New Knowledge and Tools for Topological Characterisation of the CSD Subset of Metal-Organic Frameworks (MOFs)

金属有机框架 (MOF) CSD 子集拓扑表征的新知识和工具

基本信息

批准号：
2483281
负责人：
金额：
--
依托单位：
University of Sheffield
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-2483281
关键词：
New Knowledge Tools Topological Characterisation

项目摘要

With unparalleled potential to investigate thousands of structures in a short time, computational high-throughput screening (HTS) is extremely well-suited to unravel trends in key metal-organic framework's (MOF) properties, establish structure-property relationships and guide future synthetic efforts. In the last three years, the computational analysis of structures in the CSD MOF subset has been focused on the characterization of geometric (e.g. largest pore size, pore volume, surface area) and gas adsorption properties. Clearly, previous computational work has delivered important insights, but it has not yet fully characterised properties such as the local environment of organic/inorganic clusters and the underlying topology of the identified MOFs in the CSD MOF subset. this PhD studentship focuses on synergetic combination of expertise and disciplines from the CCDC scientists in crystallography, materials science and software development, and the Sheffield team's know-how in database generation, porous materials characterisation, and molecular-level simulations. Included in this goal is the development of tools to characterise MOFs and predict structure-function relationships to accelerate materials discovery.This is a multidisciplinary project and the successful candidate will benefit from an extensive peer-group of researchers at the CCDC in Cambridge and the University of Sheffield, as well as acquiring skills at the interface between, materials science, chemistry and big data science, that are in high demand in both industry and academia.

由于无与伦比的潜力在短时间内研究了数千种结构，因此计算高通量筛选（HTS）非常适合揭示关键金属有机框架（MOF）特性（MOF）的趋势，并建立结构 - 实质关系并指导未来的合成工作。在过去的三年中，CSD MOF子集中结构的计算分析集中在几何（例如最大的孔径，孔体积，表面积）和气体吸附特性上。显然，以前的计算工作已经提供了重要的见解，但尚未完全表征诸如有机/无机簇的局部环境以及CSD MOF子集中已鉴定的MOF的基本拓扑。该博士学位的学生重点介绍了CCDC科学家在晶体学，材料科学和软件开发方面的专业知识和学科的协同组合，以及谢菲尔德团队在数据库生成，多孔材料表征和分子级模拟中的专业知识。该目标包括开发特征MOF和预测结构功能关系以加速材料发现的工具。这是一个多学科的项目，成功的候选人将受益于剑桥和谢菲尔德大学的CCDC的广泛研究人员，并在材料科学，化学科学和大型DAPAD DATAICA中，在材料科学和材料科学的界面中获得了互动技能，并在互动中获得了互动技能。