FingerMap: a new approach to predict soft material 3D objects printability

Soft material 3D printing through liquid deposition modelling (LDM) is a challenging manufacturing process where yield stress control is mandatory. Indeed, the higher the yield stress value, the more complex the 3D printed structure can be. In a bid to go one step further, this report proposes a new approach enabling the prediction of soft material 3D printability as a function of the material’s properties and shape. The prediction consists in numerical simulation to anticipate, in silico, the collapse of a voxelised 3D design, called FingerMap. To do so, a calibration of the program using three silicone formulations (with increasing yield stress value) was first performed to define a printability domain according to mass/surface ratio, overhang angle and the z-position of each voxel. Then, two anatomical 3D models (ear and aortic valve) were used to demonstrate the capacity of the tool to predict printability. Good correlations between theoretical and experimental results were obtained. The proposed in silico simulation tool was then proven to be useful for LDM, even if some limitations were identified, particularly in the case of materials exhibiting complex rheological behaviours such as time-dependent rheological properties.