Kinetic modelling of growth and storage molecule production in microalgae under mixotrophic and autotrophic conditions.

In order to improve algal biofuel production on a commercial-scale, an understanding of algal growth and fuel molecule accumulation is essential. A mathematical model is presented that describes biomass growth and storage molecule (TAG lipid and starch) accumulation in the freshwater microalga Chlorella vulgaris, under mixotrophic and autotrophic conditions. Biomass growth was formulated based on the Droop model, while the storage molecule production was calculated based on the carbon balance within the algal cells incorporating carbon fixation via photosynthesis, organic carbon uptake and functional biomass growth. The model was validated with experimental growth data of C. vulgaris and was found to fit the data well. Sensitivity analysis showed that the model performance was highly sensitive to variations in parameters associated with nutrient factors, photosynthesis and light intensity. The maximum productivity and biomass concentration were achieved under mixotrophic nitrogen sufficient conditions, while the maximum storage content was obtained under mixotrophic nitrogen deficient conditions.

Kinetic modelling of growth and storage molecule production in microalgae under mixotrophic and autotrophic conditions

In order to improve algal biofuel production on a commercial-scale, an understanding of algal growth and fuel molecule accumulation is essential. A mathematical model is presented that describes biomass growth and storage molecule (TAG lipid and starch) accumulation in the freshwater microalga Chlorella vulgaris, under mixotrophic and autotrophic conditions. Biomass growth was formulated based on the Droop model, while the storage molecule production was calculated based on the carbon balance within the algal cells incorporating carbon fixation via photosynthesis, organic carbon uptake and functional biomass growth. The model was validated with experimental growth data of C. vulgaris and was found to fit the data well. Sensitivity analysis showed that the model performance was highly sensitive to variations in parameters associated with nutrient factors, photosynthesis and light intensity. The maximum productivity and biomass concentration were achieved under mixotrophic nitrogen sufficient conditions, while the maximum storage content was obtained under mixotrophic nitrogen deficient conditions. © 2014 Elsevier Ltd.

SOI sensing technologies for harsh environment

This paper reviews and addresses certain aspects of Silicon-On-Insulator (SOI) technologies for a harsh environment. The paper first describes the need for specialized sensors in applications such as (i) domestic and other small-scale boilers, (ii) CO2 Capture and Sequestration, (iii) oil & gas storage and transportation, and (iv) automotive. We describe in brief the advantages and special features of SOI technology for sensing applications requiring temperatures in excess of the typical bulk silicon junction temperatures of 150oC. Finally we present the concepts, structures and prototypes of simple and smart micro-hotplate and Infra Red (IR) based emitters for NDIR (Non Dispersive IR) gas sensors in harsh environments. © 2012 IEEE.