Support for the UKCP consortium

支持 UKCP 联盟

基本信息

批准号：
EP/P022561/1
负责人：
Matthew Probert
金额：
$ 66.15万
依托单位：
University of York
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FP022561%2F1
关键词：
Support UKCP consortium

项目摘要

Many technological advances in modern day life are dependent upon the development of new materials, or better control and understanding of existing materials. Understanding the detailed properties of materials has therefore never been more important. The development of high quality computer simulation techniques has played an increasingly significant role in this endeavour over recent years. The UK has been at the forefront of this new wave, and the UKCP consortium has played an important part, in both developing computer codes and algorithms, and exploiting these new advances to increase our understanding of many industrially relevant materials and processes.The preferred mechanism for providing computational resources on the UK national supercomputer (ARCHER) is via large research consortia, and this proposal funds the UKCP consortium. This is a large and established consortium, containing 22 different nodes and over 160 active researchers. Each node is a different University Department and is represented by one key academic - see the "Linked Proposals" or the Track Record for a complete list of current members of UKCP. This proposal seeks computational support for a large body of research (see "Other Support") with a substantial allocation of ARCHER resources and also the support of a named Research Software Engineer (RSE). The RSE will assist with training and supporting different members of the consortium in using the principle codes used within the consortium (e.g. CASTEP), and also develop some of the new code features required to complete some of these projects.As part of this proposal, the researchers will have to develop new algorithms and also make theoretical improvements that will increase our simulation abilities (either by increasing the accuracy and reliability of calculations, or by enabling us to simulate bigger systems for longer). New algorithms include machine learning to generate new model potentials derived from accurate quantum mechanical calculations for fast calculations of large systems, improved structure optimisation, and uncertainty quantification. New functionality includes new spectroscopies, including magnetic structure, vibrations, neutron scattering and muon decay. Together, these innovations will enable the next generation of simulations and further widen our computational horizons.The research described in this proposal will make significant impacts on many areas of future technology, such as semiconductor nanostructures, protein-drug optimization, ultra-high temperature ceramics, nanoscale devices, hybrid perovskites and solar cells and inorganic nanotubes and metal-air battery anodes.There are also areas of fundamental research, designed to push our understanding of basic properties of matter, such as interfacial water, nanocrystal growth, structure of grain boundaries, pigment-protein complexes, radiation damage in DNA and high-pressure hydrogen phases.The research proposed does not easily fit into any of the traditional categories of 'physics' or 'chemistry' etc. Instead, the UKCP is a multi-disciplinary consortium using a common theoretical foundation to advance many different areas of materials-based science which has the potential for significant impact both in the short and long-term.

现代生活中的许多技术进步都依赖于新材料的开发，或对现有材料更好的控制和理解。因此，了解材料的详细特性变得前所未有的重要。近年来，高质量计算机模拟技术的发展在这一努力中发挥了越来越重要的作用。英国一直处于这一新浪潮的前沿，UKCP 联盟在开发计算机代码和算法以及利用这些新进展来增进我们对许多工业相关材料和工艺的理解方面发挥了重要作用。首选机制在英国国家超级计算机 (ARCHER) 上提供计算资源是通过大型研究联盟进行的，该提案为 UKCP 联盟提供资金。这是一个大型且成熟的联盟，包含 22 个不同的节点和 160 多名活跃的研究人员。每个节点都是一个不同的大学系，并由一位关键学者代表 - 请参阅“链接提案”或跟踪记录，了解 UKCP 现有成员的完整列表。该提案寻求为大量研究提供计算支持（请参阅“其他支持”），并分配大量 ARCHER 资源以及指定研究软件工程师 (RSE) 的支持。 RSE 将协助培训和支持联盟的不同成员使用联盟内使用的主要代码（例如 CASTEP），并开发完成其中一些项目所需的一些新代码功能。作为该提案的一部分，研究人员必须开发新的算法，并进行理论改进，以提高我们的模拟能力（通过提高计算的准确性和可靠性，或者使我们能够更长时间地模拟更大的系统）。新算法包括机器学习，通过精确的量子力学计算生成新的模型势，以实现大型系统的快速计算、改进的结构优化和不确定性量化。新功能包括新的光谱学，包括磁结构、振动、中子散射和μ子衰变。总之，这些创新将使下一代模拟成为可能，并进一步拓宽我们的计算视野。本提案中描述的研究将对未来技术的许多领域产生重大影响，例如半导体纳米结构、蛋白质药物优化、超高温陶瓷、纳米器件、混合钙钛矿和太阳能电池以及无机纳米管和金属-空气电池阳极。还有基础研究领域，旨在推动我们对物质基本性质的理解，例如界面水、纳米晶体生长、晶界结构、色素-蛋白质复合物、DNA 辐射损伤和高压氢相。所提出的研究不容易归入“物理”或“化学”等任何传统类别。相反，UKCP 是一个多学科联盟利用共同的理论基础来推进基于材料的科学的许多不同领域，这在短期和长期都有可能产生重大影响。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Two-state model for critical points and the negative slope of the melting curve

临界点和熔化曲线负斜率的二态模型

DOI：
http://dx.10.1103/physrevb.104.054120
发表时间：
2021
期刊：
Physical Review B
影响因子：
3.7
作者：
Ackland G
通讯作者：
Ackland G

OPTIMADE, an API for exchanging materials data

OPTIMADE，用于交换材料数据的 API

DOI：
10.1038/s41597-021-00974-z
发表时间：
2021-03-02
期刊：
Scientific Data
影响因子：
9.8
作者：
C. Andersen;R. Armiento;Evgeny Blokhin;G. Conduit;S. Dwaraknath;Matthew L. Evans;'. Fekete;Abhijith M. Gopakumar;Saulius Gravzulis;Andrius Merkys;Fawzi Mohamed;C. Oses;G. Pizzi;G. Rignanese;M. Scheidgen;Leopold Talirz;C. Toher;Donny Winston;R. Aversa;K. Choudhary;Pauline Colinet;S. Curtarolo;Davide Di Stefano;C. Draxl;S. Er;M. Esters;M. Fornari;M. Giantomassi;M. Govoni;G. Hautier;V. Hegde;Matthew K. Horton;P. Huck;G. Huhs;J. Hummelshøj;A. Kariryaa;B. Kozinsky;Snehal Kumbhar;Mohan Liu;N. Marzari;A. J. Morris;A. Mostofi;K. Persson;G. Petretto;Thomas A. R. Purcell;F. Ricci;F. Rose;M. Scheffler;Daniel T. Speckhard;M. Uhrin;A. Vaitkus;P. Villars;D. Waroquiers;C. Wolverton;Michael Wu;Xiaoyu Yang
通讯作者：
Xiaoyu Yang

Correlation between spin transport signal and Heusler/semiconductor interface quality in lateral spin-valve devices

横向自旋阀器件中自旋输运信号与 Heusler/半导体界面质量之间的相关性