An Optimization Algorithm for Digital Microfluidic Biochip Performance Using Interval Method

For biochemical investigation, a Digital Microfluidic Biochip (DMFB) is a Lab-on-Chip (LoC) device that uses electro-wetting-on-dielectric (EWoD) technology. It has several advantages over conventional laboratory settings. DMFBs reduce dependency on error-prone human activities by automating labor-intensive, complicated processes with increased accuracy and efficiency. By maximizing chemical use and reducing waste, this automation lowers lab space, material costs, and test completion times. The DMFB controls sample preparation operations like stirring, separation, integration, and washing-where chemical solutions are mixed in precise ratios to provide precise solution volumes-through electrical actuation. DMFB systems aim to achieve high precision in reagent ratios while reducing liquid use, stirring frequency, processing time, and liquid waste in order to increase efficiency. Our suggested approach attempts to optimize DMFB operations by limiting intake, stirring, and repository units and reducing stirring operations, repository counts, and liquid transfers. In the “stirring tree,” which represents the complete sample preparation procedure, the algorithm also minimizes the number of “stirring steps,” which gauge the amount of time spent mixing. In comparison to the Reservoir-Constrained optimal Scheduling (RCS) technique, our solution reduces stirring steps by 18% and transfer operations by 8% by implementing an interval-based scheduling strategy. These enhancements increase the device's efficacy for biochemical experiments by improving DMFB efficiency, resource utilization, and operational accuracy.