Key-areas

To provide the best possible services, our research facilities are structured around four key-areas: Bioprocesses, Physico-chemical processes, Analytical resources and Data and information systems.

Bioprocesses

Bioprocedes
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With more than 50 digesters and fermenters in operation 7/24 (0.1 L to 50 L), bioprocesses are at the core of our expertise. We are able to perform a wide range of experimental studies for waste and wastewater treatment and valorization, under controlled conditions and on-line monitoring, including microbiological characterization.

 

  • Anaerobic: methane and hydrogen production, including the production of molecules of industrial interest, biomethanation and production of single-cell protein (SCP) by purple phototrophic bacteria.
  • Aerobic: Composting (digestate), wastewater treatment solutions including microalgae and cyanobacteria, among others.

Physico-chemical processes

Procedes_physicochimiques
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Biomass pretreatment pilots: grinding, thermochemical, micro-waves, sonication as well as equipment for digestate and treated effluents post-treatment (membranes, filtration, precipitation, etc.).

 

 

Analytical resources

Ressources_analytiques
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Cutting-edge equipment for microbial and physico-chemical analysis for biomass characterization and bioprocesses monitoring.

 

 

Data and information systems

Systemes_de_donnees
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Bio2E has implemented a set of tools to manage the data generated from experimental studies conducted in our facilities with a FAIR  approach: IS (information systems), procedures for data description, data collection and storage.

 

 

  • The SILEX-LBE information system manages data for on-line monitoring of anaerobic processes, as well as microalgae production processes. It is connected to on-line data acquisition systems from sensors and automated or semi-automated analyzers.
  • EnviBIS is an ontology-based IS designed for environmental biorefinery data. It is issued from OpenSILEX, a set of methods, tools and components for IS implementation for large-scale data in agronomy, based on specifically designed ontologies