Spectral optical properties of selected photosynthetic microalgae producing biofuels

This paper presents the spectral complex index of refraction of biofuel producing photosynthetic microalgae between 400 and 750 nm. They were retrieved from their experimentally measured average absorption and scattering cross-sections. The microalgae were treated as homogeneous polydisperse spheres with equivalent diameter such that their surface area was identical to that of their actual spheroidal shape. An inverse method was developed combining Lorentz-Mie theory as the forward method and genetic algorithm. The unicellular green algae Chlamydomonas reinhardtii strain CC125 and its truncated chlorophyll antenna transformants tla1, tlaX, and tla1-CW+ as well as Botryococcus braunii, Chlorella sp., and Chlorococcum littorale were investigated. These species were selected for their ability to produce either hydrogen gas or lipids for liquid fuel production. Their retrieved real and imaginary parts of the complex index of refraction were continuous functions of wavelength with absorption peaks corresponding to those of in vivo Chlorophylls a and b. The T-matrix method was also found to accurately predict the experimental measurements by treating the microalgae as axisymmetric spheroids with the experimentally measured major and minor diameter distributions and the retrieved spectral complex index of refraction. Finally, pigment mass fractions were also estimated from the retrieved absorption index. The method and/or the reported optical properties can be used in various applications from ocean remote sensing, carbon cycle study, as well as photobiological carbon dioxide mitigation and biofuel production.

► Retrieval of optical properties from average absorption and scattering cross-sections. ► Inverse method based on Lorentz-Mie theory and genetic algorithm. ► Refraction and absorption indices of selected microalgae between 400 and 750 nm. ► Determination of pigment concentrations from absorption index. ► Good agreement between T-matrix predictions and measured radiation cross-sections.