individual projects

A synthetic description of all Early Stage Researchers (ESR) Individual Research Projects is provided in the following table.

TitleInstitutionObjectives
Assessment of light dynamics on growth performance and definition of model-based protocol for algae selection and genetic manipulationUniversity of Padova - contacts: Prof. Tomas Morosinotto, Prof. Fabrizio BezzoBiological assessment of the effects of light dynamics on microalgae growth. Identification of key biological parameters for manipulation (interaction with ESR13 to define priorities). Model-based quantification of potential benefits a given mutation on microalgae productivity. Prioritisation of potential targets for genetic manipulation (e.g. by deactivating heat dissipation boost performance in conditions of low illumination).
Experimental and numerical investigation of culture systems involving complementary species for N2 fixation and extended solar radiation absorptionImperial College London - contacts: Prof. William Rutherford, Prof.
Benoit Chachuat
Measurement of photosynthetic parameters and ammonium levels in N2-fixing strains and newly discovered far-red chlorophyll f-containing strains; formulation/calibration of mathematical models describing light-limited growth for particular wavelengths, describing nitrogen fixation / nitrogen-limited growth; experimental investigation of multi-layered culture systems combining N2-fixing strains and far-red chlorophyll f-containing strains.
Development and experimental assessment of a modelling approach for nutrient-light interactions description and optimisationTechnical University of Denmark - contacts: Prof. Irini AngelidakiThe following objectives will be pursued: i) to elucidate interactions between light, nutrients in respect to microalgae growth via experimental investigations; ii) to formulate the interdependencies in growth kinetics; iii) to formulate usable model to describe these growth interdependencies; iv) to validate the model; v) assessment of wireless illumination technology for optimal low-energy intensity control.
Development and analysis of a digital twin for monitoring, control and optimisation applications in microalgae: the Microalgae Growth Model (MGM)INRIA - contacts: Prof. Olivier BernardIntegration of state-of-the-art photosynthesis models and metabolic flux modelling approaches (DRUM framework); numerical investigation of the dynamics of nitrogen and carbon storage under variable light (e.g. diurnal cycle) using dynamic flux balance analysis; derivation of reduced models for on-line monitoring and control applications; interaction with ESR11 to integrate MGM with deep learning techniques.
Advanced techniques for model-based experiment design under uncertainty Process Systems Enterprise - contacts: Prof. Costas Pantelides, Prof. Benoit Chachuat.Develop new techniques for designing experiments using first-principles models, with particular emphasis on (a) experiments leading to improved accuracy of both model parameters and specified key performance indicators; (b) experiments for model discrimination; (c) effective handling of model uncertainty in the context of model-based experiment design. Implement these techniques within the company process modelling environment.
Development of a continuous microphotobioreactor for rapid model identificationUniversity of Padova - contacts: Prof. Fabrizio Bezzo, Dr. Eleonora SforzaDevelop a microphotobioreactor capable of: i) generation of multiple concentration gradients, ii) support of long-term culture of algae cells iii) setting different temperature levels and complex light dynamics; iv) high-throughput studies with large numbers of replicates, v) compatibility with on-line imaging and standard analytics, vi) capability to apply fast dynamic changes of environmental signals.
Microalgal population dynamics related to changes of environmental conditions TU Dresden - contacts: Prof. Thomas Walther, Dr.
Felix Krujatz
Development of a population model to describe how environmental conditions (e.g. temperature, light, nutrients) may cause the formation of sub-populations with varying cellular and metabolic properties. Integration of population models with MGM model. Definition of control strategies for favouring the growth of desired high-product populations. Experimental assessment of flow cytometry single-cell analyses to monitor population dynamics.
Development of an online monitoring system of culture fitness and stress-induced intracellular metabolite accumulation in microalgae“G. W. Leibniz” University of
Hannover - contacs: Dr. Ivo Havlik, Prof. Thomas Scheper
Development of an online optical sensor; development of an online culture colour measurement sensor (hardware, software); development of a software sensor using inputs from absorbance, colour, fluorescence, pO2 and other sensors for the microalgae culture fitness estimation; development of sensors for the estimation of accumulation of selected intracellular metabolites as lipids and/or pigments in selected microalgae strains.
Sensor technology fusion for on-line monitoring and control Wageningen University - contacts: Dr. Marcel JanssenIntegration of state-of-the-art sensor technology: integration of on-line monitoring and mass balancing based on the measurement of CO2 consumption, O2 production, biomass production and nitrogen consumption; inclusion of PAM fluorescence and VIS absorption spectroscopy. Methods for integrating MGM approach to sensors for a generic model description of microalgal production processes.
Data mining approaches for monitoring and decision support of PBR processes. Proviron - contacts: Dr. Luc Roef, Prof. Kris Laukens.Key objectives will be: i) development of a platform for integrative data mining of heterogeneous monitoring data for the prediction of process outcomes;
ii) new methods for predictive analysis of the response to growth condition permutations; iii) development of artificial
intelligence-based predictive models for monitoring and optimisation of growth conditions.
Development of a deep-learning platform for process monitoring and optimisationMINT Engineering - contacts: Mr. Gunnar Mühlstädt, Prof.
Thomas Walther.
Development of deep learning algorithms combining process models and neural networks for a rapid indirect measurements of biological variables of interest; integration (data fusion) of sensor systems in different scales of industrial tubing PBRs (scale-effect); development of tools for automatic operation based on biological specific response (strain-dependent) and cultivation features (geometry-dependent).
Microalgae high rate production by optimising biofilm-based system CentraleSupélec - contacts: Prof. Filipa Lopes, Prof.
Sihem Tebbani
Development of a model of biofilm growth dynamics and process productivity based on the generic MGM model; design of a control law aiming at maintaining optimal operating conditions that maximises the process productivity; the control law must be robust with respect to model uncertainties, estimation errors and disturbances (e.g. light variation); assessment of the benefits of a biofilm-based process over a suspended culture.
Modelling and control of the photoacclimation response in an industrial environment TMCI Padovan - contacts: Dr. Diana Simionato, Prof.
Tomas Morosinotto
Assessing photoacclimation dynamics and interactions with other photosynthetic processes; measurement and modelling in an industrial environment; assessment of photoacclimation and adaptation dynamics of selected strains and mutants; interactions between temperature and light dynamics; definition of operation strategies for optimising the response of different microalgae at varying light conditions.
Modelling and control of microalgae bacteria consortia for wastewater treatmentUniversity of Almeria - contacts: Prof. Jose
María Fernández Sevilla, Prof. Francisco Gabriel Acién Fernandez
Experimental assessment of conditions affecting growth and activity of microalgae-bacteria consortia; identification of minimum measurements required to monitor the performance of wastewater treatment; development of a model-based approach for control and optimisation of wastewater treatment in large scale reactors using microalgae.
Robust control of microalgae processes accounting for future meteorologyINRIA - contacts: Dr. Madalena Chaves, prof. Olivier BernardAutomatic model calibration from pre-treated on-line data; use future weather forecasts to optimise water and energy fluxes; from global optimisation of large scale models, develop an advanced framework within a commercial technological platform own by INRIA; assess the potential of this approach with pilot raceways; develop protocols allowing for real-time reconciliation of all sensor data resulting in real-time.