Quantum mechanics has had a profound and pervasive influence on science and technology. Phenomena that are intrinsically quantum mechanical, such as magnetism, electron transport in semiconductors, and the effect of impurity atoms in materials, lie at the heart of almost every branch of industry. Quantum mechanical calculations of properties and processes from ``first-principles'' are capable of making accurate quantitative predictions but require solving the Schrdinger equation which is extremely difficult and can only be done using powerful computers. In contrast, empirical modelling approaches are relatively cheap but lack the predictive power of first-principles methods (which are parameter-free and take as input only the atomic numbers of the constituent atoms). The predictive capability is essential, in order to make rapid progress on new and challenging problems where there is insufficient experimental data and to also generate useful empirical approaches or even to check their reliability when these exist. Within the class of first-principles methods, one approach that has been outstandingly successful is the Density Functional Theory (DFT) as it combines high accuracy with moderate computational cost. Nevertheless, the computational effort of performing calculations with conventional DFT approaches increases as the cube of the number of atoms, making them unable to tackle problems with more than a few hundred atoms even on modern supercomputers. Since the pioneering work of the Nobel laureate Walter Kohn, it has been known that it is possible to reformulate DFT so that it scales linearly, which would in principle allow calculations with many thousands or even millions of atoms. The practical realisation of this however, in a method which is as robust and accurate as conventional cubic-scaling DFT approaches has been extremely difficult. The ONETEP approach developed over many years by the applicants of this proposal has achieved just that. ONETEP is at the cutting edge of developments in first principles calculations. However, while the fundamental difficulties of performing accurate first-principles calculations with linear-scaling cost have been solved, only a small core of functionality is currently available in ONETEP which prevents its wide application. In this collaborative project between three Universities, the original developers of ONETEP will lead an ambitious workplan whereby the functionality of the code will be rapidly and significantly enriched. The code development ethic of ONETEP, namely that software is robust, user-friendly, modular, portable and highly efficient on current and future HPC technologies will be of fundamental importance and will be further strengthened by rigorous cross-checking between the three institutions of this proposal. The developments are also challenging from a theoretical point of view as they need to be within the linear-scaling framework of ONETEP, using its highly non-trivial formulation of DFT in terms of in situ optimised localised functions. The program of work provides much added value as the few fundamental enabling technologies that will be developed in its first stages will then underpin many of the functional capabilities that will follow. The result will be a tool capable of a whole new level of materials simulation at the nanoscale with unprecedented accuracy. It will find immediate application in simulations in molecular biology, nanostructures and materials, which underpin solutions in urgent current problems such as energy, environment and health. Through the increasing number of commercial and academic users and developers of ONETEP, the worldwide dissemination and wide use of this novel tool will be rapid; finally the expanding ONETEP Developers' Group will coordinate the best strategies for the future maintenance and development of the software.

Wherever advanced materials are required for technology theory and simulation have a vital role to play. That role may be in making a safety case, or reducing costs by narrowing down the selection of materials, or predicting and preventing failures. It may also be to establish whether and how materials may be designed to meet engineering specifications, or to interpret experimental characterizations of materials over a range of length and time scales.The need for this DTC cannot be overstated: there are no longer PhD graduates produced anywhere in the UK with a foundation knowledge of theoretical and computational materials physics. Current PhD graduates in theory and simulation of materials (TSM), with a first degree in a subject other than materials science, know extremely little about materials physics beyond the topic of their own research. On the other hand very few students with a first degree in materials science have sufficient training in mathematical techniques to engage in TSM at any level beyond the use of standard simulation packages. The need for breadth in the training of PhD graduates in TSM stems directly from the multi-scale and multi-physics nature of the vast majority of challenging problems in materials technology. The need exists both in industrial and academic research. The education and training provided by the DTC will be unique in the UK. For the first time in decades students will be taught theoretical materials physics at a sophisticated mathematical level, which will enable them to model the principal classes of materials across the length and time scales. They will also learn about the principal techniques of simulating materials at different length and time scales, and how information is transferred up and down the length and time scale hierarchies. The multidisciplinary training and research environment of the DTC, in combination with a wide range of cohort building and student empowerment activities, will provide a far richer educational and professional experience than a standard PhD funded through the DTA. The scientific network students will be able to form through the DTC with their peers, academics, industrialists and leading visiting scientists will be a lasting benefit for them.The DTC will bring together key staff of 4 departments across 2 faculties at Imperial College. Students will have 2 supervisors, whose expertise will not be centred at the same length scale. This will usually mean that their supervisors are in different departments. Similarly, no single department has the expertise to provide the range of courses that students will receive in their first year. For these reasons the multidisciplinary training and research environment can be delivered only through a DTC. Conversely, if the DTC is not funded then narrowly focused PhDs in TSM will continue to be generated with the same limited usefulness for industry, academe and the students themselves as they have in the past 2-3 decades.With nuclear power once again a key component of the Government strategy for energy there will be a significant demand from this sector for graduates of the DTC, as confirmed by the letter of support from UKAEA. Other forms of producing energy such as wind and solar power will also benefit. But TSM is needed in all advanced materials technologies, including aerospace and land-based transportation, building and construction, the processing, storage and communication of information, sport, prostheses and health-care, sensors and security, defence and more. The need from academic groups in the UK and overseas is also very significant. Indeed the absence of suitably trained PhD graduates is universally recognised in the attached letters of support from academics, national labs and industry, as one of their principal concerns. Judging by these letters the 50 graduates of the DTC funded by EPSRC are likely to be in very strong demand.

Quantum mechanical simulations from first principles are today used hand in hand with experiments to guide the design of new materials or biomolecules as they provide a very accurate description of the electrons that determine all the observable properties of the materials. With the advent of first principles quantum methods where the computational effort increases linearly with the number of atoms we have the capability to simulate complex materials at the forefront of research such as nanostructures (e.g. in fuel cell catalysts or electronic devices) and entire biomolecules (as needed in drug design or studies of components of the living cell). The UK-developed ONETEP program is the leading linear-scaling first principles quantum code, due to its new generation of theory that retains the full level of accuracy of conventional cubic-scaling first principles quantum methods. ONETEP has a wide and growing international user base not just within academia, but within industry (via the commercial version of the code distributed by BIOVIA). The code was developed from the beginning using modern software engineering principles with the aim of portability and high scalability to modern supercomputing platforms and user-friendly interactive input and output. The present project aims to develop in ONETEP the capabilities for a whole new level of simulation. It will expand the regime of applicability of the code from the ground state to excited states; it will provide much more accurate approximations for the electrons (hybrid and range-separated exchange correlation functionals) and finally it will dispense with the monolithic single-theory description of the entire system by allowing to seamlessly combine different levels of theory that match the different parts of complex materials systems. A multitude of grand-challenge problems will become accessible to accurate simulation with these developments: examples include light energy harvesting in biomolecules such as chlorophyl, new materials for flexible and cheap organic photovoltaics, new types of lasers/masers. In all these problems there are different levels of complexity as the photoactive site and its environment are clearly distinct, thus the multilevel description will be indispensable. This project is the flagship project of the CCP9 materials simulation community and has received overwhelming support with several members of the CCP9 consortium offering to be early adopters of our developments. The ONETEP code will become freely available to all UK academics (via free membership of CCP9, which is open to the whole UK academic community) and as a result it is expected to be accessible to all the materials, chemistry and biomolecular simulation communities. We will further promote the dissemination of the code via a dedicated masterclass (open to both academic and industrial users), and a European CECAM/Psi-k workshop. The new developments will also be disseminated to industry through their exposure within the BIOVIA Materials Studio graphical user interface via which the ONETEP code is marketed to industrial customers.

The search for new medicinal entities within the pharmaceutical industry is a critical problem. Early stage lead identification and optimization often exploits knowledge of the interaction between a putative drug, and a target enzyme or other macromolecular system. Consequently in recent years there has been exponential growth in the number of protein structures (e.g. 53 thousand structures in the RCSB Protein Data Bank) and similar growth has been observed with proprietary structure data in the pharmaceutical industry. In parallel to the growth of available structure data, significant research effort has been directed towards understanding the possible interactions of small molecules and the protein structures. Most commonly this has been through empirical docking schemes whose main focus has been to provide fast identification of an approximate binding pose. Speed is important because of the enormous size of the compound collections that need to be virtually 'screened'. These schemes provide a very reasonable estimation of the binding pose; however they almost universally fail when used to estimate differences in binding affinity. This failure is due to the approximations made in their construction. Specifically, even when physical interactions between protein and ligands are considered in an atomistic way, they are described by classical potentials, so molecules are represented as balls (atoms) connected with springs (bonds). In general this precludes the inclusion of any form of polarization of ligand or protein, or electronic charge transfer between the moieties. To get an accurate representation of such interactions one needs to use a full Quantum Mechanical (QM) representation of the system. Application of QM methods from 'first principles' to systems as large as protein-ligand complexes has until recently been beyond the scope of any available methods, due to prohibitive computational cost which scales asymptotically as ~N^3 or worse, where N is the number of atoms. Even on supercomputers, these methods are limited to no more than a few hundred atoms while most proteins of interest contain thousands of atoms. Recently the ONETEP first principles method has been developed where the computational cost scales only as ~N (linear-scaling) and is capable of calculations with thousands of atoms. The ONETEP method was originally developed and validated in the context of Materials Science simulations. The main focus of the proposed research would be application of ONETEP to a number of biological systems. The work will answer several questions such as: the ability of the method to correctly predict the relative binding affinity of series of potential drugs and the analysis of binding mechanism through visual and numerical processing of the electronic structure (density, molecular orbitals) of the complex in a full QM framework. Reliable modelling of mechanisms such as charge transfer are key to correct understanding of interactions for example in the heme group in CYP p450 enzymes - which play a central role in human metabolism. Calculations on the CYP p450s, and any other metal-containing systems, cannot be accurately performed without some consideration of the full QM effects. Previous efforts included QM/MM approaches, where a small portion of the biomolecule is treated in a QM fashion and the rest is described with classical potentials. A major concern of these approaches is the quality of the coupling between the classical and quantum regions as well as the size of the quantum region (usually too small, for computational reasons). ONETEP will therefore also provide absolute benchmarks for QM/MM approaches by treating quantum mechanically the entire biomolecule. The current proposal would provide vital validation of the linear-scaling first principles QM methodology in biomolecular simulations, which is critical before any widespread adoption of the methods within the pharmaceutical industry.

Quantum mechanics has had a profound and pervasive influence on science and technology. Phenomena that are intrinsically quantum mechanical, such as magnetism, electron transport in semiconductors, and the effect of impurity atoms in materials, lie at the heart of almost every branch of industry. Quantum mechanical calculations of properties and processes from ``first-principles'' are capable of making accurate quantitative predictions but require solving the Schrdinger equation which is extremely difficult and can only be done using powerful computers. In contrast, empirical modelling approaches are relatively cheap but lack the predictive power of first-principles methods (which are parameter-free and take as input only the atomic numbers of the constituent atoms). The predictive capability is essential, in order to make rapid progress on new and challenging problems where there is insufficient experimental data and to also generate useful empirical approaches or even to check their reliability when these exist. Within the class of first-principles methods, one approach that has been outstandingly successful is the Density Functional Theory (DFT) as it combines high accuracy with moderate computational cost. Nevertheless, the computational effort of performing calculations with conventional DFT approaches increases as the cube of the number of atoms, making them unable to tackle problems with more than a few hundred atoms even on modern supercomputers. Since the pioneering work of the Nobel laureate Walter Kohn, it has been known that it is possible to reformulate DFT so that it scales linearly, which would in principle allow calculations with many thousands or even millions of atoms. The practical realisation of this however, in a method which is as robust and accurate as conventional cubic-scaling DFT approaches has been extremely difficult. The ONETEP approach developed over many years by the applicants of this proposal has achieved just that. ONETEP is at the cutting edge of developments in first principles calculations. However, while the fundamental difficulties of performing accurate first-principles calculations with linear-scaling cost have been solved, only a small core of functionality is currently available in ONETEP which prevents its wide application. In this collaborative project between three Universities, the original developers of ONETEP will lead an ambitious workplan whereby the functionality of the code will be rapidly and significantly enriched. The code development ethic of ONETEP, namely that software is robust, user-friendly, modular, portable and highly efficient on current and future HPC technologies will be of fundamental importance and will be further strengthened by rigorous cross-checking between the three institutions of this proposal. The developments are also challenging from a theoretical point of view as they need to be within the linear-scaling framework of ONETEP, using its highly non-trivial formulation of DFT in terms of in situ optimised localised functions. The program of work provides much added value as the few fundamental enabling technologies that will be developed in its first stages will then underpin many of the functional capabilities that will follow. The result will be a tool capable of a whole new level of materials simulation at the nanoscale with unprecedented accuracy. It will find immediate application in simulations in molecular biology, nanostructures and materials, which underpin solutions in urgent current problems such as energy, environment and health. Through the increasing number of commercial and academic users and developers of ONETEP, the worldwide dissemination and wide use of this novel tool will be rapid; finally the expanding ONETEP Developers' Group will coordinate the best strategies for the future maintenance and development of the software.