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Application of machine learning for development of a drying protocol for microalga Chlorella minutissima in a single rotary drum dryer for biodiesel production
  • SASHI SONKAR,
  • Shibani .,
  • Nirupama Mallick
SASHI SONKAR
Indian Institute of Technology Kharagpur
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Shibani .
Birla Institute of Technology and Science Pilani
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Nirupama Mallick
Indian Institute of Technology Kharagpur
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Abstract

Drying of microalgal slurry is one of the important steps of downstream processing which faces several technical challenges for cost-effective biodiesel production. In this investigation, drying of C. minutissima was carried out by a single rotary drum dryer with varied drum surface temperature and rotational speed. Application of machine learning tool classified the range of residual moisture content to be <10% (wet biomass) for high lipid recovery with an accuracy of 97%. Based on the drying time, lipid recovery, and energy consumption, drum drying at 80 °C drum surface temperature with 0.3 rpm depicted ˃90% lipid recovery as compared to the bone-dried biomass. The energy consumption of 7.328 kWh for 1 kg of dried biomass was recorded with profoundly lower drying time, thus could be recommended for drying of the microalgal slurry at industrial scale.

Peer review status:POSTED

23 Oct 2020Submitted to Biotechnology and Bioengineering
24 Oct 2020Assigned to Editor
24 Oct 2020Submission Checks Completed