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

被引：50

作者：

Raj, J. Vinoth Arul ^{[1
]}

Kumar, R. Praveen ^{[1
]}

Vijayakumar, B. ^{[2
]}

Gnansounou, Edgard ^{[3
]}

Bharathiraja, B. ^{[2
]}

机构：

[1] Arunai Engn Coll, Dept Biotechnol, Thiruvannaamalai 606603, India

[2] Vel Tech High Tech Dr Rangarajan Dr Sakunthala En, Chennai 600062, Tamil Nadu, India

[3] Ecole Polytech Fed Lausanne EPFL, Bioenergy & Energy Planning Res Grp, CH-1015 Lausanne, Switzerland

来源：

BIORESOURCE TECHNOLOGY | 2021年 / 329卷

关键词：

Nannochloropsis salina; Artificial neural network; Biodiesel; Egg shell; Nanocatalyst; RESPONSE-SURFACE METHODOLOGY; WASTE COOKING OIL; TRANSESTERIFICATION; CATALYST; SHELL; ANN; NANOCATALYST; FAME; RSM;

D O I：

10.1016/j.biortech.2021.124872

中图分类号：

S2 [农业工程];

学科分类号：

0828 ;

摘要：

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.

引用

页数：8

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