A numerical framework for modeling the Xolography additive manufacturing method

Despite significant advancements in the Xolography technique, a numerical framework to digitally define the process window and optimize parameters for different setups is still lacking. This study addresses this gap by introducing the first numerical model of Xolography, simultaneously solving UV and visible light intensities while computing reaction rates. A governing reaction set is proposed, and a finite difference–based algorithm is implemented to solve the equations. Experimental characterization, numerical modeling, and optimization are combined to determine the unknown parameters. The framework is then applied to study conversion-field variations inside and outside printed regions. Results show that, for a given laser scanning velocity, intensity values closer to the minimum threshold yield more uniform conversion within the part. However, low intensities increase the risk of under-curing along the print direction. To mitigate this, adjustments in the initial laser position and projector illumination time are suggested to improve dimensional fidelity. The study further demonstrates that both under- and over-curing can occur where the cross-section changes within a geometry. Practical adjustments are proposed to reduce these effects. Overall, the proposed numerical framework enables analysis and optimization of the Xolography process across different setups, offering guidelines to improve accuracy and print quality.