Support for the UKCP consortium

现代生活中的许多技术进步都依赖于新材料的开发，或者对现有材料更好的控制和理解。因此，了解材料的详细特性从未像现在这样重要。近年来，高质量计算机模拟技术的发展在这方面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加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。在英国国家超级计算机（ARCHER）上提供计算资源的首选机制是通过大型研究联盟，本提案资助UKCP联盟。这是一个庞大而成熟的联盟，包含22个不同的节点和160多名活跃的研究人员。每个节点是一个不同的大学院系，并由一个关键学者代表-参见“链接提案”或跟踪记录，以获得UKCP当前成员的完整列表。该提案寻求对大量研究的计算支持（见“其他支持”），其中包括ARCHER资源的大量分配以及名为研究软件工程师（RSE）的支持。RSE将协助培训和支持联盟的不同成员使用联盟中使用的主要代码（例如CASTEP），并开发完成其中一些项目所需的一些新代码功能。作为这项提议的一部分，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（要么通过提高计算的准确性和可靠性，要么通过使我们能够长时间模拟更大的系统）。新的算法包括机器学习，通过精确的量子力学计算产生新的模型势能，用于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，包括磁性结构、振动、中子散射和介子衰变。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。本提案所描述的研究将对未来技术的许多领域产生重大影响，如半导体纳米结构、蛋白质药物优化、超高温陶瓷、纳米级器件、混合钙钛矿和太阳能电池、无机纳米管和金属-空气电池阳极。还有一些基础研究领域，旨在推动我们对物质基本性质的理解，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。拟议的研究不容易归入任何传统的“物理”或“化学”等范畴。相反，UKCP是一个多学科联盟，使用共同的理论基础来推进材料科学的许多不同领域，这些领域在短期和长期都有可能产生重大影响。

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.