Abstract:
Sample Preparation is the most necessary step in biochemical applications. Various
biochemical reactants are mixed together to produce mixture with target concentration.
Many algorithms have been proposed for reactant minimization and to reduce
tranportation time during sample preparation on DMFBs in the recent years. In recent
years, it have been seen that there is a fault in mixture hardware on DMFBs. Due to fault
on mixture, droplets are not mixed homogeneously during sample preparation on
DMFBs. Due to non-homogeneous mixing different part of mixed droplet may contain
different concentration of reactants. There are various algorithm developed for sample
preparation of biochemical assay but none of them are aiming reliability purpose due to
hardware fault. We implemented new technique Monte Carlo Simulation aiming
reliability during sample preparation by using different existing algorithm on DMFBs .
We are using Monte Carlo Simulation in Min-Mix[1], RMA[8] and MTCS[2] algorithm
for sample preparation if there is an inhomogeneous mixing on hardware mixture. It uses
mixing tree constructed by different algorithm and propagate error on each mixing node
then calculate actual concentration due to error. We observed that MTCS gives better
performance than Min-Mix and RMA because it uses common sub-tree, which creates a
re-convergent fan out in the tree, due to which it reduces error. Furthermore, Monte Carlo
Simulation technique can be implemented to other single target sample preparation as
well as multi target sample preparation. So this technique is very useful to know which
particular algorithm is more reliable for a specific ratio if there is an inhomogeneous
mixing in the hardware mixture on DMFBs.
