An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

> 0.85 was achieved, with mean absolute errors <15 MPa for both yield and ultimate tensile strength. A cloud-based graphical user interface was developed to facilitate user interaction, allowing researchers to input steel processing and composition to receive predictive insights on mechanical properties. The findings demonstrate the framework to support circular economy principles by reducing trial-and-error experimentation, with a view to accelerating the design of steels, and promoting sustainable steel innovation.