Artificial Neural Network–Guided Optimization of Microwave-Assisted Biodiesel Production Using a Zn–Ce-Loaded Agro-Waste Activated Carbon Bifunctional Catalyst
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Catalyst limits and the intricate, nonlinear interaction of operating parameters make it difficult to produce biodiesel from low-cost, high-free fatty acid feedstocks in an efficient and sustainable manner. By combining artificial intelligence-based process optimization with a bifunctional Zn–Ce-loaded activated carbon catalyst made from agricultural waste, this study seeks to increase the efficiency of biodiesel synthesis. Artificial neural network (ANN) models were developed and assessed using experimental data from 52 runs of the microwave-assisted production of biodiesel from waste cooking oil. The best feedforward neural network was combined with a genetic algorithm (GA) to estimate biodiesel yield and determine ideal operating parameters after a number of ANN topologies were investigated. With a correlation coefficient of roughly 0.996 and a mean square error of roughly 5.7 × 10⁻², the chosen ANN model with three hidden layers showed outstanding prediction ability. With a maximum anticipated biodiesel yield of 98.57%, ANN–GA optimization found ideal parameters of 0.3 weight percent catalyst loading, an oil-to-methanol ratio of 1:7, a reaction duration of 4.3 minutes, and a microwave power of 97.5%. These findings show that coupling ANN-GA optimization with a sustainable bifunctional catalyst offers a precise and economical method for enhancing microwave-assisted biodiesel production, providing a promising route for the effective use of feedstocks obtained from trash.
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References
Knothe G. Biodiesel and Renewable Diesel: A Comparison. Progress in Energy and Combustion Science 2010; 36(3): 364-373.
Leung DY, Wu X, Leung MKH. A Review on Biodiesel Production Using Catalyzed Transesterification. Applied Energy 2010; 87(4): 1083-1095.
Gui MM, Lee KT, Bhatia S. Feasibility of Edible Oil vs. Non-Edible Oil vs. Waste Edible Oil as Biodiesel Feedstock. Energy 2008; 33(11): 1646-1653.
Kang J, Zhang L, Wang H, Liu Y, Chen X, Zhao Q. Vernicia Montana Seed Shell-Derived Solid Acid for Heterogeneous Catalytic Transesterification from Waste Cooking Oil to Biodiesel: An Artificial Neural Network-Guided and Sustainable Approach. Molecular Catalysis 2025; 585: 115349.
Melero JA, Iglesias J, Morales G. Heterogeneous Acid Catalysts for Biodiesel Production: Current Status and Future Challenges. Green Chemistry 2009; 11(9): 1285-1308.
Cordero-Ravelo V, Schallenberg-Rodriguez J. Biodiesel Production as a Solution to Waste Cooking Oil (WCO) Disposal. Will Any Type of WCO Do for a Transesterification Process? A Quality Assessment. Journal of Environmental Management 2018; 228: 117-129.
Xie F, Zhang TA, Dreisinger D, Doyle F. A Critical Review on Solvent Extraction of Rare Earths from Aqueous Solutions. Minerals Engineering 2014; 56: 10-28.
Nargotra P, Sharma V, Bajaj BK. Application of Ionic Liquid and Alkali Pretreatment for Enhancing Saccharification of Sunflower Stalk Biomass for Potential Biofuel-Ethanol Production. Bioresource Technology 2018; 267: 560-568.
Wilcox EG, Levy R, Futrell R, Levy RP. On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior. arXiv Preprint 2020.
Verma S, Gupta S, Bandhiwal N, Kumar T, Bharadwaj C, Bhatia S. High-Density Linkage Map Construction and Mapping of Seed Trait QTLs in Chickpea (Cicer Arietinum L.) Using Genotyping-by-Sequencing (GBS). Scientific Reports 2015; 5(1): 17512.
Palitsakun S, et al., Transesterification of Jatropha Oil to Biodiesel Using SrO Catalysts Modified with CaO from Waste Eggshell. Catalysis Communications 2021; 149: 106233.
Abdulla TA, Osman M, Edgar TF. Neural Network Based Soft Sensor for Pilot-Plant Distillation Column. 2019 Spring Meeting and 15th Global Congress on Process Safety, American Institute of Chemical Engineers (AIChE) 2019.
Gülüm M, Bilgin A. Measurements and Empirical Correlations in Predicting Biodiesel-Diesel Blends’ Viscosity and Density. Fuel 2017; 199: 567-577.
Singh D, Singh B. Investigating the Impact of Data Normalization on Classification Performance. Applied Soft Computing 2020; 97: 105524.
Chakraborty T, Hsu A, Manya D, Sheriff G. Disproportionately Higher Exposure to Urban Heat in Lower-Income Neighborhoods: A Multi-City Perspective. Environmental Research Letters 2019; 14(10): 105003.
Singh J, Singh J. COVID-19 and Its Impact on Society. Electronic Research Journal of Social Sciences and Humanities 2020; 2.
Cavayas YA, Yusuff H, Porter R. Fungal Infections in Adult Patients on Extracorporeal Life Support. Critical Care 2018; 22(1): 98.
Akream NS, Abdullah AC, Al-Qasmi RM, Hamad AF, Saleh MA. High-Yield Activated Carbon Based ZnO-Ce Bifunctional Catalyst for Production of Biodiesel from Waste Cooking Oil. Energy Conversion and Management 2024; 321: 119054.
Baltagi BH, Baltagi BH. A Companion to Theoretical Econometrics. Wiley Online Library 2001.
Abusnina A. Gaussian Process Adaptive Soft Sensors and Their Applications in Inferential Control Systems. University of York 2014.
Webster JG, Eren H. Measurement, Instrumentation, and Sensors Handbook: Two-Volume Set (Electrical Engineering Handbook). CRC Press: Boca Raton, FL, USA 2014.
Demuth HB, Beale MH, De Jesus O, Hagan MT. Neural Network Design. Martin Hagan 2014.
Demuth H, Beale M, Hagan M. Neural Network Toolbox. For Use With MATLAB. The MathWorks Inc 2000; 2000: 415.
Chakraborty R, Sahu H. Intensification of Biodiesel Production from Waste Goat Tallow Using Infrared Radiation: Process Evaluation Through Response Surface Methodology and Artificial Neural Network. Applied Energy 2014; 114: 827-836.
Yusuff AS, Gbadamosi AO, Popoola LT. An Artificial Intelligence Approach to Model and Optimize Biodiesel Production from Used Cooking Oil Using CaO Incorporated Zeolite Catalyst. Energy Conversion and Management: X 2023; 20: 100452.
Arunyanart P, Piyatamrong A, Srichat A, Chollacoop N, Sudaprasert K. The Prediction of Biodiesel Production Yield from Transesterification of Vegetable Oils with Machine Learning. Results in Engineering 2024; 24: 103236.
Arunyanart W, et al. Developmental and Autism Screening: A Survey Across Six States. Infants & Young Children 2012; 25(3): 175-187.
Yusuff AS, Olutoye MA, Akpan UG, Anyanwu EE. Synthesis and Characterization of Coal Fly Ash Supported Zinc Oxide Catalyst for Biodiesel Production Using Used Cooking Oil as Feed. Renewable Energy 2021; 170: 302-314.
Maleki B, Esmaeili H. Upgrading of NiFe2O4 via Decoration of g-C3N4 Nanoparticles to a Magnetic Catalyst for the Ultrasound-Assisted Production of Biodiesel. Scientific Reports 2025.