Many technological advances in modern-day life depend upon the development of new materials, or better control and understanding of existing materials. The chemical, mechanical and physical properties of materials depend on their constituent atoms and, in particular, their electrons. CASTEP is a state-of-the-art software package which uses quantum mechanics to predict the behaviour of those electrons and, hence, the material, and it is widely used by scientists in academia and industry. Many of these researchers are experimental scientists, rather than computational specialists, and the main aim of this proposal is to support them to use CASTEP more easily, efficiently and reliably, and to expand the user community by lowering the barrier of entry for new users. The work focuses on preparing CASTEP for the future, by improving its Usability, Sustainability, Efficiency and Reliability (USER) so any researcher can run it quickly, consistently and easily on any computer, from laptops to HPC facilities. The key challenges this proposal addresses are to: * enhance accessibility for non-specialist scientists * exploit future methods and technologies * take full advantage of available computing resources * further improve reliability, and be fully validated This far-reaching programme will improve the whole CASTEP user experience, including: re-imagining CASTEP's interface (focusing on scientific output, not algorithmic details) and creating comprehensive examples and tutorials; developing a deep API for embedding CASTEP in high-level workflows; automating CASTEP's parallel decomposition; and improving fault-tolerance. The work will be in collaboration with consortia (e.g. MCC, UKCP, CCP-NC, CCP9) and national experimental facilities (e.g. SuperSTEM), as well as industry partners (e.g. NVIDIA and BIOVIA). The ultimate, overarching goal is that CASTEP itself becomes 'invisible'; a hidden software infrastructure for providing quick, clear answers to research questions, whose correctness and successful operation may be taken for granted. The research described in this proposal will make significant impacts on many areas of academic and industrial research, particularly in materials for future technology. CASTEP is already used by well over 1000 academic groups and industrial research sites across the globe, including Johnson Matthey, Sony, Solvay, PG Corp, Pfizer, Astra Zeneca and Toyota, and supports research in a vast range of materials such as semiconductor nanostructures, ultra-high temperature ceramics, nanoscale devices, fluorophores, thermoelectrics, hybrid perovskites and solar cells, inorganic nanotubes and metal-air battery anodes. This work will promote CASTEP use across a diverse range of STEM disciplines, increase the effectiveness and impact of a wide variety of research initiatives, and enable researchers to directly address 5 of EPSRC's Grand Challenges in Physics, Engineering and Chemical Science.

Molecular modelling has established itself as a powerful predictive tool for a large range of materials and phenomena whose intrinsic multiscale nature requires modelling tools able to capture their chemical, morphological and structural complexity. In the UK, the molecular modelling community, supported by the software, training and networking activities coordinated by the CCP5, has become, over the past 40 years, international-leading in this field. Building upon these successes, the new CCP5++ network will revolutionise the field of materials molecular modelling creating a new integrated community of modellers, experimentalists and data scientists that together will identify the new frontiers of the field and will transform the way these disciplines work together. To achieve its mission, the CCP5++ will coordinate and support an ambitious plan of meetings, sandpits, coding workshops, secondments and visitor schemes to cater for the large community of modellers, experimentalists and data scientists working on advanced materials. This support has proved to be vital to enable the UK condensed matter community to attain and maintain an international position at the forefront of such an intensely competitive field and will enable the UK researchers to identify and tackle major world challenges in-silico materials discovery. From the start the network memberships include key representatives of the experimental and data science communities, international software and modelling institutes, industrial collaborators and national HPC consortia and CCPs, that working together will shape the future of materials molecular modelling.

Many modern technological advances are dependent upon either the development of new materials, or better control and understanding of existing materials. As materials' properties depend on their constituent nuclei and electrons, accurate modelling of their electronic structure is crucial. In principle, this should be straightforward, as the fundamental quantum mechanical equations governing their behaviour have been known for almost 100 years; however, solving these equations is extraordinarily hard. The key advance has been the development of high quality computer simulation methods for many-electron systems able to describe realistic materials, and the UK has been at the forefront of this new field since the very start. The UKCP HEC, focused on density functional theory methods, has played a fundamental part in this effort via both developing theories, software and algorithms, and exploiting these innovative tools in use cases relevant to a range of disciplines and industries. UKCP also supports experimental communities, via computational training, RSE time and computer allocations on Tier-1 and Tier-2 HPC. The close interaction between DFT theorists, software developers and users drives innovation and expands simulation capabilities, as well as magnifying the impact of the work. The research proposed does not easily fit traditional categories of "physics", "chemistry" etc; instead, UKCP is a multidisciplinary consortium using a common theoretical foundation to advance many areas of materials-based science, with the potential for significant impact both in the short and long-term. UKCP currently comprises 24 different nodes in physics, chemistry, materials science & engineering, with over 150 active researchers. Each node is a different University Department, represented by one key academic (a Co-I on the grant). This proposal provides computational support for a large body of research across UKCP (over £40M in already-awarded grants) with a substantial allocation of ARCHER2 and Tier-2 HPC resources plus Research Software Engineer (RSE) support. The RSE provides essential expert coding support for the principal UKCP codes (CASTEP, CONQUEST & ONETEP), develops new code features as required for some UKCP projects, and assists with training and supporting the UKCP codes' user-communities. The innovations in this proposal enable the next generation of simulations and further widen our computational horizons. UKCP will develop new algorithms, workflows & theoretical methods to increase our simulation abilities, in terms of both new functionality and dramatically improved accuracy & speed. New algorithms include embedding machine learning methods into DFT to speed up calculations, and enabling treatment of large systems (bringing together the CASTEP & ONETEP codes into a single workflow and enabling DFT codes to be embedded in multiscale, multiphysics simulations). GPU ports and improved parallelism enable UKCP software to exploit current and future HPC architectures effectively & with greater energy efficiency. New functionality includes NMR spectroscopy with spin-orbit coupling, so the full periodic table can be studied with high accuracy, and advances in excited state modelling, including temperature and environmental effects. These developments enable larger, more complex systems to be studied and will make significant impacts on many areas of future technology, including LED lighting, improved wear/corrosion resistance, next generation batteries, low power electronics & spintronics, improved energy-harvesting (thermoelectric) materials, new materials for carbon capture/storage and nanoparticles for water purification. There are also areas of fundamental research, to further our understanding of basic properties of matter, such as dynamics at molecule/metal interfaces, electron interactions in solid/liquid interfaces, quantum effects in biological processes, protein-ligand binding & high-pressure hydrogen phases