Towards the Development of Reactive Machine-Learned Potentials for Describing Chemistry in Solution

开发用于描述溶液中化学反应的机器学习潜力

• 批准号: 2638399
• 金额: --
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2638399
• 关键词: Towards; Development; Reactive; Machine; Learned

Year 1: General skills training and lab rotationsYears 2-4: MLPs are an exciting and current field of research. The benefits afforded by their use (particularly their ability to escape the fundamental trade-off between accuracy and computational efficiency) make them ideal for investigating the complex intricacies of liquid-phase reactions. There is now the opportunity to shine the 'computational microscope' on novel reaction phenomena.This project will functions as a proof-of-concept study for applying reactive MLPs to describing chemistry in solution. We will develop an MLP to accurately model the static, dynamical, and reactive properties of an aqueous system of molecules. Our methodology will employs NNPs (specifically, a committee of HD-NNPs), which we will use to provide a flexible and scalable model for simulating over different system types and sizes. We will develop this NNP towards modelling the reaction between CO2 and H2O (a fundamental process in a nature) across a range of conditions, environments, and media. In conducting this initial research, we hope to both gain valuable insight into our system of study while also improving our methodology for extensions to larger and more complex reactive systems. We anticipate that developing these methods will soon manifest a new, generalised framework for simulating reactions in liquids and at interfaces, which will prove important in synthetic chemistry for elucidating new pathways, optimal reaction conditions, and obtaining new insight into the fundamental principles governing reactive events.

第1年：一般技能培训和实验室轮换第2-4年：MLP是一个令人兴奋的和当前的研究领域。它们的使用所带来的好处（特别是它们能够避免准确性和计算效率之间的根本权衡）使它们成为研究液相反应复杂性的理想选择。现在有机会在新的反应现象上闪耀“计算显微镜”。该项目将作为应用反应MLP描述溶液中化学的概念验证研究。我们将开发一个MLP来精确地模拟分子水溶液系统的静态，动态和反应特性。我们的方法将采用NNPs（特别是HD-NNPs委员会），我们将使用它来提供一个灵活和可扩展的模型，用于模拟不同的系统类型和大小。我们将开发这个NNP，以模拟CO2和H2O之间的反应（自然界中的一个基本过程），包括各种条件，环境和介质。在进行这项初步研究时，我们希望既能对我们的研究系统获得有价值的见解，又能改进我们的方法，以扩展到更大、更复杂的反应系统。我们预计，开发这些方法将很快表现出一个新的，通用的框架，用于模拟在液体和界面上的反应，这将证明在合成化学中的重要性，用于阐明新的途径，最佳反应条件，并获得新的见解的基本原则，管理反应事件。