Politecnico is also involved in supporting the use of renewable fuels of biological and non-biological origin to reduce greenhouse gas emissions in industrial processes where transitioning to fully electrified processes is challenging, such as marine transport and the steel industry. Politecnico is a partner in the Horizon Europe Innovation Action project BUTTERFLY (Biomass Utilised to the Extended Portfolio of Renewable Fuels with Large Yields), which, coordinated by the Netherlands Organisation for Applied Scientific Research (TNO), involves collaboration among industries, utility companies, research centres and SMEs from 6 EU countries.
BUTTERFLY, with funding of €10.5 million, aims to develop a process for the simultaneous production of rDME (a renewable version of the molecule DME, DiMethyl Ether, a possible substitute for diesel) and SNG (Synthetic Natural Gas, which can be used in our existing infrastructure). The research is carried out by studying the conversion of three different biomasses (lignocellulosic biomass from wood residues, industrial waste and organic waste) for applications in the steel industry, off-grid energy supply and heavy transport.
The flexibility introduced by BUTTERFLY’s process will allow adaptation to the market and the availability of biomass resources, increasing productivity and reducing costs, with carbon recovery efficiency around 97% and biomass conversion efficiency 15% higher than the current best-known methods,
Giampaolo Manzolini, full professor in the Department of Energy and activity coordinator at Politecnico di Milano
The diversification generated by the use of these different types of waste, combined with their valorisation, contributes to the reduction of the costs associated with producing advanced biofuels, the reduction of fossil fuel consumption in sectors requiring a lot of energy and, consequently, the reduction of greenhouse gas emissions.
Our activities in the process are concentrated on integrating different innovative processes developed by partners in order to maximise the yield of the plant and provide optimal management strategies, including through the use of Digital Twins, i.e. virtual replicas of the plant, which enable real-time assessment of the best management options.