Enabling high throughput molecular dynamics with automation and machine learning for development of advanced engineering polymers

Computational modelling is of increasing importance to materials science and engineering. Modelling has clear advantages over laboratory work: it is infinitely repeatable, generates a wealth of useable data, doesn't produce waste material, and is considerably cheaper in terms of both cost, and time investment. However, current modelling simulations are limited to the length scale (e.g. macroscale or atomistic) for which they were designed, which ultimately limits their application scope. This work aims to develop a methodology that enables bridging between scales to produce a true multiscale modelling experiment. This novel advancement would enable the production of high accuracy models for complex structures. These models would facilitate rapid prototyping and reduce reliance on physical testing. Furthermore, an additional objective of this work will be to expand the modelling potential of composite structures, particularly in low length scale simulations, and incorporate this into the multiscale model methodology.

This work will model atomistic chemical structures of polymers, nanomaterials and carbon fibre by using molecular dynamics (MD). MD is well suited to modelling the curing process of polymer structures and how they interact with other materials such as at the surface of carbon fibre. The final structure and material properties determined by MD will then be fed into mesoscale models, raising the scale from nanometre to micrometre. These models will reveal how a polymer matrix and carbon fibre act in a single composite ply and can be used to explain the mechanical properties of a material. Finally, the results of the mesoscale model will be used to produce a high-quality finite element (FE) model. FE analysis is able to demonstrate how large, tangible structures, such as beams, panels or trusses, respond to external loads. Using material originally modelled in MD allows for detailed material properties in the FE model, enhancing the accuracy of the model and identifying materials that have potential to cater to a given task. This whole process can be repeated with different starting materials to refine the final properties of structure being modelled.

Application of this work is broad as any development of modelling technology not only enhances inorganic materials modelling (e.g. metals, batteries, superconductors) but also biological modelling for the world of drug design. In composites, this multiscale modelling would be of significant interest to the aerospace, automotive and renewables industries to aid in the design of complex structures such as wind turbines. Of equal importance, the technology could be of interest to materials manufacturers as it has the potential to accelerate materials discovery and further the development of bespoke materials.

There are seven principal groups of beneficiaries for our new EPSRC Centre for Doctoral Training in Composites Science, Engineering, and Manufacturing.

1. Collaborating companies and organisations, who will gain privileged access to the unique concentration of research training and skills available within the CDT, through active participation in doctoral research projects. In the Centre we will explore innovative ideas, in conjunction with industrial partners, international partners, and other associated groups (CLF, Catapults). Showcase events, such as our annual conference, will offer opportunities to a much broader spectrum of potentially collaborating companies and other organisations. The supporting companies will benefit from cross-sector learning opportunities and

- specific innovations within their sponsored project that make a significant impact on the company;
- increased collaboration with academia;
- the development of blue-skies and long-term research at a lowered risk.

2. Early-stage investors, who will gain access to commercial opportunities that have been validated through proof-of-concept, through our NCC-led technology pull-through programme.

3. Academics within Bristol, across a diverse range of disciplines, and at other universities associated with Bristol through the Manufacturing Hub, will benefit from collaborative research and exploitation opportunities in our CDT. International visits made possible by the Centre will undoubtedly lead to a wider spectrum of research training and exploitation collaborations.

4. Research students will establish their reputations as part of the CDT. Training and experiences within the Centre will increase their awareness of wider and contextually important issues, such as IP identification, commercialisation opportunities, and engagement with the public.

5. Students at the partner universities (SFI - Limerick) and other institutions, who will benefit from the collaborative training environment through the technologically relevant feedback from commercial stakeholder organisations.

6. The University of Bristol will enhance their international profile in composites. In addition to the immediate gains such as high quality academic publications and conference presentations during the course of the Centre, the University gains from the collaboration with industry that will continue long after the participants graduate. This is shown by the

a) Follow-on research activities in related areas.
b) Willingness of past graduates to:

i) Act as advocates for the CDT through our alumni association;
ii) Participate in the Advisory Board of our proposed CDT;
iii) Act as mentors to current doctoral students.

7. Citizens of the UK. We have identified key fields in composites science, engineering and manufacturing technology which are of current strategic importance to the country and will demonstrate the route by which these fields will impact our lives. Our current CDTs have shown considerable impact on industry (e.g. Rolls Royce). Our proposed centre will continue to give this benefit. We have built activities into the CDT programme to develop wider competences of the students in:

a) Communication - presentations, videos, journal paper, workshops;
b) Exploitation - business plans and exploitation routes for research;
c) Public Understanding - science ambassador, schools events, website.