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  4. Modelling and process optimization for biodiesel production from Nannochloropsis salina using artificial neural network
 
research article

Modelling and process optimization for biodiesel production from Nannochloropsis salina using artificial neural network

Raj, J. Vinoth Arul
•
Kumar, R. Praveen
•
Vijayakumar, B.
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June 1, 2021
Bioresource Technology

In the present investigation, calcium oxide solid nanocatalyst derived from the egg shell and Nannochloropsis salina were used for the production of biodiesel. The morphological characteristics and functional groups of synthesized nanocatalyst was characterized by SEM and FTIR analysis. Process variables optimization for biodiesel production was studied using RSM and ANN. The R-2 values for RSM and ANN was found to be 0.8751 and 0.957 which showed that the model was significantly fit with the experimental data. The maximum FAME conversion for the synthesized nanocatalyst CaO was found to be 86.1% under optimum process conditions (nanocatalyst amount: 3% (w/v); oil to methanol ratio 1:6 (v/v); reaction temperature: 60 degrees C; reaction time 55 min). Concentration of FAME present in biodiesel was identified by GC-MS analysis.

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Type
research article
DOI
10.1016/j.biortech.2021.124872
Web of Science ID

WOS:000634859300010

Author(s)
Raj, J. Vinoth Arul
Kumar, R. Praveen
Vijayakumar, B.
Gnansounou, Edgard  
Bharathiraja, B.
Date Issued

2021-06-01

Publisher

ELSEVIER SCI LTD

Published in
Bioresource Technology
Volume

329

Article Number

124872

Subjects

Agricultural Engineering

•

Biotechnology & Applied Microbiology

•

Energy & Fuels

•

Agriculture

•

nannochloropsis salina

•

artificial neural network

•

biodiesel

•

egg shell

•

nanocatalyst

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
GR-GN  
Available on Infoscience
April 24, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/177546
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