Microalgae biomass has a strong potential as alternative, 3rd generation non crop-based biofuel. Biofuel production from microalgal biomass also directly tackles the paramount problem of climate change: fuel produced from carbon fixation from atmosphere drastically cuts the CO2 footprint of energy production.
The efforts to face scarcity of resources and climate change is even more important in the current positive demographic trend. Algae-based biomass is promising also for renewable chemicals production, enzyme technology and directed evolution-based processes.
One major limitation for scale-up to large-area cultivation, setting a technological barrier for current or potential markets, is the availability of systems for efficient monitoring. While microalgae biomass cultivated at the lab-scale reaches high and controllable yields, monitoring large-scale cultivation systems is complicated, especially for complex factor as lipids content, yet it is seminal to boost competitiveness with non-renewable energy suppliers.
In LASinAFuel we aim to realise intrinsic biolasers sensors in unicellular microalgae based on WGM microresonators, to develop a fast analysis of the status of these organisms. Their oil droplets are perfect candidates for realisation of intracellular WGM microlasers, with great potential for fast and accurate sensing of their size, shape and surface interactions. A wealth of information can then be extracted related to microalgal lifecycle and growth, oil accumulation, mechanical forces and physical stresses occurring on the individual oil droplet. This breakthrough tool is conceived for specialised laboratories, but with specific protocols and guidelines it can also be translated to non-specialised use.
Remarkably, only a few species of microalgae have been tested for biofuel production, and only some of them have been screened versus nutrients and cultivation conditions: a fast and reliable monitoring tool is needed to boost a potentially enormous screening of uncharacterised microalgae and cultivation conditions. Moreover, other long-term strategies based on directed evolution approaches (a strategy awarded this year with the Nobel Prize in Chemistry) may also be successfully screened with the biolasing approach developed in this project.
In addition, dyes distributing differently in the various algal microenvironments will be exploited to develop an easy, cheap and user-friendly method for estimation of oil amount per microalgal unit. The method will be based on a colorimetric test to perform with a smartphone app, and being ratiometric it will not need calibration. The average colour emitted or reflected by the sample will be decoded by the smartphone to yield the mean oil content. Ultimately, the envisioned potential of LASinAFuel is the development of a fast and sensitive detection tool to apply in all high-throughput screenings of oil-producing microalgae, both for research and for industrial large-scale cultivations.