Machine Learning Simulations Reveal How Plastic Transforms into Hard Carbon

Researchers at the University of Oxford's Department of Chemistry have employed machine learning simulations to unravel the atomic-scale transformation of common polymers into hard carbon. Published in Chemical Science, the study traces the process that gives hard carbon its disordered structure—a key feature for its use in batteries and other technologies. The simulations provide unprecedented insight into the formation mechanism, potentially enabling better control over the material's properties. This advancement could lead to more efficient production of hard carbon from plastic waste, addressing both energy storage needs and environmental concerns. The work highlights the power of computational methods in materials science.