Accelerating the Scale-up of Next-Generation Fuels from CO2

IDRIC Project MIP 5.7

University of Southampton
University of Chester

Background

A deeper level of understanding is required at the lab-scale in terms of species conversion for a range of physical and operational parametric variations. Experimental investigations will inform and validate advancements in a recently developed computational model that is 150% faster than discrete element modelling (DEM) with computational times scaling linearly with reactor size, as opposed to exponentially for the DEM model. Reactor and operational datasets will be used to optimise methanol yields. Industrial interactions are essential to consider varied feedstock compositions including contaminants which are considerable in practice given feedstock stems from waste resources. Engagement with partners across at least two industrial clusters will guide the study towards operating conditions at scale and provide a sense check for scalability.

Dr Lindsay-Marie Armstrong

Dr Lindsay-Marie Armstrong

Principal Investigator
University of Southampton

Project Team

University of Southampton:

Professor Robert Raja
Dr Stylianos Kyrimis

Aim

This interdisciplinary study will combine experimental and computational scale-up study to conduct a performance optimisation and scale-up feasibility study for waste-to-methanol and waste-to-sustainable aviation fuel for the hard-to-decarbonise transportation sector.

More Detail

BACKGROUND: The IEA recognises that CO2-derived products will play a global role in reducing CO2 emissions, but only if their demand exceeds 10 MtCO2/year. CO2-based fuels can drastically increase the demand and consumption of captured CO2 by up to 2050 Mt/year as a sustainable energy vector. Methanol synthesis via CO2 hydrogenation is less exothermic; utilises simpler and more efficient reactors and heat exchangers; lowering operational costs. However, the water products and accompanying water-gas-shift, expedites catalyst deactivation. This process can be industrially competitive if optimal operating conditions are identified, including exploring the influence of catalyst morphology and physicochemical properties for greater activity and methanol selectivity. Kinetic models already exist for the industrial Cu/ZnO/Al2O3 catalyst yet there is a need to optimise performance for varying operating conditions, CO2 feedstock and process integration.

INNOVATIVE ASPECTS: Long-term research needs to address its feasibility at different scales, sectors and applications, types and proportion of fuel blends; optimisation of the catalyst, reactor and system; etc. Immediate research project will upgrade a recently developed state-of-the-art multiphase scale-up tool to incorporate more detailed intra- and inter-catalytic behaviour under varying operational conditions and varying waste feedstock compositions for the synthesis of a particular fuel, e.g., methanol and potentially for SAF.

Fig 1: High resolution 3D ethanol conversion for DEM model vs SR model vs standard porosity models.

Fig 1: High resolution 3D ethanol conversion for DEM model vs SR model vs standard porosity models. DEM scaled exponentially with particle size, the SR and porosity models scaled linearly.

Meet the Team

 

Professor Robert Raja

Professor Robert Raja

University of Southampton

Dr Stylianos Kyrimis

Dr Stylianos Kyrimis

University of Southampton

Professor Robert Raja

Professor Robert Raja

University of Southampton

Dr Stylianos Kyrimis

Dr Stylianos Kyrimis

University of Southampton

Associated Outputs