Reactant and Waste Minimization in Multitarget Sample Preparation on Digital Microfluidic Biochips

An open-source compiler and PCB synthesis tool for digital microfluidic biochips

“…In Table 1, the term CV is shorthand for concentration value, i.e., the desired concentration of a target droplet. Six of the algorithms that we have implemented generate a dilution tree that produces one droplet of a desired CV, using different optimization strategies [11,19,29,65,66,72]; four more algorithms generate multi-output DAGs (sometimes, but not always, a forest of trees) that produce multiple droplets of desired CVs [4,28,30,54]. The aforementioned algorithms all assume that one sample fluid is diluted with a buffer (a non-reactive fluid that maintains the pH of the sample fluid during dilution).…”

Sample preparation for many-reactant bioassay on DMFBs using common dilution operation sharing

“…A reasonable approximation would be 〈341, 341, 342〉 if the precision level d is set to 10. That is, the value of d determines the minimal unit in a concentration value, and the quantization error is thus limited to 1 2 +1 [18] [29]. One can choose a sufficiently large d to ensure the associated quantization error is tolerable.…”

“…In this experiment, we randomly select a set of k different target concentrations where k = 1, 2, 3, 10, 20, 50, and 100 for multi-target sample preparation, just as [22], [25], [26], and [29]. The results of BS, RSMA, CoDOS, and extended CoDOS are reported in Table II.…”

“…Several studies addressing the sample preparation problem on DMFBs have been proposed [15]- [29]. Most of them regard the total count of waste droplets or the total amount of required reactants as the minimization goal.…”

Recent Advances in Applications of Droplet Microfluidics

“…Lai et al developed an intelligent digital microfluidic processor for biomedical detection [25]. Huang et al proposed a reactant and waste minimization algorithm for multitarget sample preparation on digital microfluidic biochips [26]. Chen et al developed a reliability-oriented placement algorithm for reconfigurable digital microfluidic biochips by using a 3D deferred decision making technique to optimize bioassay completion times [27].…”