Our Hub research is driven by the societal need to produce medicines and materials for modern living through novel manufacturing processes. The enormous value of the industries manufacturing these high value products is estimated to generate £50 billion p.a. in the UK economy. To ensure international competitiveness for this huge UK industry we must urgently create new approaches for the rapid design of these systems, controlling how molecules self-assemble into small crystals, in order to best formulate and deliver these for patient and customer. We must also develop the engineering tools, process operations and control methods to manufacture these products in a resource-efficient way, while delivering the highest quality materials. Changing the way in which these materials are made, from what is called "batch" crystallisation (using large volume tanks) to "continuous" crystallisation (a more dynamic, "flowing" process), gives many advantages, including smaller facilities, more efficient use of expensive ingredients such as solvents, reducing energy requirements, capital investment, working capital, minimising risk and variation and, crucially, improving control over the quality and performance of the particles making them more suitable for formulation into final products. The vision is to quickly and reliably design a process to manufacture a given material into the ideal particle using an efficient continuous process, and ensure its effective delivery to the consumer. This will bring precision medicines and other highly customisable projects to market more quickly. An exemplar is the hubs exciting innovation partnership with Cancer Research UK. Our research will develop robust design procedures for rapid development of new particulate products and innovative processes, integrate crystallisation and formulation to eliminate processing steps and develop reconfiguration strategies for flexible production. This will accelerate innovation towards redistributed manufacturing, more personalisation of products, and manufacturing closer to the patient/customer. We will develop a modular MicroFactory for integrated particle engineering, coupled with a fully integrated, computer-modelling approach to guide the design of processes and materials at molecule, particle and formulation levels. This will help optimise what we call the patient-centric supply chain and provide customisable products. We will make greater use of targeted experimental design, prediction and advanced computer simulation of new formulated materials, to control and optimise the processes to manufacture them. Our talented team of scientists will use the outstanding capabilities in the award winning £34m CMAC National Facility at Strathclyde and across our 6 leading university spokes (Bath, Cambridge, Imperial, Leeds, Loughborough, Sheffield). This builds on existing foundations independently recognised by global industry as 'exemplary collaboration between industry, academia and government which represents the future of pharmaceutical manufacturing and supply chain R&D framework'. Our vision will be translated from research into industry through partnership and co-investment of £31m. This includes 10 of world's largest pharmaceutical companies (eg AstraZeneca, GSK), chemicals and food companies (Syngenta, Croda, Mars) and 19 key technology companies (Siemens, 15 SMEs) Together, with innovation spokes eg Catapult (CPI) we aim to provide the UK with the most advanced, integrated capabilities to deliver continuous manufacture, leading to better materials, better value, more sustainable and flexible processes and better health and well-being for the people of the UK and worldwide. CMAC will create future competitive advantage for the UK in medicines manufacturing and chemicals sector and is strongly supported by industry / government bodies, positioning the UK as the investment location choice for future investments in research and manufacturing.

Granular materials are almost ubiquitous in our daily lives and include soil particles, pharmaceuticals in solid dosage forms, tea, coffee and powdered food ingredients, e.g., flour, bran, salt, sugar or condensed milk. Researchers investigating granular materials often use computer simulations to study their behaviour in detail. One such software tool, discrete element modelling (DEM), has become extremely popular in the last 20 years due to its power and flexibility and its popularity continues to grow year-on-year. DEM is based on a time-stepping algorithm: some calculations are performed, then time is incremented by a tiny time-step before the calculations are repeated. The size of this time-step determines how quickly the simulation may be run; it is therefore advantageous to choose the largest possible time-step. However, there is a limiting value - the 'critical' time-step - beyond which the simulation becomes unstable and the results become invalid. Unfortunately, the methods used to estimate the critical time-step at present are crude and different approaches can lead to greatly differing estimates. The lack of an accurate method to estimate critical time-steps for non-trivial simulations means that large factors of safety are required. This is why small and unnecessarily conservative time-steps are often adopted which causes simulations to run slowly. The overall aim of this project is to improve upon existing approaches for estimating critical time-steps for DEM simulations. This overarching aim can be divided into four objectives. Firstly, bounds will be calculated on the critical time-step for the simplest possible DEM simulation with only two idealised particles. Once this objective has been fully met, objectives two and three involve extending this analysis to systems of many particles and including complications in the basic discrete element model. These objectives will be achieved using a well-established approach for analysing the stability of nonlinear dynamical systems. The final objective is to critically evaluate the current methods for estimating critical time-steps by comparison with the findings of this study. This study has many potential benefits. Being able to estimate critical time-steps more accurately will allow the factors of safety applied to simulation time-step to be reduced. This has potentially huge implications for efficiency: simulation durations could be reduced from days to several hours. It will also become feasible to run larger, more ambitious simulations than was formerly the case. For example, a researcher who is barely able to run a simulation containing 100,000 particles might be able to increase the number of particles five-fold, without a commensurate increase in the duration of their simulation, by simply choosing a less conservative time-step. As the results of this study will be published openly and disseminated widely, this research will also be useful for increasing the efficiency of other related multi-body simulation codes. Furthermore, there are obvious environmental benefits as DEM simulations at all scales may be run in less time if the time-step can be increased without compromising the stability of the simulation.