Integration of Computation and Experiment for Accelerated Materials Discovery

计算与实验相结合，加速材料发现

• 批准号: EP/N004884/1
• 负责人: Matthew Rosseinsky
• 金额: $ 847.42万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FN004884%2F1
• 关键词: Integration; Computation; Experiment; Accelerated; Materials

Society faces major challenges that require disruptive new materials solutions. For example, there is a worldwide demand for materials for sustainable energy applications, such as safer new battery technologies or the efficient capture and utilization of solar energy. This project will develop an integrated approach to designing, synthesizing and evaluating new functional materials, which will be developed across organic and inorganic solids, and also hybrids that contain both organic and inorganic modules in a single solid.The UK is well placed to boost its knowledge economy by discovering breakthrough functional materials, but there is intense global completion. Success, and long-term competitiveness, is critically dependent on developing improved capability to create such materials. All technologically advanced nations have programmes that address this challenge, exemplified by the $100 million of initial funding for the US Materials Genome Initiative.The traditional approach to building functional materials, where the properties arise from the placement of the atoms, can be contrasted with large-scale engineering. In engineering, the underpinning Newtonian physics is understood to the point that complex structures, such as bridges, can be constructed with millimetre precision. By contrast, the engineering of functional materials relies on a much less perfect understanding of the relationship between structure and function at the atomic level, and a still limited capability to achieve atomic level precision in synthesis. Hence, the failure rate in new materials synthesis is enormous compared with large-scale engineering, and this requires large numbers of researchers to drive success, placing the UK at a competitive disadvantage compared to larger countries. The current difficulty of materials design at the atomic level also leads to cultural barriers: in building a bridge, the design team would work closely with the engineering construction team throughout the process. By contrast, the direct, day-to-day integration of theory and synthesis to identify new materials is not common practice, despite impressive advances in the ability of computation to tackle more complex systems. This is a fundamental challenge in materials research.This Programme Grant will tackle the challenge by delivering the daily working-level integration of computation and experiment to discover new materials, driven by a closely interacting team of specialists in structure and property prediction, measurement and materials synthesis. Key to this will be unique methods developed by our team that led to recent landmark publications in Science and Nature. We are therefore internationally well placed to deliver this timely vision.Our approach will enable discovery of functional materials on a much faster timescale. It will have broad scope, because we will develop it across materials types with a range of targeted properties. It will have disruptive impact because it uses chemical understanding and experiment in tandem with calculations that directly exploit chemical knowledge. In the longer term, the approach will enable a wide range of academic and industrial communities in chemistry and also in physics and engineering, where there is often a keener understanding of the properties required for applications, to design better materials. This approach will lead to new materials, such as battery electrolytes, materials for information storage, and photocatalysts for solar energy conversion, that are important societal and commercial targets in their own right.We will exploit discoveries and share the approach with our commercial partners via the Knowledge Centre for Materials Chemistry and the new Materials Innovation Factory, a £68 million UK capital investment in state-of-the-art materials research facilities for both academic and industrial users. Industry and the Universities commit 55% of the project cost.

社会面临需要破坏性新材料解决方案的主要挑战。例如，全世界对可持续能源应用的材料有需求，例如安全的新电池技术或有效的太阳能捕获和利用。该项目将开发一种综合方法来设计，合成和评估新的功能材料，这些功能材料将在有机和无机固体之间开发，并在单个固体中包含有机和无机模块的混合动力。成功和长期竞争力在关键上取决于开发创建此类材料的改进能力。所有技术先进的国家都有解决这一挑战的计划，以美国材料基因组倡议的1亿美元初始资金为例。建造功能材料的传统方法可以与大型工程形成对比。在工程学中，基础牛顿物理学被理解为可以用毫米精度构建复杂的结构（例如桥梁）。相比之下，功能材料的工程依赖于对原子水平上结构和功能之间关系的完美理解，并且在合成中达到原子水平精度仍然有限​​。因此，与大型工程相比，新材料合成的失败率提高了，这需要大量的研究人员取得成功，使英国陷入竞争性灾难中，与较大的国家相比。当前原子层的材料设计难度也导致了文化障碍：在建造桥梁时，设计团队将在整个过程中与工程施工团队紧密合作。相比之下，理论与综合识别新材料的直接，日常整合不是常见的实践，而是目的地计算能力解决更复杂系统的能力的令人印象深刻的进步。这是材料研究中的一个基本挑战。该计划的赠款将通过提供计算和实验的日常工作级别的整合来解决挑战，以发现新材料，这是由在结构和财产预测，测量和材料合成方面紧密相互作用的专家团队驱动的。关键的将是我们的团队开发的独特方法，该方法导致了科学和自然的最新地标出版物。因此，我们在国际上有很好的位置来实现这种及时的愿景。我们的方法将在更快的时间范围内发现功能材料。它将具有广泛的范围，因为我们将跨具有一系列目标特性的材料类型开发它。它会产生破坏性的影响，因为它使用化学理解和实验与直接探索化学知识的计算同时实验。从长远来看，该方法将使化学和物理和工程领域的广泛学术和工业社区能够在其中经常了解应用程序所需的属性来设计更好的材料。这种方法将导致新材料，例如电池电解质，用于信息存储的材料以及用于太阳能转化的光催化剂，它们本身就是重要的社会和商业目标。我们将通过知识中心的材料化学和新的材料创新工厂和6,800万英镑的材料来源的工具来利用发现并与我们的商业合作伙伴通过知识中心与我们的商业合作伙伴共享该方法。行业和大学承担了项目成本的55％。

项目成果

Inducing Social Self-Sorting in Organic Cages To Tune The Shape of The Internal Cavity.

• DOI: 10.1002/anie.202007571
• 发表时间: 2020-09-14
• 期刊: Angewandte Chemie (International ed. in English)
• 作者: Abet V;Szczypiński FT;Little MA;Santolini V;Jones CD;Evans R;Wilson C;Wu X;Thorne MF;Bennison MJ;Cui P;Cooper AI;Jelfs KE;Slater AG
• 通讯作者: Slater AG

Photocatalytic overall water splitting under visible light enabled by a particulate conjugated polymer loaded with iridium

由负载铱的颗粒共轭聚合物实现可见光下光催化整体水分解

• DOI: 10.26434/chemrxiv-2022-8vr18
• 发表时间: 2022
• 作者: Bai Y

Complex Phase Behaviour and Structural Transformations of Metal-Organic Frameworks with Mixed Rigid and Flexible Bridging Ligands.

• DOI: 10.1002/chem.201805028
• 发表时间: 2018-12
• 期刊: Chemistry
• 作者: H. D. Arkawazi;Rob Clowes;A. Cooper;T. Konno;Naoto Kuwamura;C. Pask;M. Hardie

Photocatalytic proton reduction by a computationally identified, molecular hydrogen-bonded framework

• DOI: 10.26434/chemrxiv.11341850.v1
• 发表时间: 2019-12
• 期刊: Journal of Materials Chemistry A
• 影响因子: 11.9
• 作者: Catherine M. Aitchison;Christopher M. Kane;D. McMahon;Peter R. Spackman;A. Pulido;Xiaoyan Wang;L. Wilbr

Inducing Social Self-Sorting in Organic Cages To Tune The Shape of The Internal Cavity

• DOI: 10.1002/ange.202007571
• 发表时间: 2020-01-01
• 期刊: Angew. Chem.
• 作者: Abet, V.;Szczypinski, F. T.;Slater, A. G.
• 通讯作者: Slater, A. G.