Optimization of dual transesterification of jatropha seed oil to biolubricant using hybridized response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS)-genetic algorithm (GA)
The over-reliance of the industrial and automobile sectors on petroleum-based lubricants, the feedstocks of which pose environmental challenges, has generated the need for sustainable alternatives in order to promote economic development and a sustainable green environment. The study investigated th...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Sustainable Chemistry for the Environment |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949839223000500 |
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| author | Callistus N. Ude Christopher N. Igwilo Kenechi Nwosu-Obieogu Patrick C. Nnaji Collins N. Oguanobi Ndidi F. Amulu Cordelia Nneka Eze Uchenna C. Omenihu |
| author_facet | Callistus N. Ude Christopher N. Igwilo Kenechi Nwosu-Obieogu Patrick C. Nnaji Collins N. Oguanobi Ndidi F. Amulu Cordelia Nneka Eze Uchenna C. Omenihu |
| author_sort | Callistus N. Ude |
| collection | DOAJ |
| description | The over-reliance of the industrial and automobile sectors on petroleum-based lubricants, the feedstocks of which pose environmental challenges, has generated the need for sustainable alternatives in order to promote economic development and a sustainable green environment. The study investigated the optimization of process variables for the dual transesterification of jatropha seed oil into a biolubricant using a hybridized response surface methodology-genetic algorithm (RSM-GA) and an adaptive neuro-fuzzy inference system-genetic algorithm (ANFIS-GA). The seed oil was extracted using a Soxhlet extractor and characterized for its physicochemical properties. The catalyst for the reaction was synthesized by the acid modification of clay. The experimental design was created using Design Expert, and process parameters were optimized using RSM-GA and ANFIS-GA. The yield of oil was 56%, and its properties did not impede the catalyst from transesterification without pretreatment. The modified clay effectively converted the jatropha seed oil into a biolubricant. The ANFIS-GA model attained the highest yields (92.36%) under the optimal parameters of 3 h reaction time, 120 °C reaction temperature, 3% wt catalyst dosage, 5:1 TMP/JSOME molar ratio, and 300 rpm agitation speed. Therefore, the incorporation of ANFIS and RSM with GA was more efficient in optimizing and predicting the biolubricant yield. |
| first_indexed | 2024-04-24T16:46:54Z |
| format | Article |
| id | doaj.art-090eed1b68b44b8280e083da8dd72d5a |
| institution | Directory Open Access Journal |
| issn | 2949-8392 |
| language | English |
| last_indexed | 2024-04-24T16:46:54Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Sustainable Chemistry for the Environment |
| spelling | doaj.art-090eed1b68b44b8280e083da8dd72d5a2024-03-29T05:52:32ZengElsevierSustainable Chemistry for the Environment2949-83922023-12-014100050Optimization of dual transesterification of jatropha seed oil to biolubricant using hybridized response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS)-genetic algorithm (GA)Callistus N. Ude0Christopher N. Igwilo1Kenechi Nwosu-Obieogu2Patrick C. Nnaji3Collins N. Oguanobi4Ndidi F. Amulu5Cordelia Nneka Eze6Uchenna C. Omenihu7Department of Chemical Engineering, Michael Okpara University of Agriculture, Umudike, Umuahia, Abia State, Nigeria; Corresponding author.Department of Science Laboratory Technology, Federal College of Agriculture, P.M.B. 7008, Ishiagu, Ebonyi State, NigeriaDepartment of Chemical Engineering, Michael Okpara University of Agriculture, Umudike, Umuahia, Abia State, NigeriaDepartment of Chemical Engineering, Michael Okpara University of Agriculture, Umudike, Umuahia, Abia State, NigeriaDepartment of Chemical Engineering, Michael Okpara University of Agriculture, Umudike, Umuahia, Abia State, NigeriaDepartment of Chemical Engineering, Institute of Management and Technology, Enugu, Enugu State, NigeriaDepartment of Chemical Engineering, Chukwuemeka Odumegwu Ojukwu University, Uli, Anambra State, NigeriaDepartment of Chemical Engineering, Michael Okpara University of Agriculture, Umudike, Umuahia, Abia State, NigeriaThe over-reliance of the industrial and automobile sectors on petroleum-based lubricants, the feedstocks of which pose environmental challenges, has generated the need for sustainable alternatives in order to promote economic development and a sustainable green environment. The study investigated the optimization of process variables for the dual transesterification of jatropha seed oil into a biolubricant using a hybridized response surface methodology-genetic algorithm (RSM-GA) and an adaptive neuro-fuzzy inference system-genetic algorithm (ANFIS-GA). The seed oil was extracted using a Soxhlet extractor and characterized for its physicochemical properties. The catalyst for the reaction was synthesized by the acid modification of clay. The experimental design was created using Design Expert, and process parameters were optimized using RSM-GA and ANFIS-GA. The yield of oil was 56%, and its properties did not impede the catalyst from transesterification without pretreatment. The modified clay effectively converted the jatropha seed oil into a biolubricant. The ANFIS-GA model attained the highest yields (92.36%) under the optimal parameters of 3 h reaction time, 120 °C reaction temperature, 3% wt catalyst dosage, 5:1 TMP/JSOME molar ratio, and 300 rpm agitation speed. Therefore, the incorporation of ANFIS and RSM with GA was more efficient in optimizing and predicting the biolubricant yield.http://www.sciencedirect.com/science/article/pii/S2949839223000500Response surface methodologyAdaptive neuro fuzzy inference systemTransesterificationGenetic algorithmJatropha seed oil |
| spellingShingle | Callistus N. Ude Christopher N. Igwilo Kenechi Nwosu-Obieogu Patrick C. Nnaji Collins N. Oguanobi Ndidi F. Amulu Cordelia Nneka Eze Uchenna C. Omenihu Optimization of dual transesterification of jatropha seed oil to biolubricant using hybridized response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS)-genetic algorithm (GA) Sustainable Chemistry for the Environment Response surface methodology Adaptive neuro fuzzy inference system Transesterification Genetic algorithm Jatropha seed oil |
| title | Optimization of dual transesterification of jatropha seed oil to biolubricant using hybridized response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS)-genetic algorithm (GA) |
| title_full | Optimization of dual transesterification of jatropha seed oil to biolubricant using hybridized response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS)-genetic algorithm (GA) |
| title_fullStr | Optimization of dual transesterification of jatropha seed oil to biolubricant using hybridized response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS)-genetic algorithm (GA) |
| title_full_unstemmed | Optimization of dual transesterification of jatropha seed oil to biolubricant using hybridized response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS)-genetic algorithm (GA) |
| title_short | Optimization of dual transesterification of jatropha seed oil to biolubricant using hybridized response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS)-genetic algorithm (GA) |
| title_sort | optimization of dual transesterification of jatropha seed oil to biolubricant using hybridized response surface methodology rsm and adaptive neuro fuzzy inference system anfis genetic algorithm ga |
| topic | Response surface methodology Adaptive neuro fuzzy inference system Transesterification Genetic algorithm Jatropha seed oil |
| url | http://www.sciencedirect.com/science/article/pii/S2949839223000500 |
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