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Realcat

REALCAT Team

REALCAT, a platform gathering high-throughput (HT) equipment for chemical catalyst and biocatalyst, was designed to develop the new concept of hybrid catalysis, which combines the best of the two worlds.


The REALCAT team operates last generation HT robots, fast analysis and HT characterization tools following a well-defined screening strategy. The integration of HT technologies generates a huge amount of data, which are analyzed and treated by the REALCAT team using advanced statistical tools.


The combination of the multidisciplinary skills of our experts with the speed of the HT equipment and the well-defined screening strategy constitutes the real strength of the Realcat platform to drive innovation in the field of catalysis.

Les forces de Realcat Figure 1 : REALCAT's Assets

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The UCCS
(Unit of Catalysis and Solid State Chemistry - UMR CNRS 8181)

The unit is structured around three axis: solid state chemistry, heterogeneous catalysis and catalysis and molecular chemistry. The UCCS activities focus on two main scientific domains: Energy and Sustainable Development.

The research projects are in the fields of biomass valorization, green chemistry, bio- sourced chemicals, pollution treatment, new and clean fuels, fuel and nuclear waste, fuel cells and high temperature electrolysers.

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The UCCS provides expertise to REALCAT in the fields of material science, chemical catalysis, characterization of catalysts and catalytic screening.

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REALCAT relies on the strong expertise in solid state chemistry and catalysis of UCCS and combines all its skills (synthesis, characterization, catalytic performance tests and development of HT screening tools). REALCAT projects are mainly dedicated to the development of sustainable catalytic processes.

The strength of UCCS research activities is relying on an approach at 3 levels:

  • News materials creation

    The research consists on the innovation in the field of new catalysts or new materials synthesis.


  • The development of advanced structural characterization methods to study the new materials development.

    This includes the High-Field NMR for solid and other methods of characterization (the X-ray diffraction, atomic force microscopy, surfaces analysis (XPS- ToF-SIMS).


  • Catalytic reactions implementation:

    It is performed from the laboratory scale to the industrial semi-pilot scale. The upscaling is made possible thanks to the catalytic pilot hall.

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Institut Charles VIOLLETTE 
ICV – cross-border laboratory BioEcoAgro

The Institut Charles VIOLLETTE is part of the cross-border UMR BioEcoAgro, which also brings together teams from the UPJV, INRAé and the TERRA research center in Gembloux, Belgium. Historically, the institute brings together three major scientific fields: plant biotechnology, white biotechnology and advanced analytical methods for quality control and safety assurance of food products of aquatic and local origin. It operates within the 9 teams that make up this mixed research unit, divided into 3 clusters of expertise:

  • Innovative cropping systems for agro-ecological and bio-economic transition in the context of climate change

  • Biomolecules of plant and microbial origin: from identification to production

  • Formulation – quality and food safety nutrition – health.

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VIOLLETTE brings its expertise to REALCAT in biotechnology, biocatalysis and screening of new biological/bio-based molecules.

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Among them, the team n°6 "Biotransformation / Enzymes and Biocatalysis" of the cluster n°2 is particularly involved in the development and operation of the REALCAT platform. It offers fundamental research in white biotechnology focused on the development of new innovative bioprocesses in the field of microbiology and enzymatic catalysis.

All of these projects are part of the production of new biomolecules of the peptide type intended for the agri-food or health sectors, and the production of biosourced platform molecules, particularly for polymer synthesis.

The Biotransformation / Enzymes and Biocatalysis team of the ICV is one of founders of REALCAT platform. The projects of this team focus on:

  • The control of biocatalytic tools

    for the valorization of food co-product originating from fishing and the agro-resources (plant polymers) by a new concept of biorefinery.

    The ultimate goal of this project is the bio-production of useful ingredients in the field of health as well as those of platforms molecules for chemistry and renewable energies.


  • The development of clean and integrated process

    for the selective production of functional biomolecules (intensification of production in bioreactors, extraction and purification of biomolecules, increase of productivity by process integration, modeling of these operations and identification of the factors to control for an up-scaling) and the transformation of agro-resources.


  • The control of transfers and interface processes

    occurring during the contact between biomolecules and microorganisms with materials of different physicochemical nature (food, roots, vegetative parts of the plant, cell walls, ...) in the process of digestive physiology.

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CRIStAL
(Research Center in Computer Science, Signal and Automatic Control of Lille) (UMR CNRS 9189)

CRIStAL research activities involve topics related to major scientific and social issues such as:

big data, software, image and its uses, human-computer interaction, robotics, control and supervision of large systems, intelligent embedded systems, ... with computer applications particularly in trade sectors of industry, technologies for health, smart grids.

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CRIStAL tasks involves:

  • fast and optimized analysis of the large data flow produced by the platform
  • rational selection of experiment and classification of the generated complexes enzyme

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Two CRIStAL teams are particularly involved in REALCAT platform

"Data Intelligence Group" (DatInG)

combines strong skills in databases, machine learning, data mining, and signal processing.

Its research focuses on graph databases for storing and querying information networks, signals (mathematical entities coming from physical measures), sequential data and addresses learning an optimal behavior in a dynamic, noisy, time-varying stream of data.


The Modeling for life sciences (MSV) group

designs algorithms and models to decode life. In particular, it is interested in addressing challenges in systems biology and genomics. How is the information encoded and transmitted?
How to predict the activity of the compounds, their interactions? How to model and simulate them?


The 3 actors and their role in the catalytic screening cycle

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Monitoring of all the data associated with a catalyser from its creation to its caracterization and the measurement of its performances in the reaction