Computer learning technique will help design novel materials

16 September 2015 Neural networks and machine learning help to identify mixed-metal catalysts for useful reactions A new method for identifying metallic catalysts for specific chemical conversions could help materials scientists and chemists design new materials with useful properties, predict the method’s inventors at Virginia Tech. The researchers, led by chemical engineers Luke Achenie and Hongliang Xin, used neural networks and machine learning techniques to ‘teach’ a computer system to study the interactions between important chemical groups on the surfaces of different metals to determine which alloys would be the best at catalysing the desired reactions. Catalysis occurs when compoiunds are adsorbed onto the surface of a material which can donate electrons Previously, catalyst identification has been a trial-and-error process which, although it has led to the discovery of polymers…

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