Experimental investigation of replication accuracy of polymer-based microfluidic chip fabricated through induction-assisted hot embossing and parametric optimization through nature-inspired algorithms

Abstract

Hot embossing (HE) creates micron-scaled patterns on a polymer substrate. Conventional-HE faces a long cycle-time issue and reduces productivity. An induction-assisted HE (IHE) setup was developed in-house to solve this issue. A microfluidic chip was made using an in-house developed setup on polymethyl methacrylate. Micro-features on aluminum-6061 mold were made using fiber laser machining instead of photolithography, followed-by reactive ion etching or electroplating to save both costs and time. Accurate micropattern replication is vital for HE. Embossing factors affect replication accuracy. Less deviation in micro-channel depth improves replication accuracy. The experimental data was gathered via L27 orthogonal array. Linear regression was used to connect process parameters and response variables. The embossing temperature affects micro-channel depth by 79.78%. Particle swarm optimization, artificial bee colony (ABC), firefly algorithm (FA), and grey wolf optimization (GWO) optimized IHE process parameters. Firefly algorithm outperformed. The FA converged in four iterations, whereas particle swarm optimization took 12 and ABC 38. All methods (excluding GWO) reached 6.5809 μm, the global best. A confirmation test shows optimal operating conditions reduce embossed micro-channel depth variation from 126.758 μm to 7.0327 μm and improve replication accuracy from 19.94% to 95.50%. The predicted and experimental embossed micro-channel depth deviation percentile error is 6.86%. An IHE setup was used to bond the microfluidic chip. The microchannel in the microfluidic chip was treated with vaporized bonding before thermal bonding to prevent deformation/blocking. No blue ink leaked during the testing of the manufactured microfluidic chip, showing acceptable quality.