Machine learning algorithm makes impossible screening of advanced materials possible
Monday, September 15, 2014 - 08:31
in Physics & Chemistry
(Phys.org) —A fundamental part of climate change response is expected to involve the discovery of advanced materials capable of cost-effectively capturing CO2 from burning fossil fuels. One particular class of materials, called metal-organic frameworks (MOFs), have tremendous potential to revolutionize CO2 capture technologies. For example, MOFs have record-breaking high surface areas, so that one gram of solid can have two football fields of internal surface area to adsorb and later release CO2.