Team:TU-Delft/Modeling/Diffusion

From 2012.igem.org

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Partial Differential Equations (PDE) are used to solve this problem.
Partial Differential Equations (PDE) are used to solve this problem.
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== Approach ==
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Now we have a complete problem that we will solve using a numerical approach.
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Put this in the pressure domain.
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== Boundary conditions ==
== Boundary conditions ==
Two boundary conditions are set for these two surfaces of petridish-gas and gas-agar.
Two boundary conditions are set for these two surfaces of petridish-gas and gas-agar.
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For the problem definition to be complete and be able to start programming in MATLAB  
For the problem definition to be complete and be able to start programming in MATLAB  
we only need one more value, being the diffusion coefficient. For this an empirical relation from the [1] was used.
we only need one more value, being the diffusion coefficient. For this an empirical relation from the [1] was used.
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== PDE ==
 
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Now we have a complete problem that we will solve using a numerical approach.
 
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Put this in the pressure domain.
 
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And you probably guessed but my value for h is ok in the model and in my code this translates to the line:
And you probably guessed but my value for h is ok in the model and in my code this translates to the line:

Revision as of 20:49, 26 September 2012

Team:TUDelft/CSSLaksh Menu

Diffusion Model

One of the main objectives of the project was to synthesize a practical device, the Snifferometer for tuberculosis detection. As a first step towards achieving this goal, we built a temporal model of the system using PDE's which was simulated in matlab. A 2D reaction-diffusion system was then implemented in COMSOL multiphysics using the knowledge obtained from single cell pathway model,ombining the behaviours of the which helped us get a better understanding of how such a device could be implemented and the response times involved in such a process.

Contents

Diffusion Model

Setup of diffusion model

Figure 1: Full structure of diffusion device.

The diffusion setup contains two parts: petridish of smelling liquid/solid in the bottom and agar of olfactory yeast on the top.

Modeling of this setup was especially done to evaluate the speed of diffusion from the ligand phase to the yeast cells themselves and see if this behavior is slow or quick with respect to the biochemical behavior of the yeast.

Partial Differential Equations (PDE) are used to solve this problem.


Approach

Now we have a complete problem that we will solve using a numerical approach. Put this in the pressure domain.

Boundary conditions

Two boundary conditions are set for these two surfaces of petridish-gas and gas-agar.

  • At x=0, the Dirichlet boundary condition was placed:

DirichletBC.PNG

with Psat being the saturation pressure of the specific compound being IsoAmylAcetate as an example in our model. For IsoAmylAcetate this value is 533.3 Pa at room temperature.

  • One can take Neumann boundary condition at x=l, where l is the distant between petridish and agar and assumed to be 0.01 meter.

NeumannBC.PNG

In this part of the system the molecules bounce against the agar surface back into the gasphase. A van Neumann boundary is the way to give a mathematical workable structure to that. For the problem definition to be complete and be able to start programming in MATLAB we only need one more value, being the diffusion coefficient. For this an empirical relation from the [1] was used.

And you probably guessed but my value for h is ok in the model and in my code this translates to the line:

dcdt(i,1)= a*x(i-1,1)+a*x(i+1,1) -2*a*x(i,1);

and YES a=h here and YES that IS confusing considering the other above statements. What I basically did is grab a bunch of Ordinary differential equations and couples them So that it becomes a PDE ( partial differential equation ). H*time step should also not be bigger than 0.5 and that does not happen, so the solution is stable.

Analytical solutions for this problem appeared a little more troublesome than expected. There are solutions ( in Sum row form ), but I was anticipating a nice function. I will get a book at the library to see if there are any better ones, but for now this works out fine. I can also use a Cranck-Nicolson approach to the problem to have another numerical solution for verification. And last but not least. The results:

Figure 2: Simulation of diffusion model.(in 3D Cartesian coordinate, X axis is time, Y axis is the distance from the petridish, Z axis is the concentration)

Figure 2 shows the simulation result with distance dimension 0 - 0.01 meter and the time dimension 0 - 100 seconds. From Figure2 it can be seen after 100 seconds it approximately reaches steady state at the x=0.01 boundary.

Snifferometer

One of the other goals of the diffusion modeling was to model the device which we intended to build for the project. We made use of the finite element analysis simulator Comsol Multiphysics[3]

for developing this model.
Figure 1: Snifferometer - Device with the modified yeast cells for sensing

Different models were analyzed for their suitability before coming to the final design in Figure. The device at the bottom has a membrance preventing the yeast coming in direct contact with external substances, above which is a layer of agar in which yeast is placed, the nutrients for it's growth is fed in through a channel along the sides of the tube using which the yeast cells can also be replaced as and when needed. A micro-optrode is then used to sense the photons emitted by the fluoroscent proteins.

Saliva Model

File:Test1.swf

References

Chen, N. H. (1962). New Generalized Equation for Gas Diffusion Coefficient. J. Chem. Eng. Data, 37–41.