A modelling approach for high-value products from microalgae

Microalgae have a broad spectrum of potential applications, such as for human consumption, aquaculture feed, nutraceuticals and pharmaceuticals. The utilisation of microalgae offers a sustainable approach due to their ability to fixate CO2 and uptake inorganic nitrogen and phosphorous sources from wastewater. The freshwater microalgae Haematococcus pluvialis is of explicit industrial interest due to its

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Adaptive Model for temperature control

Due to the complex dynamics of the growth of microalgae a sophisticated control method is needed, to achieve the maximum yield out of a microalgae plant. Model-predictive control (MPC) is a powerful tool gaining a lot of attention in the field of modern control systems. With the help of an underlying model predicting the system

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Microalgal population dynamics related to changes of environmental

Microalgae constitute the basis of life, in a variety of marine and freshwater ecosystems. They are efficient cell factories, the majority operating photosynthetically to turn light energy and atmospheric carbon dioxide (CO2) with simple inorganic nutrients into biomass. Moreover, they have great potential for the production of industrially relevant high-value products such as proteins, polysaccharides,

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Advanced techniques for model-based experiment design under uncertainty

The use of first-principles mathematical models to describe bio-chemical phenomena is paramount to the effective development of microalgae processes. Model-based design of experiments (MBDoE) represents a valuable tool providing several methodologies that assist the model-building strategy of such complex mathematical models. The objective is to design experiments (or campaigns of experiments) that will provide the

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