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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
  • Shibani .,
  • Nirupama Mallick
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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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.
23 Oct 2020Submitted to Biotechnology and Bioengineering
24 Oct 2020Assigned to Editor
24 Oct 2020Submission Checks Completed