3D Printing and Machine Learning

Cycle Life Prediction of Lithium Ion Batteries Based on Data Driven Methods

Expert-guided Learning for Data-constrained Materials Science Problems

Fast and Generalizable Detailed Router Using Attention-based Reinforcement Learning

Introductory Comments: Machine Learning for Discovery of Structure-Process-Property Relations in Electronic Materials

Neural Network Potential for Lattice Dynamics Calculations and Thermal Conductivity Prediction

Parametric Analysis to Quantify Process Input Influence on the Printed Densities of Binder Jetted Alumina Ceramics

SimuLearn: Machine Learning-empowered Fast and Accurate Simulator to Support 4D Printing Design

Uncertainty Quantification and Active Learning of Neural Network Models for Predicting ZrO2 Crystal Energy

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