The number of ways for final state

[itex]W_{f}=\frac{N!}{({n_{2}-1)!\, (n_{1}+1)!}}[/itex]​

Using [itex]S=k_{B}ln(W)[/itex] Change in Entropy is

[itex]\Delta S_{2LS} = S_{f}-S_{i} = k_{B}\Big [ln W_{f} - ln W_{i}\Big ] = k_{B}\Big [\frac {ln W_{f}}{ln W_{i}}\Big ][/itex]​

Substituting values from above and simplifying

[itex]\Delta S_{2LS} = S_{f}-S_{i} =k_{B} ln \Big[\frac{n_{1}!\, n_{2}!} {(n_{2}-1)!\, (n_{1}+1)!} \Big ][/itex]​
Using Stirling's approximation [itex] ln N! = N\,ln\,N - N [/itex]


[itex]\Delta S_{2LS}=k_{B} \Big[ \frac{ \big(n_{1}\, ln(n_{1})-n_{1}))(n_{2}\, ln(n_{2})-n_{2})\big)}{ \big( (n_{2}-1)ln(n_{2}-1)-(n_{2}-1)\big ) \big((n_{1}+1)ln(n_{1}+1)-(n_{1}+1)\big) } \Big] [/itex]​

and simplifying


[itex]\Delta S_{2LS}=k_{B} [n_{1} \, ln(n_1) + n_{2} \, ln(n_2) - (n_{2}-1) \, ln(n_{2}-1) - (n_{1}+1) \, ln(n_{1} + 1)] [/itex]​
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.
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Suppose to get following Solution

[itex]\Delta S_{2LS}=k_{B}\, ln(n_{1}/n_{2}) [/itex]​

No idea how to get it used all simplification techniques. Please give me some hints.
 
Last edited:
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  • #2
Hello, NewtonApple and welcome to PF!

NewtonApple said:
[itex]\Delta S_{2LS} = S_{f}-S_{i} =k_{B} ln \Big[\frac{n_{1}!\, n_{2}!} {(n_{2}-1)!\, (n_{1}+1)!} \Big ][/itex]

You should be able to greatly simplify this without resorting to Stirling.
 
Last edited:
  • #3
Thanks a bunch TSny!
 

Related to Statistical Mechanics - Change in Entropy

1. What is statistical mechanics?

Statistical mechanics is a branch of physics that uses statistical methods to explain the behavior of large systems of particles. It provides a framework for understanding the macroscopic properties of a system by studying the microscopic behavior of its constituent particles.

2. What is entropy in statistical mechanics?

In statistical mechanics, entropy is a measure of the disorder or randomness of a system. It is a fundamental concept that is used to quantify the amount of energy that is unavailable for work in a thermodynamic process.

3. How does entropy change in a closed system?

In a closed system, entropy tends to increase over time. This is due to the second law of thermodynamics, which states that the total entropy of a closed system will never decrease. This means that the system will naturally tend towards a state of maximum disorder.

4. What factors influence the change in entropy?

The change in entropy of a system is influenced by various factors, including temperature, pressure, and the number of particles in the system. Changes in these variables can cause the particles in the system to rearrange and increase or decrease the system's overall disorder, resulting in a change in entropy.

5. Can entropy ever decrease in a system?

In theory, it is possible for entropy to decrease in a system. However, this would require a highly unlikely and specific arrangement of particles, and it would only be a temporary decrease. In the long run, the overall trend of entropy is always towards an increase.

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