WP9 Supporting technology for data interpretation

Partners involved: UL (WP leader), DTU, TUB, Micronit.

Successful application of MBR technology should rely on maximizing the exploitation of the flexibility and the capabilities of the MBR platform to deliver information-rich experiments on one hand, and on extracting as much information as possible from the obtained experimental data on the other hand. In practice, this can be achieved by coupling advanced mathematical data interpretation to the MBR experiments. This WP is therefore devoted to technologies that support MBR development.

Research plan

Cultivations (WP6) and biocatalysis processes at microscale (WP7) will be described by mechanistic models of reactor systems both based on ordinary differential equations (ODEs) or partial differential equations (PDEs), and will specifically be based on the modeling of S. cerevisiae batch and continuous. Based on an existing Matlab toolbox, the application of uncertainty and sensitivity analysis for this model will be implemented with the aim to propose adjustments to the operation and the data-collection of the experimental set-up.

Furthermore, software sensors will be developed for the MBR platforms, to extend the number of variables for which on-line information is available. The two chemometric methods principal component analysis (PCA) and partial least squares (PLS) regression are commonly applied together with spectroscopic data (WP8) and process data (WP6), and will be used to predict variables such as biomass concentration and substrate concentration which are usually difficult to measure.

An analysis of fluid dynamics, transport phenomena and reaction kinetics will be developed for different enzyme-catalyzed processes within microstructured devices (WP7) and analyzed by on-line monitoring with optical nano- sensor particles (WP8).

A CFD modelling of biocatalytic conversions within a MBR will be investigated (WP6). The possibilities for either phenomenological or empirical modelling of the particle/surfaces/microorganisms-interactions (WP6 and WP8) will be evaluated. Validation of the CFD simulations will be based on a micro Particle Image Velocimetry and Confocal Laser Scanning Microscopy, enabling to analyse specific growth/production patterns at the microscale.

Methods for Design of Experiments (DoE) will be incorporated in software such as MatlabTM, and on coupling these on-line to the MBR platform (WP6). The final goal is to demonstrate the ability of exploiting continuous culture MBRs with S. cerevisiae in a DoE, for example to characterize the design space of the process (WP6).