Structural Optimization Design of Microfluidic Chips Based on Fast Sequence Pair Algorithm

The market for microfluidic chips is experiencing significant growth; however, their development is hindered by a complex design process and low efficiency. Enhancing microfluidic chips' design quality and efficiency has emerged as an integral approach to foster their advancement. Currently, the existing structural design schemes lack careful consideration regarding the impact of chip area, microchannel length, and the number of intersections on chip design. This inadequacy leads to redundant chip structures resulting from the separation of layout and wiring design. This study proposes a structural optimization method for microfluidic chips to address these issues utilizing a simulated annealing algorithm. The simulated annealing algorithm generates an initial solution in advance using the fast sequence pair algorithm. Subsequently, an improved simulated annealing algorithm is employed to obtain the optimal solution for the device layout. During the wiring stage, an advanced wiring method is used to designate the high wiring area, thereby increasing the success rate of microfluidic chip wiring. Furthermore, the connection between layout and routing is reinforced through an improved layout adjustment method, which reduces the length of microchannels and the number of intersections. Finally, the effectiveness of the structural optimization approach is validated through six sets of test cases, successfully achieving the objective of enhancing the design quality of microfluidic chips.

Automated summary

The market for microfluidic chips is growing significantly, but their development is hindered by a complex design process and low efficiency. Enhancing the design quality and efficiency of microfluidic chips has become an important approach to promote their advancement. The existing structural design schemes lack consideration of factors such as chip area, microchannel length, and the number of intersections, resulting in redundant chip structures. This study proposes a structural optimization method that utilizes a simulated annealing algorithm to address these issues and successfully enhances the design quality of microfluidic chips through validation with test cases.