Unlocking CO₂ conversion potential with single atom catalysts and machine learning in energy application

SACs are transforming CO₂ conversion and energy applications due to their high catalytic efficiency, unique electronic structures, and maximal atom utilization. They have shown great promise in CO₂ electroreduction, hydrogenation, and dry reforming, yet challenges remain in their synthesis, stability, and scalable production. This review explores advances in SAC design, support interactions, and electronic tuning to enhance catalytic performance. It also analyzed state-of-the-art characterization techniques used to probe SAC structures and reaction mechanisms. Machine learning is emerging as a powerful tool for predicting SAC stability and optimizing reaction pathways. By examining recent breakthroughs and existing limitations, this work provides insights into the future of SACs in energy applications and CO₂ utilization, highlighting their role in sustainable chemical transformations and carbon-neutral technologies.