From Molecular Bricks to Sustainable Nanomaterials: An Accurate and Scalable Unsupervised Workflow

The rational design of sustainable nanomaterials increasingly depends on organic molecular units whose optical, electronic, and catalytic properties stem from minute structural details. Achieving the required level of accuracy—beyond standard density functional theory (DFT)—is crucial to disentangle intrinsic geometrical features from environment‐induced effects in applications such as organocatalysis, organic light‐emitting diodes, and dye‐sensitized solar cells. Here we introduce an adaptive accuracy framework rooted in the Pisa Composite Schemes (PCS), combining rigorous quantum‐mechanical foundations with scalable efficiency. The reference PCS2 protocol, based on explicitly correlated coupled‐cluster (CC‐F12) theory, achieves spectroscopic accuracy for medium‐sized molecules, while the BDPCS3 model extends the reach of PCS methods to much larger systems through double‐hybrid DFT and bond corrections. Together, they form a hierarchical and internally consistent strategy that balances precision and cost across molecular scales. Applications to quinone derivatives, aromatic biomolecules, amino acids, and light‐driven molecular machines demonstrate predictive accuracy and transferability. Seamless integration with the Nano‐LEGO platform further enables automated fragment recognition and reconstruction, paving the way for the data‐driven design of functional molecular materials. Overall, this framework bridges accuracy and scalability, offering a practical route toward predictive modeling and rational design in next‐generation nanoscience.