The development of computational chemistry approach to predict the viscosity of lubricants
The development of computational chemistry approach to predict the viscosity of lubricants
复制标题
预测润滑剂粘度的计算化学方法的发展
DOI：
10.1016/s0301-679x(02)00234-7
复制
发表时间：
2003
影响因子：
6.2
通讯作者：
A. Miyamoto
中科院分区：
文献类型：
--
作者：
K. Konno;D. Kamei;T. Yokosuka;S. Takami;M. Kubo;A. Miyamoto
精密机械要求开发新的润滑剂，实现无摩擦接触、完美传递扭矩等。然而，实验方法需要很长时间才能找到新的润滑剂。因此，用计算化学方法预测润滑剂的性质对于加快润滑剂的设计是至关重要的。本研究采用基于神经网络的分子动力学模拟与预测方法，对粘度进行了精确的评价。
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.