The development of computational chemistry approach to predict the viscosity of lubricants

Sophisticated machinery requires the development of new lubricants that realize friction-less contact, perfect transmittance of torque, and so on. However, experimental approaches have needed long time to find new lubricants. Therefore, the prediction of lubricant properties by computational chemistry should be crucial to accelerate the design of lubricants. This study treats precise evaluation of viscosity employing molecular dynamics simulation and prediction based on neural network.