Scaling laws articles from across Nature Portfolio

In 2018 a descriptor was put forward to correlate the activity of various electrocatalytic reactions on carbon-based single-atom catalysts, but some data the work was based on were later found to be incorrect. This work revisits and amends the original 2018 study while presenting a modified version of the φ descriptor.

A protocol using large-scale training of graph networks enables high-throughput discovery of novel stable structures and led to the identification of 2.2 million crystal structures, of which 381,000 are newly discovered stable materials.

The mechanical response of polymer films is affected by size effects under nanoconfinement, but the mechanism of such response in terms of molecular configurations and chain conformations has proven elusive. The authors reveal the conformational origin of the stiffening behavior in crosslinked polymeric nanofilms via simulations and experiments.

Big data is crucial for machine learning, but the redundancies in the datasets are rarely studied. Here the authors reveal significant redundancy in large materials datasets, showing that up to 95% of data can be removed without impacting prediction accuracy.