Algae are the promising feedstock of biofuel. The screening of competent species and proper fertilizer supply is of the most important tasks. To accelerate this rather slow and laborious step, we developed an integrated high-throughput digital microfluidic (DMF) system that uses a discrete droplet to serve as a microbioreactor, encapsulating microalgal cells. On the basis of fundamental understanding of various droplet hydrodynamics induced by the existence of different sorts of ions and biological species, incorporation of capacitance-based position estimator, electrode-saving-based compensation, and deterministic splitting approach, was performed to optimize the DMF bioreactor. Thus, it enables all processes (e.g., nutrient gradient generation, algae culturing, and analyzing of growth and lipid accumulation) occurring automatically on-chip especially in a high-fidelity way. The ability of the system to compare different microalgal strains on-chip was investigated. Also, the Chlorella sp. were stressed by various conditions and then growth and oil accumulation were analyzed and compared, which demonstrated its potential as a powerful tool to investigate microalgal lipid accumulation at significantly lower laborites and reduced time.
Keywords: DMF bioreactor; algal biofuels; automatic screening; nutrient gradient.
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