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Integration of Computation and Experiment for Accelerated Materials Discovery

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:
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
项目状态:
已结题
起止时间:
2015 至 --

项目摘要

项目成果

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中文摘要
翻译
社会面临着重大挑战,需要颠覆性的新材料解决方案。例如,全世界都需要可持续能源应用的材料,例如更安全的新电池技术或有效地捕获和利用太阳能。该项目将开发一种综合的方法来设计、合成和评估新的功能材料,这些材料将跨越有机和无机固体,以及在单一固体中包含有机和无机模块的混合材料。通过发现突破性的功能材料,英国在促进知识经济方面处于有利地位,但全球范围内的完成度很高。成功和长期的竞争力,在很大程度上取决于提高制造此类材料的能力。所有技术先进的国家都有应对这一挑战的计划,例如美国材料基因组计划的1亿美元初始资金。构建功能材料的传统方法,其特性源于原子的位置,可以与大规模工程形成对比。在工程领域,牛顿物理学的基础被理解为复杂的结构,如桥梁,可以以毫米级的精度建造。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不太完美的理解,并且在合成中实现原子水平精度的能力仍然有限。因此,与大规模工程相比,新材料合成的失败率是巨大的,这需要大量的研究人员来推动成功,与大国相比,英国处于竞争劣势。目前材料设计在原子层面上的困难也导致了文化障碍:在建造一座桥梁时,设计团队将在整个过程中与工程施工团队密切合作。相比之下,尽管在处理更复杂系统的计算能力方面取得了令人印象深刻的进步,但直接、日常地将理论和合成结合起来识别新材料的做法并不常见。这是材料研究中的一个基本挑战。该项目资助将通过提供日常工作水平的计算和实验集成来解决挑战,以发现新材料,由结构和性能预测,测量和材料合成方面的专家团队密切互动。实现这一目标的关键是我们团队开发的独特方法,这些方法最近在《科学》和《自然》上发表了具有里程碑意义的文章。因此,我们在国际上处于有利地位,能够及时实现这一愿景。我们的方法可以在更短的时间内发现功能材料。它将具有广泛的范围,因为我们将在具有一系列目标属性的材料类型中开发它。它将产生破坏性的影响,因为它将化学知识和实验与直接利用化学知识的计算结合起来。从长远来看,这种方法将使化学、物理和工程领域的广泛学术和工业界能够设计出更好的材料,这些领域通常对应用所需的特性有更敏锐的理解。这种方法将产生新的材料,如电池电解质、信息存储材料和太阳能转换的光催化剂,这些材料本身就是重要的社会和商业目标。我们将通过材料化学知识中心和新材料创新工厂(英国投资6800万英镑,为学术和工业用户提供最先进的材料研究设施),开发发现并与我们的商业合作伙伴分享方法。工业界和大学承担了项目成本的55%。
英文摘要
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.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1002/anie.202007571
发表时间: 2020-09-14
期刊: Angewandte Chemie (International ed. in English)
影响因子: --
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
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]
通讯作者: Catherine M. Aitchison;Christopher M. Kane;D. McMahon;Peter R. Spackman;A. Pulido;Xiaoyan Wang;L. Wilbr
DOI: 10.1002/chem.201805028
发表时间: 2018-12
期刊: Chemistry
影响因子: --
作者: [H. D. Arkawazi;Rob Clowes;A. Cooper;T. Konno;Naoto Kuwamura;C. Pask;M. Hardie]
通讯作者: H. D. Arkawazi;Rob Clowes;A. Cooper;T. Konno;Naoto Kuwamura;C. Pask;M. Hardie
DOI: 10.26434/chemrxiv-2022-8vr18
发表时间: 2022
期刊:
影响因子: --
作者: [Bai Y]
通讯作者: Bai Y
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