Smart Systems Engineering Contributing to the Life Cycle of Material Discovery and a Net-Zero Future

Facing the pressing environmental and climate change challenges, novel approaches are needed for sustainable development towards a carbon-neutral future. The emergence of big data analytics, internet of things, machine learning (ML), and general artificial intelligence (AI) provide enormous smart tools for processing complex data and information generated from experimental and computational research, as well as industrial applications, which could revolutionize next-generation research, industry and society. The potential contribution of ML combined with big data to energy and environmental is worth of investigation. Our recent developments of ML models and data-driven optimization will be demonstrated via a series of use cases, e.g. machine vision and AI automated molecular imaging, active learning guided low-carbon sensor development and applied ML for prediction of CO₂ capture and utilization. The design, operation and management of multi-scale systems with enhanced economic and environmental performance are then presented. Materials innovation plays a key role in a net-zero emission future. Finally, opportunities, challenges, and future directions of smart materials, energy and environment management faced by the pressing sustainable development and carbon-neutrality targets are discussed.