Differentiable Frameworks (D1.2)

Project D1.2 establishes automatic differentiability as a standard feature in our scientific software. By enabling gradient-based computations across all tools, we aim to accelerate optimization, improve predictive accuracy, and create new pathways for designing 3D-nanoprinted functional materials and devices. By embedding automatic differentiation into scientific software, we will create a unified, versatile platform for simulation and design. This will lead to faster development cycles, improved alignment between theory and experiment, and transformative advances in photonics, biomaterials, and beyond.