We have disseminated our research findings through a range of different outputs.
We hosted a webinar: The Future of Materials: Self-healing Polymers and Glass. Researchers from our consortium, discussed their work, showcasing the self-healing polymers and glasses they have developed as part of the project.
Haines-Gadd, M., Charnley, F. and Encinas-Oropesa, A. (2021) Self-healing materials: A pathway to immortal products or a risk to circular economy systems? Journal of Cleaner Production, Volume 315, 2021, 128193.
Rautiyal, P., Gupta, G., Edge, R., Leay, L., Daubney, A., Patel, M.K., Jones, A.H. and Bingham, P.A. (2021) Gamma irradiation-induced defects in borosilicate glasses for high-level radioactive waste immobilisation. Journal of Nuclear Materials, Volume 544, 2021, 152702, ISSN 0022-3115.
Chen, T.-Y., Rautiyal, P., Vaishnav, S., Gupta, G., Schlegl, H., Dawson, R.J., Evans, A.W., Kamali, S., Johnson, J.A., Johnson, C.E. and Bingham, P.A. (2020) Composition-structure-property effects of antimony in soda-lime-silica glasses. Journal of Non-Crystalline Solids, Volume 544, 2020, 120184, ISSN 0022-3093.
Maddock, R. M. A., Pollard, G. J., Moreau, N. G., Perry, J. J. and Race, P. R. (2020) Enzyme-catalysed polymer cross-linking: Biocatalytic tools for chemical biology, materials science and beyond. Biopolymers, Volume 111, Issue9, September 2020, e23390
Wang, W., Pang, W., Bingham, P. A., Mania, M., Chen, T. -Y. and Perry, J. J. (2020) Evolutionary Learning for Soft Margin Problems: A Case Study on Practical Problems with Kernels," 2020 IEEE Congress on Evolutionary Computation (CEC), 2020, pp. 1-7.
Wang, W., Moreau, N. G., Yuan, Y., Race, P. R. and Pang, W. (2019) Towards machine learning approaches for predicting the self-healing efficiency of materials. Computational Materials Science, Volume 168, 2019, Pages 180-187.