Artificial Intelligence Led Selection of Crystal Conformations

人工智能主导晶体构象的选择

• 批准号: 2330961
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2330961
• 关键词: Artificial; Intelligence; Led; Selection; Crystal

The main objective for this project is to apply deep neural network methods to the prediction of crystal conformations. In order to achieve this, new conformational descriptors will be developed and computed in all conformations in the CSD as well as other unobserved conformations generated computationally. A neural network model then will be trained and used for the prediction of crystal conformations. If successful we will then go on to investigate deep reinforcement learning methods to enhance the predictive power of current prediction algorithms.

该项目的主要目标是将深度神经网络方法应用于晶体构象的预测。为了实现这一点，新的构象描述符将开发和计算在CSD中的所有构象以及其他未观察到的构象计算产生。神经网络模型，然后将被训练和用于晶体构象的预测。如果成功，我们将继续研究深度强化学习方法，以提高当前预测算法的预测能力。