UC San Diego

Functional microdevices such as micro-robotics, tissue engineering scaffolds, and lab-on-a-chip are finding promising application across many industries, such as energy, environment, medicine, defense, and consumer products, due to their high performance and miniaturized size. These devices often have complex 3D geometry across multiple length scales to achieve their functionalities, and their performance is strongly dependent on the accuracy and precision of these features.

Microscale 3D printing is an emerging free-form additive manufacturing technique for fabricating functional microdevices. Among various types of 3D printing methods, photopolymerization-based 3D printing is the most promising technique, because of its fine resolution, fast speed, and ability to fabricate structures with high quality.

Despite numerous instances of successful fabrication of functional microdevices using photopolymerization-based 3D printing, this technique still faces many challenges to produce micro-architectures in high fidelity and high resolution. It is important to study and refine our ability to manipulate light-matter interactions in the photopolymerization process during printing.

One significant challenge in fabricating microdevices using photopolymerization-based 3D printing is that the functional materials used in their construction can be light scattering, thus deteriorating final fabrication fidelity and resolution. In this dissertation, two methods are developed to overcome this issue: one method uses flashing photopolymerization approach to avoid the effect of light scattering, and the other method uses a machine learning approach to compensate for the effect of light scattering.

Furthermore, photopolymerization-based 3D printing technique has an issue of anisotropic resolution, where the axial resolution can be much worse than the lateral resolution due to the nature of light’s propagation. To address this, a projection printing method using patterned evanescent fields was developed. This approach could be a promising solution to improving the axial resolution.