Machine Learning Proves Faster Than Quantum Mechanical Calculations in Discovery of New …

Home News Machine Learning Proves Faster Than Quantum Mechanical Calculations in Discovery of New Compounds Michael Feldman | September 22, 2016 01:08 CEST Researchers at the University of Basel in Switzerland have used machine learning to predict the thermodynamic characteristics of 90 new mineral compounds with potential commercial use. The machine learning models were able to predict the chemical stability of all possible iterations of a particular type of class of crystals several orders of magnitude faster than if the researchers had relied on quantum mechanical calculations. The class of compounds in this case was elpasolite, a crystalline material that in nature is made up of four chemical elements: sodium, potassium, aluminum, and fluorine. Some elpasolites emit light when exposed to ionic radiation, which makes them candidates for scintillators, a…


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