Materials Acceleration Platforms (MAPs) are emerging as a new paradigm for accelerating materials discovery by integrating automated experimentation, advanced characterization, computation, FAIR data management and artificial intelligence within closed-loop workflows. This session, among the first in Italy specifically dedicated to MAPs, is co-organized with CRIOSS4CET, the initiative consolidating the iENTRANCE@ENL Research Infrastructure and supporting the evolution of platforms toward interconnected and data-driven research environments. The contributions span complementary levels of this vision: laboratory automation and reproducible high-throughput workflows for perovskite and organic photovoltaics; AI-driven surrogate models, graph neural networks and Bayesian optimization for materials property prediction and experiment planning; interoperable digital infrastructures, FAIR data, provenance and federated services enabling distributed MAPs to communicate and learn from shared datasets.
The session will conclude with an open discussion on autonomy, interoperability, standards, and the future integration of MAPs within national and European research ecosystems.