Biological computation for programmed applications of biomineralized photosynthetic engineered living material (BP-ELM)

This project seeks to define parameters to scale up Engineered Living Materials for low-carbon construction. Using a novel process of photosynthetically mediated biomineralization, the proposed research seeks to produce bulk solid phase materials using cyanobacterial organisms. This presents a manufacturing opportunity to create light-powered, carbon negative living architecture, reducing the footprint of our built environment.
The research will use biochemical engineering techniques to achieve a goal of programmable animate materials. Experimental characterisation of the biophysical (gas transfer, light wavelength) and biochemical parameters (nutrients) governing growth of the cyanobacterial species capable of biomineralisation will be conducted in order to determine the stimuli-response relationships. Dynamics will be analysed through machine learning to create a semantic data model and applied digitally to simulate the behaviour of the BP-ELM. A design-build-test cycle will be adopted to refine the model through fabrication of scale-up prototypes. This will establish which biological stimuli will become input parameters to define material properties and inform on-demand growth and regeneration.
To deliver this project, the student will receive training in bioprocess scale up techniques and advanced robotic manufacturing. The proposal is aligned with the remit of Bio-ID, and has evolved out of the independent, original research of Mr.Tamuli.

EPSRC remit:
All projects must lie within EPSRC's remit. Please provide at least 1 and up to 3 of EPSRC's research areas that this project fits within. The list of research areas are available on EPSRC's website.