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Verified Commit ef921b2a authored by Simon Josef Thür's avatar Simon Josef Thür
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sum more fixes

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......@@ -67,8 +67,12 @@ And by extension
Rearranging the above, we find an expression for the potential:
\begin{align}
\phi & =\frac{kT}{q}\ln\frac{n}{n_i} \label{label:eq:boltzman:phi_n} \\
\phi & = -\frac{kT}{q}\ln\frac{p}{n_i} \label{label:eq:boltzman:phi_p}
\phi_n & =\frac{kT}{q}\ln\frac{n}{n_i} \label{label:eq:boltzman:phi_n} \\
\phi_p & = -\frac{kT}{q}\ln\frac{p}{n_i} \label{label:eq:boltzman:phi_p} \\
\begin{split}
\phi_B & = \phi_n-\phi_p \\
& = \frac{kT}{q} \ln\frac{N_A N_D}{n_i^2}
\end{split} \label{label:eq:boltzman:phi_B}
\end{align}
For Si at room temperature this is an increase of 60 mV per decade in doping.
\begin{equation}
......
......@@ -32,17 +32,17 @@ Importantly, the SCR resistance ist the most important one and others can be neg
\subsection{Space charge region (SCR)}
In essence, applying a forward/reverse bias effects the depletion region:
\begin{align}
\phi_B & \rightarrow \phi_B-V_{pn} \\
x_n(V) & =\sqrt{\frac{2\varepsilon(\phi_B-V)N_a}{q(N_a+N_d)N_d}} \\
x_p(V) & =\sqrt{\frac{2\varepsilon(\phi_B-V)N_d}{q(N_a+N_d)N_a}} \\
x_d(V) & =\sqrt{\frac{2\varepsilon(\phi_B-V)N_dN_a}{q(N_a+N_d)}} \\
\left|E(V)\right| & =\sqrt{\frac{2q(\phi_B-V)(N_aN_d)}{\varepsilon(N_a+N_d)}}
\phi_B & \rightarrow \phi_B-V_{pn} \\
x_n(V) & =\sqrt{\frac{2\varepsilon(\phi_B-V)N_a}{q(N_a+N_d)N_d}} \\
x_p(V) & =\sqrt{\frac{2\varepsilon(\phi_B-V)N_d}{q(N_a+N_d)N_a}} \\
x_d(V) & =\sqrt{\frac{2\varepsilon(\phi_B-V)(N_a+N_d)}{q N_d N_a}} \\
\left|E(V)\right| & =\sqrt{\frac{2q(\phi_B-V) N_a N_d}{\varepsilon (N_a + N_d)}}
\end{align}
In the case of a strongly doped $p^+n$ junction,
we can approximate the SCR since it exists only in the lesser doped region.
\begin{equation}
x_n(V)=x_{n0}\sqrt{a-\frac{V}{\phi_B}}
x_n(V)=x_{n0}\sqrt{1-\frac{V}{\phi_B}}
\end{equation}
......@@ -55,7 +55,7 @@ In reverse bias, the PN junction acts as a capacitor.
So as a function of the bias voltage, we get
\begin{equation}
\begin{split}
C_j(V) &= \frac{\varepsilon}{x_c(V)}\\
C_j(V) &= \frac{\varepsilon}{x_d(V)}\\
&=\sqrt{\frac{q\varepsilon N_aN_d}{2q(\phi_B-V)(N_a+N_d)}}\\
&=\frac{C_{j0}}{\sqrt{1-\frac{V}{\phi_B}}}
\end{split}
......
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