Polymers play a vital role in our daily lives and we continuously encounter polymers that are specifically designed and optimised for optimal performance. They are present in various aspects of our lives, such as clothing, computer displays, and medical technologies. However, in order to maintain a sustainable and healthy society, we need advanced solutions that offer higher performance and new capability that are affordable. They could also pave the way for innovative materials that open doors to new medicines, advanced lubricants, organic photovoltaics, and lithium battery matrix technologies. Living anionic polymerisation is a highly precise chemical synthesis technique that can be used to make these polymers, allowing for an array of molecular architectures. However, there is a lack of efficient methods to quickly screen polymers synthesised using this technique. Currently, it is only carried out in specialised laboratories equipped with the necessary infrastructure and skilled personnel to meet the rigorous experimental conditions. Due to this, scientists will make only one or two batches of material per week meaning rapid prototyping is impossible. Here, we will develop a platform technology which facilitates synthesis of polymers by LAP using an automated reactor platform which can maintain precise conditions with minimal human input. By equipping this instrumentation with machine learning capability, we will demonstrate an ability to rapidly screen polymers and demonstrate the ability to scale-up whilst maintaining the precision required. This technology will precipitate an array of opportunities for developing new sustainable materials which can contribute to solving challenges facing society.

This project aims to tackle major industrial challenges, which limit the full uptake of microencapsulation technology in a broad range of areas including paints and coatings, home and personal care, agrochemicals and lubricants to name but a few. Ideal microcapsules are typically core-shell structures, of sizes in the range of micrometres, capable of retaining valuable active ingredients such as pharmaceutical drugs or fragrance oils within their core and releasing them in a controlled manner at a location and rate that is predetermined. In order to design efficient microcapsule systems, it is critical that the properties of both microcapsule core and their protective shell are well controlled and fully optimised for their specific application. This includes for example delivery of enzymes in washing powders, of pesticides for agro-chemicals, of flavours in foods, of biocides in paints/coatings and of antioxidants in cosmetics. Currently, most commercial microcapsules are spherical structures with a shell made from synthetic or bio-sourced polymers. These designs suffer from significant drawbacks, including: a) microcapsule shell porosity is often too high and does not allow for efficient retention of the active ingredients before the intended delivery - this is a significant challenge in medical applications to minimise the side effects from leaching drugs; b) microcapsule deposition and retention on the targeted surface is often too low - this leads to a very large proportion of microcapsules containing perfume oils being washed down the drain in a washing machine cycle, thus potentially causing both water contamination and higher doses needed (i.e. increased product cost); c) polymer shells are often made from synthetic non-recyclable and non-biodegradable materials, which cause environmental pollution when they unintentionally accumulate, a major current environmental safety concern currently being increasing regulated; and d) microcapsules are mostly manufactured from precursor objects in the form of emulsion droplets, which are typically produced using very energy-intensive and wasteful processes. Addressing the important challenges above is key if the large potential of microencapsulation technology is to be harnessed a) for more targeted and more efficient delivery (including the use of much lower dosages and the drastic reduction in side effects) of pesticides in agricultural fields, potent drugs in treating serious diseases for example and b) for developing new solutions in a wide variety of industries, for example via designing new energy storage devices for more efficient home insulation. On this basis, our project will combine the strength of three of the most active UK academic groups and strongly committed key industrial partners to develop solutions to these challenges, including: - Developing a low energy manufacturing process to produce the emulsion droplet precursors to microcapsules; - Designing and testing a range of alternative microcapsule shell inorganic chemistries (i.e. not organic polymers) that improve properties of current systems, including: - More robust and less permeable shells to decrease shell permeability and thus also reduce potential for undesired leaching (and side effects) of the encapsulated active ingredients; - More sustainable and biodegradable shells that do not linger in the locations they accumulate; Producing microcapsules of non-spherical shapes to improve their deposition and retention on the targeted surfaces (through increased surface area of interaction with the surfaces), thus enabling more efficient use and lower dosages of active ingredients to be achieved. The project will fund 3 post-doctoral researchers working on the various aspects discussed above via EPSRC and a combination of the academic institutions and the industrial partners will provide additional funding for 2 PhD students also working on parts of the overall project.

The internal combustion engine will remain dominant across high power marine, distributed power generation and off-road vehicles for several decades to come, requiring intensified fundamental research around greener fuels and clean, high efficiency operating modes. The UK has an internationally leading reputation for excellence in fundamental engine research for lighter duty cars, vans and trucks, with clear opportunities now apparent to transfer fundamental knowledge and skills to large engines. At present, the UK academic community is totally lacking large single cylinder engine facilities, with researchers restricted to automotive scale experiments and simulations extrapolated up to larger scale (with significant errors in fundamental predictions). This is a major omission in accelerating Net Zero fuels, disruptive large engine technologies and policies from within the UK. The vision is therefore to establish a world-leading, megawatt scale decarbonised engine experimental facility, with two unique research engines strategically co-located as a new collaborative centre of excellence and nationally accessible asset leveraging existing infrastructure and expertise.

Developing and improving our R&D and manufacturing capabilities to prepare greater numbers of higher quality crystalline materials has become a growing societal and hence industrial need. This requires higher levels of precision and speed throughout the R&D development cycle to meet the evolving needs for precision crystals in fine chemical's sector such as for pharmaceuticals, agrochemicals and additives. For example, a more differentiated product range is expected to be produced with a significantly faster molecule to patient journey, in much smaller volumes and at significantly lower costs. For pharmaceuticals, this will provide a wider range of more targeted medicines and dosage forms, ensuring the delivery of patient-targeted dosage forms with much improved safety and efficacy, hence enormously benefiting economy, environment and society. Such an increase in the multiplicity of crystalline products demands the implementation of digitally-enabled and AI technologies as highlighted in UK government policy and global initiatives. The surface properties of crystals are very important for the digital design and manufacture of precision particles via solution crystallisation. Control of the surfaces expressed on crystalline particles represents a critical objective for the fine chemical industry which manufactures ca. 70% of their ingredients in solid (crystalline) form. These crystals have their unique shapes and surface chemistry which, when variable, can impact adversely upon product quality and performance. Specifically, the effective digital design of such products and the associated processes for their manufacture demands a detailed knowledge of surface properties of the product's formulation ingredients. Currently there exists a critical gap to relate the measurable properties at the molecular and single crystal levels to the behaviour and performance of the same material when it is manufactured or used in particulate form. This perspective demands the development of a digitally-enabled platform which is able to characterise, monitor and control crystal size and shape. However, existing crystal shape descriptors available with current commercial particle measurement systems have limited capabilities and the corresponding algorithms tend, unrealistically, to be based upon the assumption that non-spherical crystals can be treated as spherical ones. Therefore, the development of advanced process-inspired analytical tools, particularly of AI-based approach, combining with first-principle, shape-based models are clearly needed. Such approaches are important in order to ensure that the UK's research-led fine chemical and pharmaceutical industry continues to provide outstanding international leadership in product development and manufacture so maintaining and enhancing its global competitiveness. The proposed research will apply machine learning based upon crystal morphology prediction (forward engineering) to map from 2D in-process microscopy data back to a description of a crystal's 3D shape (reverse engineering) and, through this, to its functional surface properties. This will enable the design and control of more efficient and agile manufacturing processes for crystalline fine chemicals, delivering precision crystals with a much tighter specification in terms of their size and shape than is currently feasible, hence resulting in products having more consistency, less variability, higher quality. The outcomes will be a digital platform of crystal shape characterisation and process dynamics control for precision particle manufacture. The approach developed will be shared through academic collaboration (such as the CMAC Hub, INFORM2020, Cambridge Crystallographic Data Centre, Imperial College etc.) and with industry (Infineum, Keyence, Pfizer, Roche, Syngenta etc.) and also extended in due course more widely, expecting potentially enormous economic and societal impact.

This proposal seeks EPSRC Follow-On grant funding to fund the technical and commercial development and integration of molecular modelling software (HABIT and SYSTSEARCH) developed by the crystallisation science and engineering research group at the University of Leeds which enables the prediction of the crystal shape and related surface chemistry of pharmaceutical, fine chemical and energy solid phase products and their mediation by their crystallisation environment. The predictive approach developed draws down on the modelled material's crystallographic structure together with the application of appropriate empirical inter-atomic/molecular force-field parameters through which the structure's key inter-molecular interactions (supra-molecular synthons) for both host (homo-synthons) and growth environment (hetero-synthons related to e.g. solvent, additives and impurities) can be identified, characterised regarding their strength and directivity and related to the product's physical and chemical properties. The work has been developed through a previous EPSRC senior fellowship programme and a number or associated EPSRC research grants. Commercialisation is envisaged through re-engineering the software based on user requirements, afforded through the data-bases and software of the Cambridge Crystallographic Data Centre (CCDC) and, through this, providing a significant enhancement of the predictive resources available to both academic and industrial research groups. The commercially robust software package, HABIT2011, will be offered through CCDC and directly to end user customers. The Synthonic Engineering identity will be established as an internal project, initially internally incubated within the University and later established as a spin off company. Synthonic Engineering will support the continuing technical and scientific development/enhancement of the HABIT2011 software; facilitate product licensing opportunities for other potential users; and provide consultancy, know-how and contract research support to the commercial sector. The utility of the modelling will be embedded within 4 key representative end-user companies: pharmaceuticals (Pfizer), agrochemicals (Syngenta), fuels (Infineum) and nuclear processing (National Nuclear Laboratory) through applications demonstrators on commercial compounds and at least one scientific instrument company (Malvern Instruments). These companies will also provide membership for a steering board to ensure the project's currency to the industrial sector.