deletions | additions       diff --git a/2.tex b/2.tex  index dbf5f69..b75bd9c 100644  --- a/2.tex  +++ b/2.tex 
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[A]=\frac{k_{-1}k_{-2}A_0}{k_1k_2+k_{-1}k_{-2}+k_1k_{-2}}+\frac{A_0(k_1k_2+k_1k_{-2})}{k_1k_2+k_{-1}k_{-2}+k_1k_{-2}}\mathrm{e}^{-k_1t}  \end{equation}  Thus, by inspection of Eqns (12) and (19), $x_1 \approx k_1$. Equation (4) may be similarly rearranged and integrated to solve assuming equilibrium conditions, where $x_3 \approx k_{-2}$.  Unfortunately, equations (12)-(14) cannot be expressly used to determine exact values for $k_1$, $k_{-1}$, $k_2$, and $k_{-2}$ explicitly because those variables are coupled. coupled (recall the simplifying assumption that a three-component exponential fit to the experimental data converges to a two-component exponential fit when values of $m$ and $n$ are similar).  It is, however, relatively straight-forward to determine $K_1$ and $K2$ $K_2$  by fitting the experimental data with a function of the form $y(t) = y_0+\alpha{}\mathrm{e}^{-\beta{}t}$ to obtain $y_0$ for $A$, $B$, and $C$. It then follows that \begin{equation}  K_1=\frac{y_0(B)}{y_0(A)}  \end{equation}