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The mixing entropy formula derived in the previous problem actually applies to any ideal gas, and to some dense gases, liquids, and solids as well. For the denser systems, we have to assume that the two types of molecules are the same size and that molecules of different types interact with each other in the same way as molecules of the same type (same forces, etc.). Such a system is called an ideal mixture. Explain why, for an ideal mixture, the mixing entropy is given by

ΔSmixing=klnNNA

where Nis the total number of molecules and NAis the number of molecules of type A. Use Stirling's approximation to show that this expression is the same as the result of the previous problem when both Nand NAare large.

Short Answer

Expert verified

The chane in entropy mixing for an ideal mixture isΔSmixingNk[(1x)ln(1x)+xlnx]

Step by step solution

01

Step: 1  Equating entropy:

Let's say we start with a set of Nidentical molecules. This system's entropy is a number S0, which may or may not be straightforward to determine. Assume that we suddenly transform NAof these molecules to a new species at some point in the future (which has similar properties to the original species as mentioned).The amount of different ways we may select to locate these NAmolecules among the Nsites accessible will increase the entropy.

The entropy of mixing is:

ΔSmixing=klnNNA

The Coefficient binomial is

ΔSmixing=klnN!NA!NNA!

where,NA=(1-x)N

ΔSmixing=klnN!((1x)N)!(xN)!

02

Step: 2 Stirling's approximation:

By using Stirling's approximationn!2πnnnen,the factorial is

N!2πNNNeNxN!2πxN(xN)xNexN(1x)N!2π(1x)N((1x)N)(1x)Ne(x1)N

Substitutiong values,we get

ΔSmixingkln2πNNNeN2π(1x)N((1x)N)(1x)Ne(x1)N2πxN(xN)xNexNΔSmixingkln2πNNN2π(1x)N((1x)N)(1x)N2πxN(xN)xNΔSmixingklnNN2πNx(1x)((1x)N)(1x)N(xN)xN

03

Step: 3 Finding entropy mixing value:

Where,ln(ab)=ln(a)+ln(b);lnab=ln(a)ln(b)

we get,

ΔSmixingkNlnN12ln(2πNx(1x))((1x)N)ln((1x)N)xNln(xN)

Taking third term part

((1x)N)ln((1x)N)=((1x)N)(ln(1x)+ln(N))((1x)N)ln((1x)N)=Nln(1x)+xNln(1x)Nln(N)+xNln(N)

Taking fourth term part

xNln(xN)=xNlnxxNlnN

The entropy mixing by

ΔSmixingk12ln(2πNx(1x))(1x)Nln(1x)xNlnxΔSmixingNk[(1x)ln(1x)+xlnx]

The first component in the second line has been omitted since it is insignificant in comparison to the following two terms for bigN.

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Most popular questions from this chapter

Problem 2.20. Suppose you were to shrink Figure2.7until the entire horizontal scale fits on the page. How wide would the peak be?

This problem gives an alternative approach to estimating the width of the peak of the multiplicity function for a system of two large Einstein solids.

(a) Consider two identical Einstein solids, each with Noscillators, in thermal contact with each other. Suppose that the total number of energy units in the combined system is exactly 2N. How many different macrostates (that is, possible values for the total energy in the first solid) are there for this combined system?

(b) Use the result of Problem2.18to find an approximate expression for the total number of microstates for the combined system. (Hint: Treat the combined system as a single Einstein solid. Do not throw away factors of "large" numbers, since you will eventually be dividing two "very large" numbers that are nearly equal. Answer: 24N/8πN.)

(c) The most likely macrostate for this system is (of course) the one in which the energy is shared equally between the two solids. Use the result of Problem 2.18to find an approximate expression for the multiplicity of this macrostate. (Answer:24N/(4πN) .)

(d) You can get a rough idea of the "sharpness" of the multiplicity function by comparing your answers to parts (b) and (c). Part (c) tells you the height of the peak, while part (b) tells you the total area under the entire graph. As a very crude approximation, pretend that the peak's shape is rectangular. In this case, how wide would it be? Out of all the macrostates, what fraction have reasonably large probabilities? Evaluate this fraction numerically for the case N=1023.

Use a pocket calculator to check the accuracy of Stirling's approximation forN=50 . Also check the accuracy of equation 2.16forlnN! .

A black hole is a region of space where gravity is so strong that nothing, not even light, can escape. Throwing something into a black hole is therefore an irreversible process, at least in the everyday sense of the word. In fact, it is irreversible in the thermodynamic sense as well: Adding mass to a black hole increases the black hole's entropy. It turns out that there's no way to tell (at least from outside) what kind of matter has gone into making a black hole. Therefore, the entropy of a black hole must be greater than the entropy of any conceivable type of matter that could have been used to create it. Knowing this, it's not hard to estimate the entropy of a black hole.
aUse dimensional analysis to show that a black hole of mass Mshould have a radius of order GM/c2, where Gis Newton's gravitational constant and cis the speed of light. Calculate the approximate radius of a one-solar-mass black holeM=2×1030kg .
bIn the spirit of Problem 2.36, explain why the entropy of a black hole, in fundamental units, should be of the order of the maximum number of particles that could have been used to make it.

cTo make a black hole out of the maximum possible number of particles, you should use particles with the lowest possible energy: long-wavelength photons (or other massless particles). But the wavelength can't be any longer than the size of the black hole. By setting the total energy of the photons equal toMc2 , estimate the maximum number of photons that could be used to make a black hole of mass M. Aside from a factor of 8π2, your result should agree with the exact formula for the entropy of a black hole, obtained* through a much more difficult calculation:

Sb.h.=8π2GM2hck

d Calculate the entropy of a one-solar-mass black hole, and comment on the result.

Suppose you flip 50fair coins.

(a) How many possible outcomes (microstates) are there?

(b) How many ways are there of getting exactly25heads and25tails?

(c) What is the probability of getting exactly 25heads and 25tails?

(d) What is the probability of getting exactly 30heads and 20tails?

(e) What is the probability of getting exactly 40heads and 10 tails?

(f) What is the probability of getting 50heads and no tails?

(g) Plot a graph of the probability of getting n heads, as a function of n.

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