Chemical potential and fugacity

AI Thread Summary
The discussion centers on the definition and equivalence of chemical potential and fugacity in statistical physics. The author explores how chemical potential is defined in both Maxwell-Boltzmann and quantum statistics, highlighting the confusion arising from its dual presentation. They clarify that chemical potential should be defined in the context of the Grand Canonical Ensemble, where particle number can vary, leading to the relation μ = (∂U/∂N)_{S,V}. The author successfully derives the relationship between chemical potential and fugacity, showing that α = -μ/kT and β = 1/kT, thus proving the equivalence. This exploration emphasizes the importance of a unified definition of chemical potential in thermodynamic equations.
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I am trying to learn statistical physics. While learning MB statistics, my textbook defined chemical potential as ##\mu = (\frac{\partial F}{\partial N})_{V,T}##. That's nice.

Later when I started on Quantum statistics, my textbook described all three distribution functions via:
##n_i = \frac{g_i}{e^{\alpha + \beta E_i} + \kappa}##
We had already found out the value of beta from MB statistics (using MB distr. function. Why would that apply here is another mystery altogether)

Then suddenly book said:
##n_i = \frac{g_i}{e^{\frac{E_i - \mu}{K_B T}} + \kappa}##

Where we define chemical potential via the relation ##\alpha = -\mu/kT## (and its exponential is called fugacity)

How and why did the book define the same thing twice!?
 
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To all future people who want to know: I found out how can we show equivalence.

We need to define mu only once, but neither in these places. We need to define mu in the fundamental thermodynamic equation:

First consider Grand Canonical Ensemble, that is, allow particle number to change.

Generalise first and second laws into this:

##dU = TdS - PdV + \mu dN##
We define ##\mu## as the rate of change of energy per unit change in particle number.

Then from this relation, ##\mu = (\frac{\partial U}{\partial N})_{S,V}##
F = U-TS
So, ##dF=-PdV - SdT + \mu dN##
##\Rightarrow \mu = (\frac{\partial F}{\partial N})_{T,V}## (Yaay!)

Now while deriving the distribution function by maximizing the log of number of microstates and using method of Lagrange multipliers we got:

##d(lnW) = \alpha dN + \beta dE##
So, ##\alpha = (\frac{\partial ln(W)}{\partial N})_{E,V}##

But we know ##S=k_B ln(W)## (separate derivation for that. But it is standalone)
##\Rightarrow lnW = \frac{S}{k_B}##
##\Rightarrow \alpha = \frac{1}{k_B} (\frac{\partial S}{\partial N})_{E,V}##

Now, ##TdS=dU+PdV-\mu dN##
##(\frac{\partial S}{\partial N})_{U,V} = \frac{-\mu}{T}##

Therefore, ##\alpha = \frac{-\mu}{kT}## (Yaaaay!)

Similarly we can show that ##\beta = \frac{1}{kT}##

Hence Proved.
 
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