Segmentation approach for enhanced DLP bioprinting

Achieving high-resolution outputs in Digital Light Processing (DLP) bioprinting requires precise control over photocrosslinking, particularly for dense, intricate models with fine gaps. Over-crosslinking is affected by factors such as light scattering, limited depth of focus, and molecular diffusion. Traditionally, these issues are managed by altering the material and light source. This study presents a novel segmentation approach designed to address these challenges by leveraging the inherent diffusion characteristics of the DLP system rather than altering its core components. The generation and diffusion of free radicals increase with light intensity and the density of the illuminated area, which alters the risk of over-crosslinking in these regions. The proposed technique involves segmenting the photomask into discrete regions and employing an on-off activation strategy to enhance control over photopolymerization. By strategically segmenting the mask and alternating the activation of adjacent segments, the technique effectively manages the distribution and concentration of free radicals and allows time for the termination phase of photopolymerization. It creates spatial gaps, helps manage free radical diffusion, prevents unwanted combinations, and filling of small gaps, thus improving resolution. Demonstrated by printing a bronchial model, this approach achieved a 100 μm gap between bronchial branches at a 14.43x compression ratio to anatomical size. The live-dead assay shows sustained cell viability of up to 90% for GelMA and up to 85% for GelMA-PEGDA constructs across seven days. This study shows that the segmentation strategy significantly reduces over-crosslinking, advancing DLP bioprinting for applications requiring precise control over complex features and detailed features.