Sign in Subscribe
Technical institutes

Breakthrough in Mechanical Engineering: Induction-Assisted Hot Embossing for Microfluidic Chip Fabrication

Strategic Insights

— 2 min read

Investigations at the National Institute of Technology in West Bengal, India, have led to a significant advancement in mechanical engineering, particularly in the field of microfluidic chip fabrication. Researchers have developed an induction-assisted hot embossing (IHE) setup to overcome the limitations of conventional hot embossing, which faces a long cycle-time issue and reduces productivity. By employing IHE, the team successfully created micron-scaled patterns on a polymer substrate, demonstrating improved replication accuracy and reduced costs.

Key Takeaways:

  • The IHE setup was developed in-house to solve the long cycle-time issue of conventional hot embossing, resulting in improved productivity.
  • A microfluidic chip was fabricated using the IHE setup on polymethyl methacrylate, with micro-features on aluminum-6061 mold made using fiber laser machining instead of photolithography.
  • Accurate micropattern replication is vital for HE, with embossing factors affecting replication accuracy.
  • Particle swarm optimization, artificial bee colony (ABC), firefly algorithm (FA), and grey wolf optimization (GWO) were used to optimize IHE process parameters, with firefly algorithm (FA) outperforming the others.
  • The FA converged in four iterations, whereas particle swarm optimization took 12 and ABC 38, achieving a global best of 6.5809 μm.
  • A confirmation test showed optimal operating conditions reducing embossed micro-channel depth variation from 126.758 μm to 7.0327 μm and improving replication accuracy from 19.94% to 95.50%.
  • The predicted and experimental embossed micro-channel depth deviation percentile error is 6.86%.
  • The research has been peer-reviewed and published in the Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering.

Statistics:

  • The embossing temperature affects micro-channel depth by 79.78%.
  • The experimental data was gathered via L-27 orthogonal array.
  • Linear regression was used to connect process parameters and response variables.
  • Firefly algorithm (FA) achieved a global best of 6.5809 μm in four iterations.
  • Particle swarm optimization took 12 iterations to achieve the global best, while ABC took 38 iterations.
  • The predicted and experimental embossed micro-channel depth deviation percentile error is 6.86%.
  • The embossed micro-channel depth variation was reduced from 126.758 μm to 7.0327 μm.
  • The replication accuracy improved from 19.94% to 95.50%.

Sources:

  • Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering
  • National Institute of Technology, Dept. of Mechanical Engineering, Durgapur 713209, West Bengal, India
  • Science Engineering Research Board (SERB), India
  • Sage Publications Ltd, 1 Olivers Yard, 55 City Road, London EC1Y 1SP, England
  • Experimental Investigation of Replication Accuracy of Polymer-based Microfluidic Chip Fabricated Through Induction-assisted Hot Embossing and Parametric Optimization Through Nature-inspired Algorithms. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 2025;239(3):1217-1233.

Read more