77 |
|
\label{introEq:SM2} |
78 |
|
\end{equation} |
79 |
|
|
80 |
< |
The solution to Eq.~\ref{introEq:SM2} maximizes the number of |
80 |
> |
The solution of interest to Eq.~\ref{introEq:SM2} maximizes the number of |
81 |
|
degenerate configurations in $E$. \cite{Frenkel1996} |
82 |
|
This gives |
83 |
|
\begin{equation} |
101 |
|
degeneracy in Eq.~\ref{introEq:SM3} and the second law of |
102 |
|
thermodynamics. Namely, that for a closed system, entropy will |
103 |
|
increase for an irreversible process.\cite{chandler:1987} Here the |
104 |
< |
process is the partitioning of energy among the two systems. This |
104 |
> |
maximization of the degeneracy when partitioning the energy of the system can be likened to the maximization of the entropy for this process. This |
105 |
|
allows the following definition of entropy: |
106 |
|
\begin{equation} |
107 |
|
S = k_B \ln \Omega(E), |
383 |
|
Eq.~\ref{introEq:MCmarkovEquil} is solved such that |
384 |
|
$\boldsymbol{\rho}_{\text{limit}}$ matches the Boltzmann distribution |
385 |
|
of states. The method accomplishes this by imposing the strong |
386 |
< |
condition of microscopic reversibility on the equilibrium |
387 |
< |
distribution. This means that at equilibrium, the probability of going |
386 |
> |
condition of detailed balance on the equilibrium |
387 |
> |
distribution. This means that the probability of going |
388 |
|
from $m$ to $n$ is the same as going from $n$ to $m$, |
389 |
|
\begin{equation} |
390 |
|
\rho_m\pi_{mn} = \rho_n\pi_{nm}. |
401 |
|
For a Boltzmann limiting distribution, |
402 |
|
\begin{equation} |
403 |
|
\frac{\rho_n}{\rho_m} = e^{-\beta[\mathcal{U}(n) - \mathcal{U}(m)]} |
404 |
< |
= e^{-\beta \Delta \mathcal{U}}. |
404 |
> |
= e^{-\beta \Delta \mathcal{U}}, |
405 |
|
\label{introEq:MCmicro3} |
406 |
|
\end{equation} |
407 |
< |
This allows for the following set of acceptance rules be defined: |
407 |
> |
where $\Delta\mathcal{U}$ is the change in the total energy of the system. This allows for the following set of acceptance rules be defined: |
408 |
|
\begin{equation} |
409 |
|
\accMe( m \rightarrow n ) = |
410 |
|
\begin{cases} |
921 |
|
|
922 |
|
The chapter concerning random sequential adsorption simulations is a |
923 |
|
study in applying Statistical Mechanics simulation techniques in order |
924 |
< |
to obtain a simple model capable of explaining the results. My |
924 |
> |
to obtain a simple model capable of explaining experimental observations. My |
925 |
|
advisor, Dr. Gezelter, and I were approached by a colleague, |
926 |
|
Dr. Lieberman, about possible explanations for the partial coverage of |
927 |
|
a gold surface by a particular compound synthesized in her group. We |