A Smart Step Towards Intelligent Microfabrication


In microfluidic device fabrication, soft lithography unquestionably stands as the gold standard. Its robust nature offers dependable results with superior resolution and feature fidelity.  But this is not a “one shoe fits all” scenario as soft-lithography requires the use of clean room and advanced materials which is not available in all institutions even in the developed countries. Even when researchers possess access to state-of-the-art facilities, the design iteration for micro-devices proves challenging due to substantial overhead device costs. This methodology, primarily tailored for large-scale manufacturing, poses a barrier to advancements in the field that require considerable design iterations. The sizable initial investment often makes it challenging to achieve a break-even point. Such implications have posed hurdles for research groups and industries across various sectors, spurring the development of rapid prototyping methods. Several praiseworthy efforts have surfaced, targeting the creation of more accessible and cost-efficient microfluidic device fabrication methods.

The vision of this work is to facilitate rapid prototyping of microfluidic devices without compromising the feature fidelity while providing a more than acceptable feature resolution. Several factors have been considered while generalizing the approach for microfluidic device fabrication platform. For example, the resolution of the patterns, minimum allowable feature gap, feature complexity, continuous feature printing, scalability of the device, and control over the uniformity. Additionally, efforts have been made to reduce human interference as much as possible. This led us to develop the first version of Image-Guided In-situ Maskless Lithography (IGIs-ML). This uses several tools to ensure reliable rapid prototyping of microfluidic devices by in-situ UV polymerization. The first is a feature tracking algorithm during UV polymerization. The concept combines the feedback from the high-speed camera and real-time image processing to track and control each pattern independently. This not only ensures superior repeatability, but also opens a new avenue for closed-loop control during the printing process which has been demonstrated in this proof of concept study. Machine vision based intelligent manufacturing are becoming increasingly popular in manufacturing and we believe the proposed concept could hold the key to introduce intelligent control in micro-fabrication.

On top of that, careful analysis of the proximity effect during UV polymerization helped us tailor a simple solution to increase feature fidelity for fine features that outperform most microfluidic rapid-prototyping methods. Not only does it work for discrete patterns, but we have also demonstrated its application for continuous patterning for large-scale microfluidic devices with different resolutions. Ideally, the user will only require drawing the device design in CAD software and load the blank device containing the inlets and outlets onto the platform and the fabrication will be done automatically.

While we acknowledge that this is the first generation of our platform with certain limitations, there are more possibilities than barriers. We envisage a future where such generalized methodology can be extended beyond microfluidic device fabrication and find applications in VAT polymerization or 3D printing, given proper implementation.

The inception of our method was to enhance the design iteration of DLD devices used in cell separation. However, it did not take long for us to realize the enormous potential of this method when generalized for a broader range of microfabrication applications. The progression of the method to its final form was a carefully orchestrated process, ensuring its adaptability to a broad user base. This project, by its very nature, was unorthodox and demanded the concerted effort of the entire team. Every team member rose to the challenge, contribute their expertise and dedication. In the labyrinthine journey of our research, the collective resilience and unyielding spirit of our team transformed an ambitious concept into a promising reality.

Our story goes beyond just the successful execution of a research project. It is a testament of the power of innovative thinking, collaboration, and relentless pursuit of knowledge, all of which have the potential to revolutionize the field of microfabrication and beyond.

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Biological Techniques
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