Prediction model for sintering shrinkage in micro-nano ceramic 3D printing of triply periodic minimal surface structures

Micro-nano ceramic 3D printing technology offers unique advantages in the fields of microfluidic chips and biological scaffolds through layer-by-layer additive manufacturing. However, its sub-micron accuracy requirements make the control of sintering shrinkage particularly critical. In this study, the sintering shrinkage of micro-nano ceramic 3D printing was investigated as the primary research focus. An orthogonal experimental design combined with supplementary experimental points was used to construct a shrinkage prediction model, incorporating the nonlinear response of materials. By introducing higher-order interaction terms and applying regularization regression (LASSO), the model’s fitting accuracy and generalization ability were improved. The experimental results indicate that the prediction model yields a low mean squared error (MSE = 0.2507) and effectively captures the nonlinear effects of printing layer thickness, exposure time, and light source intensity on sintering shrinkage. Furthermore, optimal process control parameters were identified, with a combination of h = 0.01 mm and I = 25200 μW/cm2 ensuring moderate shrinkage (23–24 %). Finally, the model’s reliability and accuracy were validated in practical applications, using it to guide the preparation of ceramic TPMS structures. This study provides new theoretical support and technical pathways for micro-nano scale process control in ceramic additive manufacturing.