Fig. 1: Overview of the presented work.
From: Inverse design of stochastic, voxelated thermo-viscoelastic digital materials
From left to right: (1) efficient material representation leveraging homogenization; (2) a material model for stochastic digital materials of two polymer base materials is developed using a temperature and frequency-dependent de Gennes37 percolation theory; (3) an ANN is trained on the material model to estimate the material mixture ratio given required stiffness, time scale and temperature (images provided from left to right by lovemask/stock.adobe.com, haji/stock.adobe.com, and Ralf’s icons/stock.adobe.com); (4) the validity of the proposed modeling approaches is shown by applying them to a personalized wrist orthosis and a machine damper. Source data are provided as a Source Data file.
