Biosensor diffusion equation solution

In summary, the conversation discusses the solution of a diffusion-capture problem in an online lecture by Prof. Allam, which is further elaborated in a research paper. The key to arriving at the expression for N(t) is to solve two equations and substitute the solution into the first one, resulting in the given expression for N(t).
  • #1
mzh
64
0
Hi
In this online lecture (click "View Presentation"), Prof. Allam discusses the solution of a diffusion-capture problem.
On slide 8, he formulates two equations
[tex]I = C_0 (\rho_0 - \rho_S)\\
I = A \frac{dN}{dt} = A k_F N_0 \rho_S[/tex]
from which he arrives at an expression for [tex]N(t)[/tex], namely [tex]N(t)=\rho_0 t\left[\frac{A}{C_0} + \frac{1}{k_F}\right]^{-1}.[/tex]

Here, [tex]I, C_0, \rho_0, \rho_S[/tex] indicate a flux of the species with concentration [tex]N[/tex] over a surface [tex]A[/tex] and [tex]\rho_0, \rho_S[/tex] are the concentrations in equilibrium and at the surface of the sensor where the capture with the rate [tex]k_F[/tex] happens.

Can someone point me out on how to arrive at the expression for [tex]N(t)[/tex]? Would be greatly appreciated.
The work is further discussed in Nair et al., APL 88, 233120, 2006.
 
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  • #2
The key to arriving at the expression for N(t) is to solve the two equations given above. To do this, first solve for I in terms of \rho_S:I = C_0(\rho_0 - \rho_S)I = A k_F N_0 \rho_STherefore,C_0(\rho_0 - \rho_S) = A k_F N_0 \rho_SMultiplying both sides by \rho_S,C_0 \rho_0 \rho_S - C_0 \rho_S^2 = A k_F N_0 \rho_S^2Rearranging,C_0 \rho_S^2 - (A k_F N_0 + C_0) \rho_S + C_0 \rho_0 = 0Solving for \rho_S,\rho_S = \frac{A k_F N_0 + C_0 \pm \sqrt{(A k_F N_0 + C_0)^2 - 4 C_0^2 \rho_0}}{2C_0}Substituting \rho_S into the first equation,I = C_0 \left[ \rho_0 - \frac{A k_F N_0 + C_0 \pm \sqrt{(A k_F N_0 + C_0)^2 - 4 C_0^2 \rho_0}}{2C_0} \right]Simplifying and rearranging,N(t) = \frac{I}{C_0} \left[ \frac{A}{C_0} + \frac{1}{k_F} \right]^{-1} which is the expression for N(t) given in the question.
 

Related to Biosensor diffusion equation solution

1. What is the biosensor diffusion equation?

The biosensor diffusion equation is a mathematical model that describes the transport of molecules within a biosensor. It takes into account factors such as diffusion, convection, and reaction kinetics to predict the concentration of molecules at different points in the biosensor.

2. Why is solving the biosensor diffusion equation important?

Solving the biosensor diffusion equation is important because it allows us to understand and optimize the performance of biosensors. By predicting the concentration profiles of molecules, we can determine the sensitivity and response time of a biosensor, which are crucial factors in its effectiveness.

3. How is the biosensor diffusion equation solved?

The biosensor diffusion equation is usually solved by using numerical methods, such as finite difference or finite element methods. These methods break down the equation into smaller, solvable parts and use iterative calculations to find the solution.

4. What are the assumptions made in the biosensor diffusion equation?

Some common assumptions made in the biosensor diffusion equation include steady-state conditions, uniform diffusion coefficients, and negligible convection. These assumptions may not always hold true in real-life situations, but they allow for a simpler and more tractable solution to the equation.

5. Can the biosensor diffusion equation be applied to all types of biosensors?

No, the biosensor diffusion equation is most commonly used for biosensors that involve diffusion as the main transport mechanism. Biosensors that rely on other transport mechanisms, such as convection or electrical current, may require different equations to describe their behavior.

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