AI-Powered Optimization of Direct Air Capture Technologies for Carbon Dioxide Removal

This research focuses on applying advanced AI techniques, including Bayesian optimization and deep learning, to optimize the design and operational parameters of direct air capture (DAC) technologies. Our findings significantly enhance the efficiency and cost-effectiveness of carbon dioxide removal efforts, contributing to climate change mitigation.