AI approach enhances efficiency of material multiscale simulation for wearable electronics

The integration of microscale and macroscale simulations has long been a computational challenge in material science. Addressing this, researchers have developed AGAT, a machine learning model that efficiently predicts the behaviors of materials used in wearable electronics, particularly focusing on CNTs/PDMS composites.

challenge computational efficiency electronics electronics & semiconductors integration machine machine learning machine learning model material materials researchers science simulation simulations wearable