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Lecture 6: Intro to Entropy Reading: Zumdahl 10.1, 10.3 Outline: –Why enthalpy isn’t enough. –Statistical interpretation of entropy –Boltzmann’s Formula.

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Presentation on theme: "Lecture 6: Intro to Entropy Reading: Zumdahl 10.1, 10.3 Outline: –Why enthalpy isn’t enough. –Statistical interpretation of entropy –Boltzmann’s Formula."— Presentation transcript:

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2 Lecture 6: Intro to Entropy Reading: Zumdahl 10.1, 10.3 Outline: –Why enthalpy isn’t enough. –Statistical interpretation of entropy –Boltzmann’s Formula

3 Enthalpy and Spontaneous Rxns Early on in the development of thermodynamics, it was believed that if a reaction was exothermic, it was spontaneous. Consider the following reaction: H 2 O(s) H 2 O(l)  H° rxn = +6.02 kJ Endothermic…..yet spontaneous!

4 Enthalpy and Spontaneous Rxns Consider the following problem: Mixing of a gas inside a bulb adiabatically (q = 0). q = 0, w = 0,  E = 0, and  H = 0 ….but it still happens

5 Statistical Interpretation of Entropy Imagine that we have a collection of 3 distinguishable particles who have a total energy of 3 . Let’s ask the question, “How will this fixed amount of energy distribute itself over the particles?”

6 Statistics and Entropy (cont.) Our system consists of three distinguishable particles. There are three “quanta” of energy (  ) available for a total of energy of “3  ”

7 First Arrangement: All on one The first possible arrangement we consider is one in which all energy resides on one particle There are three ways to do this

8 Second Arrangement: 2, 1, 0 Next arrangement: 2  on 1, 1  on another, and the third has 0  Six ways to do this

9 Third Arrangement The final possible arrangement is 1  on each particle. Only one way to do this.

10 Which Arrangement? Which arrangement is most probable? Ans: The arrangement which the greatest number of possibilities In this case: “2, 1, 0”

11 The Dominant Configuration Configuration: a type of energy distribution. Microstate: a specific arrangement of energy corresponding to a configuration. Which configuration will you see? The one with the largest # of microstates. This is called the dominant configuration.

12 Determining Weight Weight (  ): the number of microstates associated with a given configuration. We need to determine , without having to write down all the microstates. A = the number of particles in your system. a i is the number of particles with the same amount of energy. ! = factorial, and  means take the product. 

13 Determining Weight (cont.) Consider 300 students where 3 students have 1  of energy, and the other 297 have none. A = 300 a 1 = 3 a 0 = 297 = 4.5 x 10 6

14 Weight and Entropy The connection between weight (  ) and entropy (S) is given by Boltzmann’s Formula: S = kln  k = Boltzmann’s constant = R/N a = 1.38 x 10 -23 J/K The dominant configuration will have the largest  ; therefore, S is greatest for this configuration

15 Example: Crystal of CO Consider the depiction of crystalline CO. There are two possible arrangements for each CO molecule. Each arrangement of CO is possible. For a mole of CO:  = N a !/(N a /2!) 2 = 2 Na

16 Example: Crystal of CO For a mole of CO:  = N a !/(N a /2!) 2 = 2 Na Then, S = k ln(  ) = k ln (2 Na ) = N a k ln(2) = R ln(2) = 5.64 J/mol.K

17 Another Example: Expansion What is  S for the expansion of an ideal gas from V 1 to 2V 1 ? Focus on an individual particle. After expansion, each particle will have twice the number of positions available.

18 Expansion (cont.) Original Weight =  Final Weight =  Then  S = S 2 -S 1 = k ln(2  ) - kln(  ) = k ln(2  /  ) = k ln(2)

19 Expansion (cont.) Therefore, the  S per particle = k ln (2) For a mole of particles:  S = k ln (2 Na ) = N a k ln(2) = R ln(2) = 5.64 J/mol.K

20 Expansion (cont.) Note in the previous example that weight was directly proportional to volume. Generalizing:  S = k ln (  final ) - kln(  initial ) = k ln(  final /  initial ) = Nk ln(  final /  initial ) for N molec. = Nkln(V final /V initial )


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