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Researchers at U of T, Northwestern Use AI to Accelerate Discovery of Industrial Materials
Researchers at the University of Toronto and Northwestern University are using machine learning to craft the best materials for different industrial uses.
The findings, published this week in Nature Machine Intelligence, demonstrated that the use of AI can help propose novel materials for diverse applications, helping to speed up the design cycle for materials. One example is the separation of carbon dioxide from industrial combustion processes.
With the objective of improving the separation of chemicals in industrial processes, the team of researchers including collaborators from Harvard University and the University of Ottawa, set out to identify the best reticular frameworks – for example, metal organic frameworks and covalent organic frameworks – for use in the process. Such frameworks, which can be thoug ....

Randall Snurr , Johng Searle , Zhenpeng Yao , Canadian Network For Research , Innovation In Machining Technology , Engineering Research Council Of Canada , Natural Sciences , University Of Ottawa , Us Department Of Energy , University Of Toronto , Harvard University , Mccormick School Of Engineering At Northwestern University , Office Of Science , Vector Institute For Artificial Intelligence , Northwestern University , Nature Machine Intelligence , Theoretical Chemistry , Vector Institute , Mccormick School , Canadian Network , Machining Technology , Engineering Research Council , கனடியன் வலைப்பின்னல் க்கு ஆராய்ச்சி , கண்டுபிடிப்பு இல் எந்திரம் தொழில்நுட்பம் , பொறியியல் ஆராய்ச்சி சபை ஆஃப் கனடா , இயற்கை அறிவியல் ,