A virtual replication tool to combine soil phytoremediation with lignocellulosic biomass valorisation.

Biotech+AI

PHYBI: Phytomanagement as a sustainable feedstock source of lignocellulosic-based high-value bio-based products for textile applications.

PHYBI concept is to combine the soil phytoremediation concept with lignocellulosic biomass valorisation in an integrated phytomanagement circular economy approach.

 

This concept focuses its efforts across different levels of development:

 

  • Test, optimization and validation of four phytomanagement case studies;
  • Optimisation of biomass fractionation into lignocellulosic components based on organosolv technique; and
  • Characterisation and application of lignocellulosic fractions to create a well-planned market route for the potential end-applications in the textile industry.

 

Furthermore, the project develops a Virtual Replication Tool where phytomanagement, valorisation process and end-products are integrated, resulting in guidelines, recommendations and thresholds for the replication of PHYBI’s case studies along other areas.

 

To finalise the project concept, social innovation activities strongly connect the process with the market and society with the aim to deliver high quality products with high level of acceptance. To achieve its goals, PHYBI brings together a multidisciplinary team integrating experts in plant and soil science, chemical engineering and biorefineries, computational science, textile materials and products, agroindustry, and market analysis, knowledge exchange and social innovation.


Our main tasks

  • Modelling of plant/microbe interactions to improve phytoremediation.
  • Collection of data and database management.
  • Modelling of the unitary processes.
  • Virtual tool development.
  • User-friendly interface and open source version.
  • Integrated sustainability assessment and guidelines for future implementation.
  • Scientific and technical coordination.
  • Administrative and financial management.
  • Risk management.
  • Research data management.

Partners

CETIM | DIH LEAF | IDENER.AI | MISCANTHUS DOO | NEXT TECHNOLOGY TECNOTESSILE | PHYTOWELT GREEN TECHNOLOGIES | STEINBEIS | UNIVERSIDAD DE BURGOS | UNIVERSIDAD DE OVIEDO | UNIVERSITY BOURGOGNE FRANCHE COMTÉ

Start date – finish date

10 / 2024 - 09 / 2028


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement Nº 101156439