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Understanding and controlling polymorphism in molecular solids

了解和控制分子固体中的多态性

基本信息

批准号：
2480944
负责人：
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：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2480944
关键词：
Understanding controlling polymorphism molecular solids

项目摘要

the research questions the project is trying to address/the objectives of the project; Understanding and controlling polymorphism, where molecules crystallise into multiple solid forms, is a major unsolved problem in structural chemistry. While some theoretical insight into polymorphism can be obtained by calculating lattice energies, force fields and Density Functional Theory do not readily decompose energies into different types of interaction. This severely limits the insight available from crystal-structure prediction studies that could otherwise point to new predictive rules or "smarter" screening approaches. One objective is to identify the pertinent interactions in polymorphic systems by using a recent energy partitioning method called Interacting Quantum Atoms (IQA). The second objective is to train a machine-learning technique called kriging on these atomic energy contributions to derive an accurate and transferable force field called FFLUX. We will use FFLUX to explore larger problems such as predicting surface termination/reactivity and crystal morphology. The third objective is to incorporate FFLUX into the UKRI-sponsored software package DL_POLY (Daresbury lab), and to prove that the results obtained by FFLUX are indeed closer to experiment than those produced by classical force fields. A fourth objective is to automate these processes by using the Cambridge Structural Database to select molecules and identify the major degrees of freedom for building the force field. Our ultimate aim is to provide a comprehensive database of parameters and software to allow crystal engineers to perform "point and click" force field calculations with DFT levels of accuracy.the approach that will be taken to answer these questions (what the student will actually be doing); This project builds on the results of the EPSRC Fellowship entitled "Reliable computational prediction of molecular assembly". This work has led to a next-generation in-house force field called FFLUX. This force field is much more realistic than a point-charge based force field such as AMBER. FFLUX also introduces multipole moments, which are essential for accurate electrostatics governing a considerable part of the non-covalent interactions between the typically polar molecules that form the crystals. The modern IQA method offers a step change in the rigour of atomistic energy analysis. IQA is a parameter-free method that is intuitive but, at the same time, very close to the quantum mechanical character of atoms themselves. When combined with the in-house Relative Energy Gradient (REG) method IQA returns powerful qualitative statements on which atoms govern the behaviour of the overall system and why (i.e. by which type of energy). The REG method has been developed in the main supervisor's group and comes with an in-house code called REG.py.The student will be programming in FORTRAN90 and Python, modifying the in-house codes ICHOR, DL_FFLUX and REG.py to interface them with the problem of crystal structure prediction. He will run molecular dynamics simulations using FFLUX, for the first time on crystals. The student will be involved with careful and systematic testing and thus gather unprecedented insight. He will fine-tune the parameterisation of FFLUX. Comparisons with classical force fields will also be made.the novel engineering and/or physical sciences content of the research (the science that places it within EPSRC's remit).This project resorts under the Chemical Sciences Grand Challenge of "Directed Assembly of Extended Structures with Targeted Properties (DAESTP)". There is a strong Machine Learning component to this project, and thus overlap with Artificial Intelligence, a popular funding topic. The associated scientific product is called FFLUX, which is a completely new force field, designed by novel principles and encoded as a software package.

该项目试图解决的研究问题/该项目的目标;理解和控制多晶型，即分子结晶成多种固体形式，是结构化学中一个未解决的主要问题。虽然可以通过计算晶格能来获得对多态性的一些理论见解，但力场和密度泛函理论并不容易将能量分解为不同类型的相互作用。这严重限制了晶体结构预测研究的洞察力，否则这些研究可能会指向新的预测规则或“更智能”的筛选方法。一个目标是通过使用最近的能量划分方法称为相互作用量子原子（IQA），以确定多态系统中的相关相互作用。第二个目标是在这些原子能贡献上训练一种称为克里金的机器学习技术，以获得一种称为FFLUX的准确且可转移的力场。我们将使用FFLUX探索更大的问题，如预测表面终止/反应性和晶体形态。第三个目标是将FFLUX纳入UKRI赞助的软件包DL_POLY（达雷斯伯里实验室），并证明FFLUX获得的结果确实比经典力场产生的结果更接近实验。第四个目标是通过使用剑桥结构数据库来选择分子并识别用于构建力场的主要自由度，从而使这些过程自动化。我们的最终目标是提供一个全面的参数数据库和软件，让晶体工程师执行“点和点击”力场计算与DFT的准确性水平。将采取的方法来回答这些问题（学生实际上将做什么）;这个项目建立在EPSRC奖学金的结果题为“可靠的计算预测的分子组装”。这项工作导致了下一代内部力场，称为FFLUX。这种力场比基于点电荷的力场（如琥珀）更真实。FFLUX还引入了多极矩，这对于精确的静电学至关重要，静电学控制了形成晶体的典型极性分子之间相当大一部分的非共价相互作用。现代IQA方法在原子能量分析的严格性方面提供了一个步骤。IQA是一种直观的无参数方法，但同时非常接近原子本身的量子力学特性。当与内部的相对能量梯度（REG）方法相结合时，IQA返回关于哪些原子控制整个系统的行为以及为什么（即通过哪种类型的能量）的强有力的定性陈述。REG方法已经在主要主管的小组中开发，并附带了一个名为REG.py的内部代码。学生将使用FORTRAN 90和Python编程，修改内部代码ICHOR，DL_FFLUX和REG.py，以将其与晶体结构预测问题连接起来。他将使用FFLUX首次在晶体上运行分子动力学模拟。学生将参与仔细和系统的测试，从而收集前所未有的洞察力。他将微调FFLUX的参数化。与经典力场的比较也将进行。研究的新工程和/或物理科学内容（将其置于EPSRC职权范围内的科学）。该项目隶属于化学科学大挑战“具有目标属性的扩展结构的定向组装（DAESTP）"。这个项目有一个强大的机器学习组件，因此与人工智能重叠，这是一个受欢迎的资助主题。相关的科学产品被称为FFLUX，这是一个全新的力场，由新颖的原理设计并编码为软件包。