Integrating digital modelling techniques to develop a sugarcane biowaste valorisation process
- Project lead
- Dongda Zhang
- Institute
- The University of Manchester
Summary:
This project aims to improve the technology readiness level and manufacturability of a sustainable industrial biotechnology developed at Green Fuel Research Ltd. (GFR) which can effectively create valuable chemicals (butanol, succinic acid and lactic acid) from sugarcane biomass waste. The project strongly underpins a UK’s national research priority – Growing the Bioeconomy. The UK’s bioeconomy is currently worth £220 billion and is estimated to double by the year 2030. GFR is a UK company which specialises in developing the next generation bio-refinery platform for valorising biowaste from sugarcane and paper industries. Specifically, this research project will focus on improving the performance of several key steps including raw material detoxification, hydrolysate fermentation, and downstream product separation through the use of advanced digital modelling techniques including machine learning, data-driven optimisation, kinetic modelling, and rigorous process simulation and intensification.
Aims:
- Develop and apply novel digital modelling techniques for ABE process data analysis, process design, and process optimisation;
- Investigate different product separation techniques and explore the feasibility of designing an intensified reaction-separation system;
- Understand biowaste carbon utilisation efficiency of the underlying process for production of different biofuels;
- Enable knowledge exchange and establish a long-term collaboration between the University of Manchester and GFR.
Outcomes:
We developed and compared different dynamic models to understand carbon utilisation efficiency of ABE fermentation process for production of different biofuels, and developed a design of experiments framework to assist process optimisation. We have also investigated different product separation techniques to minimise energy use and waster emissions, with process flowsheet models developed and compared against literature information. These results pave the way to accelerate the scale-up of biomass valorisation technology and translation of biological sciences into bio-based sustainable manufacturing. In addition, research outcome of this project has been used as evidence to secure a 4-year BBSRC DTP CASE PhD project.
Impact:
This project helps identify promising separation strategies to improve the TRL and economic viability of GRF’s biotechnology, allowing for future upscaling of this bioprocess. Knowledge exchange is accomplished by applying the digital modelling tools developed in Zhang’s group to analyse ABE process data, making practical contributions to the bioprocess industry.
Academic partner: Dongda Zhang, The University of Manchester
Industry partner: Sergio Lima, Green Fuels Research Ltd
