Metal alloys production faces escalating environmental, geopolitical, supply chain, and ethical challenges that demand a paradigm shift in alloy design, beyond conventional performance-centric methodologies. Here, we introduce a comprehensive, data-driven alloy design framework for compositionally complex alloys (CCAs) that simultaneously optimises performance criteria alongside economic viability, environmental impact, and societal considerations by combining predictive machine learning (ML) modelling and multi-indicator elemental footprint analysis. Nine ML regression models were evaluated, and the model demonstrating the best predictive accuracy was selected to guide alloy design for higher hardness. The elemental footprint assessment considered nine indicators: raw material price, supply risk, normalised vulnerability to supply restriction, embodied energy, water usage, rock-to-metal ratio, human health damage, human rights pressure, and labour rights pressure. Two CCA compositions predicted through the proposed strategy were synthesised to evaluate the effectiveness of the approach. The characterisation results demonstrated that the down-selected alloy achieved superior hardness (~70% higher than that of reference high-entropy alloys), whilst simultaneously cutting elemental footprint by as much as 42%. This strategy establishes a scalable pathway to sustainable CCAs, offering a model for responsible materials innovation. Conceptually, the work establishes a sustainability-first, tripartite design loop in which elemental footprint screening constrains the design space, ML serves as a surrogate hardness ranking model, and CALPHAD plus targeted experiments provide physics-based and empirical validation of phase constitution and achievable hardness. • Data-driven alloy design strategy integrating performance and sustainability. • Nine ML models tested; best guided compositions with higher hardness. • Elemental footprint analysis covers economic, environmental, and social factors. • Synthesised CCAs achieved ~70% higher hardness than reference alloys. • Elemental footprint reduced by up to 42%, enabling sustainable alloy design.
Sharma et al. (Fri,) studied this question.