Machine Learning‐Driven Grayscale Digital Light Processing for Mechanically Robust 3D‐Printed Gradient Materials (Adv. Mater. 42/2025)

Machine Learning-Driven Grayscale Digital Light Processing In their Research Article (DOI: 10.1002/adma.202504075), Jisoo Nam, Boxin Chen, and Miso Kim combine machine learning-driven optimization with grayscale digital light processing to create 3D-printed gradient materials with tailored mechanical properties. Pixel-level light control enables seamless stiffness modulation, improving stress distribution, toughness, and fatigue life. The cover image illustrates the translation of digital design data into architected gradients for durable, high-performance impact absorbers and protective structures.