Increasingly, scientists are recognizing that negative emissions technologies (NETs) to remove and sequester carbon dioxide from the atmosphere will be an essential component in the strategy to mitigate climate change. Lawrence Berkeley National Laboratory (Berkeley Lab), a multidisciplinary Department of Energy research lab, is pursuing a portfolio of negative emissions technologies and related research.
Tag: MOF
Machine Learning Advances Materials for Separations, Adsorption, and Catalysis
An artificial intelligence technique — machine learning — is helping accelerate the development of highly tunable materials known as metal-organic frameworks (MOFs) that have important applications in chemical separations, adsorption, catalysis, and sensing.