OLAOSEBIKAN ABIDOYE OLAFADEHAN

@unilag.edu.ng

Professor/Department of Chemical and Petroleum Engineering
University of Lagos, Lagos, Nigeria

OLAOSEBIKAN ABIDOYE OLAFADEHAN


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https://researchid.co/johnblakey

RESEARCH INTERESTS

Modelling and Simulation of Chemical and Biochemical Reaction Systems, Computational Fluid Dynamics, Adsorption, Separation Processes, Environmental Engineering and Optimization studies.
26

Scopus Publications

804

Scholar Citations

16

Scholar h-index

23

Scholar i10-index

Scopus Publications

  • Integration of Machine Learning and Feature Analysis for the Optimization of Enhanced Oil Recovery and Carbon Sequestration in Oil Reservoirs
    Bukola Mepaiyeda, Michal Ezeh, Olaosebikan Olafadehan, Awwal Oladipupo, Opeyemi Adebayo, Etinosa Osaro
    Chemengineering, 2026
    The dual imperative of mitigating carbon emissions and maximizing hydrocarbon recovery has amplified global interest in carbon capture, utilization, and storage (CCUS) technologies. These integrated processes hold significant promise for achieving net-zero targets while extending the productive life of mature oil reservoirs. However, their effectiveness hinges on a nuanced understanding of the complex interactions between geological formations, reservoir characteristics, and injection strategies. In this study, a comprehensive machine learning-based framework is presented for estimating CO2 storage capacity and enhanced oil recovery (EOR) performance simultaneously in subsurface reservoirs. The methodology combines simulation-driven uncertainty quantification with supervised machine learning to develop predictive surrogate models. Simulation results were used to generate a diverse dataset of reservoir and operational parameters, which served as inputs for training and testing three machine learning models: Random Forest, Extreme Gradient Boosting (XGBoost), and Artificial Neural Networks (ANN). The models were trained to predict three key performance indicators (KPIs): cumulative oil production (bbl), oil recovery factor (%), and CO2 sequestration volume (SCF). All three models exhibited exceptional predictive accuracy, achieving coefficients of determination (R2) greater than 0.999 across both training and testing datasets for all KPIs. Specifically, the Random Forest and XGBoost models consistently outperformed the ANN model in terms of generalization, particularly for CO2 sequestration volume predictions. These results underscore the robustness and reliability of machine learning models for evaluating and forecasting the performance of CO2-EOR and sequestration strategies. To enhance model interpretability and support decision-making, SHapley Additive exPlanations (SHAP) analysis was applied. SHAP, grounded in cooperative game theory, offers a model-agnostic approach to feature attribution by assigning an importance value to each input parameter for a given prediction. The SHAP results provided transparent and quantifiable insights into how geological and operational features such as porosity, injection rate, water production rate, pressure, etc., affect key output metrics. Overall, this study demonstrates that integrating machine learning with domain-specific simulation data offers a scalable approach for optimizing CCUS operations. The insights derived from the predictive models and SHAP analysis can inform strategic planning, reduce operational uncertainty, and support more sustainable oilfield development practices.
  • Dynamic Studies of Binary Adsorption System in Fixed Beds using Orthogonal Collocation on Finite Element Method
    O. A. Olafadehan, K. O. Amoo, K. F. K. Oyedeko, A. J. Adesina
    International Journal of Applied and Computational Mathematics, 2024
  • Adsorption of cobalt (II) ions from aqueous solution using cow bone and its derivatives: Kinetics, equilibrium and thermodynamic comparative studies
    Kehinde Olawale Amoo, Temiloluwa Emmanuel Amoo, Olaosebikan Abidoye Olafadehan, Edith Egbimhanlu Alagbe, Ayo Joshua Adesina, Mutiat Oyedolapo Bamigboye, Boyede Dele Olowookere, Kehinde David Ajayi
    Results in Engineering, 2023
    Mono-component adsorption of Co2+ ions from simulated industrial water was investigated by using cow bone (CB), cow bone char (CBC), and activated cow bone carbon (ACBC) adsorbents synthesized from raw cow bone as the precursor. The resulting prepared adsorbent materials were then characterized using analytical methods such as: zeta potential measurements, BET surface area, FTIR, SEM, EDS, and XRD analysis. For all synthesized adsorbents, the main compositions were mesopores with the presence of CC, PO32−, CO32 and O–H bonds signifying hydroxyapatite nature of the adsorbents. The isoelectric point (pHIEP) of ACBC was obtained to be 3.59 (lowest among the prepared adsorbents) thereby signifying that ACBC's electrostatic force of attraction was relatively higher between the Co2+ and its surface. The study showed that the pseudo second-order kinetic model had the best correlation for all the adsorption kinetic experimental data for each prepared adsorbent, inferring that the rate-controlling step during the Co2+ ions adsorption onto the prepared adsorbents is chemisorption. The Sips isotherm model excellently predicted the adsorption data for the adsorption of Co2+ ions on the CB adsorbents while the Langmuir isotherm best fitted the equilibrium data of the CBC, and ACBC prepared adsorbents with excellent correlation coefficients, while maximum adsorption capacities, qmax, were obtained to be 52.50, 58.80, and 64.50 mg g−1 for CB, CBC, and ACBC respectively. The study of the thermodynamic properties of the adsorption of Co2+ showed the process was endothermic, non-spontaneous and endogenic for the ACBC adsorbent, while being exothermic for the CB, and CBC adsorbents in addition to having physisorption properties.
  • Effect of catalyst-to-oil ratio and catalyst temperature on determining the yield of gasoline in the riser reactor
    Olubunmi G. Abatan, Olaosebikan A. Olafadehan, Vincent E. Efeovbokhan, Olagoke Oladokun, Augustine O. Ayeni
    Results in Engineering, 2023
    Increasing the yield of Gasoline has been the desire of every crude oil refining process in the oil industry. The principal unit that has significantly contributed to increasing the yield of Gasoline is the Fluid Catalytic Cracking (FCC) unit. The performance of the FCC unit is dependent on many parameters, substantively the catalyst-to-oil ratio (COR) and the temperature of the catalyst (tcat) when entering the riser reactor. To understand the effect of COR and tcat, a five-lump kinetics model was developed, and the simulated result was further plugged into MINITAB 7.0 software in order to generate a set of empirical equation models. The empirical equation models predicted the optimal yield of gasoline to be 56.83%, with corresponding optimal parameters of COR and temperature of catalyst as 3.35 and 900 K, respectively. The actual yield of gasoline at 3.35 COR and 900 K catalyst temperature was 56.78%, with a 0.09% error compared to the predicted yield of gasoline. The two parameters were varied with the values from previous studies, and the predicted result compared to the actual is 7.8648 root mean square error (RMSE). Therefore, the empirical equation model is reliable in predicting the yield of gasoline with respect to the COR and temperature of catalyst.
  • Production and characterization of composite nanoparticles derived from chitosan, CTAB and bentonite clay
    Olaosebikan Abidoye Olafadehan, Victor Ehigimetor Bello, Kehinde Olawale Amoo
    Chemical Papers, 2022
  • Modeling and Simulation of Partial Oxidation of Methanol to Formaldehyde on FeO/MoO3 Catalyst in a Catalytic Fixed Bed Reactor
    A. O. Olatunde, O. A. Olafadehan, M. Usman
    Iranian Journal of Chemistry and Chemical Engineering, 2021
    A two-dimensional mathematical model was developed for a porous heterogeneous catalytic fixed bed reactor. The model took into account the effect of heat generated by adsorption of reactants on the catalyst surface and heat transfer from the fluid phase to the surroundings which have significant effect on reactor performance especially at reactor hotspot. The developed model predicted the partial oxidation of methanol to formaldehyde on FeO/MoO3 catalyst, a complex reaction system. Excellent agreement was achieved when the resultant simulated results were compared with experimental data in the literature. The proposed model predicted the location of hotspot at a dimensionless distance of 0.4413 (= 0.0309 m) the same as the experiment value but with a temperature of 619 K compared with experimental value of 622 K. The conventional heterogeneous and pseudo-homogeneous models predicted the hotspot temperature to be about 8 K and 34 K lower than the experimental value respectively.
  • Comparative investigation of RSM and ANN for multi-response modeling and optimization studies of derived chitosan from Archachatina marginata shell
    V.E. Bello, O.A. Olafadehan
    Alexandria Engineering Journal, 2021
    The design of this paper was to investigate comparatively the optimization techniques of response surface methodology (RSM) and artificial neural network (ANN) when applied to the conditions for chitosan production from Archachatina marginata shell and the % removal of methylene blue, MB, from synthetic textile wastewater. The proposed RSM and ANN models are optimized using genetic algorithm (GA). The optimum conditions for the extraction processes of chitosan and % removal of MB are determined and the derived chitosan at optimized conditions is characterized using analytical techniques. The ANN portrays better modeling abilities than RSM for the responses. The predicted values of % yield of chitosan, % DD and % removal of MB are obtained as 51.56, 98.68 and 94.71 respectively using the RSM-GA technique while the ANN-GA technique predicted 45.32%, 91.96% and 95.96% respectively. The experimental values of the responses are in excellent agreement with the ANN-GA predicted values with % errors being 1.8, 1.2 and 1.19 respectively. Hence, the conditions of chitosan production from Archachatina marginata shell and its bioremediation capacity of synthetic wastewater from textile industry can be adequately and accurately optimized and modeled using ANN-GA for routine seafood applications and treatment of industrial wastewater effluents.
  • Optimum Conditions for Extraction of Chitin and Chitosan from Callinectes amnicola Shell Waste
    O. A. Olafadehan, T. O. Ajayi, K. O. Amoo
    Theoretical Foundations of Chemical Engineering, 2020
    The optimization of process variables for the extraction of chitin and chitosan from crab (Callinectes amnicola) shell waste and for the degree of deacetylation (DDA) of extracted chitosan was investigated using response surface methodology (RSM). The respective effects of four and three process parameters on the extraction yields of chitin and chitosan and on the DDA of chitosan were examined. The optimized chitin extraction conditions based on the yield (4.84 g or 19.36%) were obtained to be 3.25 M HCl solution, 18.55 h demineralization time, 2.39 M NaOH solution and 2 h deproteinization time, while the maximum chitosan yield (5.98 g or 13.29%) was obtained at modelled optimized conditions of 50% w/w NaOH solution, 85.05°C deacetylation temperature, and 133.64 min deacetylation time. The modelled optimization conditions for the highest DDA of chitosan produced from crab shell waste were 50% w/w NaOH solution, 84.46°C deacetylation temperature, and 187 min deacetylation time, with the corresponding predicted DDA of 84.20%. Excellent agreement was obtained between experimental DDA of chitosan (84.50%) and the predicted value, with the percentage error being ±0.36. Independent predicted robust quadratic models for predicting the yields of chitin and chitosan extraction and the DDA of chitosan from the crab shell waste were obtained, validated and verified.
  • Data on artificial neural network and response surface methodology analysis of biodiesel production
    A.A. Ayoola, F.K. Hymore, C.A. Omonhinmin, P.O. Babalola, E.O. Bolujo, G.A. Adeyemi, R. Babalola, O.A. Olafadehan
    Data in Brief, 2020
    The biodiesel production from waste soybean oil (using NaOH and KOH catalysts independently) was investigated in this study. The use of optimization tools (artificial neural network, ANN, and response surface methodology, RSM) for the modelling of the relationship between biodiesel yield and process parameters was carried out. The variables employed in the experimental design of biodiesel yields were methanol-oil mole ratio (6 - 12), catalyst concentration (0.7 - 1.7 wt/wt%), reaction temperature (48 - 62°C) and reaction time (50 - 90 min). Also, the usefulness of both the RSM and ANN tools in the accurate prediction of the regression models were revealed, with values of R-sq being 0.93 and 0.98 for RSM and ANN respectively.
  • Biodegradation assessment of bacillus subtilis isolated from locust beans on crude oil
    Petroleum and Coal, 2020
  • Mechanistic kinetic models for steam reforming of concentrated crude ethanol on Ni/Al2O3 catalyst
    Journal of Engineering Science and Technology, 2015
  • Refinery products/waste optimization using a synthesized pinch technique
    K. E. Abhulimen, V. O. Adeniyi, O. A. Olafadehan
    Theoretical Foundations of Chemical Engineering, 2012
  • Numerical solution of steady state dispersion flow model for lactose-lactase hydrolysis with different kinetics in fixed bed
    Journal of Engineering Science and Technology, 2010
  • Mechanistic kinetic models for hydrogenolysis of benzothiophene on Co-Mo/-alumina catalyst
    O. A. Olafadehan, E. U. Okinedo
    Petroleum Science and Technology, 2009
  • Mathematical modeling and simulation of steady state plug flow for lactose-lactase hydrolysis in fixed bed
    O. A. Olafadehan, D. S. Aribike, A. M. Adeyemo
    Theoretical Foundations of Chemical Engineering, 2009
  • Mechanistic kinetic models for n-heptane reforming on platinum/alumina catalyst
    O. A. Olafadehan, A. A. Susu, A. Jaiyeola
    Petroleum Science and Technology, 2008
  • Modeling of fixed bed adsorption of phenols on granular activated carbon
    D. S. Aribike, O. A. Olafadehan
    Theoretical Foundations of Chemical Engineering, 2008
  • Kinetic models for hydrogenolysis of thiophene on Co-Mo/γ-alumina catalyst
    O. A. Olafadehan, S. O. Oghenekaro
    Petroleum Science and Technology, 2008
  • Numerical solution of binary liquid-phase adsorption onto porocel clay using linear, Freundlich and Langmuir isotherms
    Olaosebikan A. Olafadehan, Alfred A. Susu
    Adsorption Science and Technology, 2005
  • Computerized solution of the dynamic sorption process for binary system in heterophase medium
    Olaosebikan A. Olafadehan, Alfred A. Susu
    Petroleum Science and Technology, 2005
  • Simultaneous reaction-deactivation kinetics in n-Octane and methylcyclopentane reforming reactions on platinum-containing catalysts
    Chemical Engineering Communications, 2005
  • Modeling and simulation of liquid-phase ternary adsorption in activated carbon column
    Olaosebikan A. Olafadehan, Alfred A. Susu
    Industrial and Engineering Chemistry Research, 2004
  • Modelling and simulation of ternary liquid-phase adsorption onto activated carbon
    Olaosebikan A. Olafadehan, Alfred A. Susu
    Adsorption Science and Technology, 2004
  • Computerized solution of the dynamic sorption process for a binary system in a heterophase medium
    Olaosebikan A. Olafadehan, Alfred A. Susu
    Industrial and Engineering Chemistry Research, 2004
  • Computerized solution of the dynamic sorption process for a ternary system in a heterophase medium
    O. A. Olafadehan, A. A. Susu
    Theoretical Foundations of Chemical Engineering, 2004
  • Computerized solution of the dynamic sorption process for a ternary system in a heterophase medium
    Teoreticheskie Osnovy Khimicheskoi Tekhnologii, 2004

RECENT SCHOLAR PUBLICATIONS

  • Optimisation Studies of Naphthalene Adsorption on Bentonite Clay Impregnated on Chitosan and Surfactant using RSM–CCD, ANN–BP and ANN–PSO Techniques
    OA Olafadehan
    Journal of Engineering Research 31 (1), 111-133 , 2026
    2026
  • Modelling an End-of-Pipe Technology for Processing Petroleum Oily Sludge
    OA Olafadehan, KE Abhulimen, NB Eze, AM Bello, QO Olafadehan
    Journal of Chemical and Petroleum Engineering , 2026
    2026
  • Integration of Machine Learning and Feature Analysis for the Optimization of Enhanced Oil Recovery and Carbon Sequestration in Reservoirs
    B Mepaiyeda, M Ezeh, O Olafadehan, A Oladipupo, O Adebayo, E Osaro
    ChemRxiv 2025 (0826) , 2025
    2025
    Citations: 3
  • Dynamic Studies of Binary Adsorption System in Fixed Beds using Orthogonal Collocation on Finite Element Method
    OA Olafadehan, KO Amoo, KFK Oyedeko, AJ Adesina
    International Journal of Applied and Computational Mathematics 10 (3), 108 , 2024
    2024
    Citations: 1
  • Adsorption of cobalt (II) ions from aqueous solution using cow bone and its derivatives: Kinetics, equilibrium and thermodynamic comparative studies
    KO Amoo, TE Amoo, OA Olafadehan, EE Alagbe, AJ Adesina, ...
    Results in Engineering 20, 101635 , 2023
    2023
    Citations: 25
  • Effect of catalyst-to-oil ratio and catalyst temperature on determining the yield of gasoline in the riser reactor
    OG Abatan, OA Olafadehan, VE Efeovbokhan, O Oladokun, AO Ayeni
    Results in Engineering 19, 101224 , 2023
    2023
    Citations: 3
  • Dynamic studies of binary adsorption system in fixed beds
    OA Olafadehan, KO Amoo, KFK Oyedeko, AJ Adesina
    2023
  • Comparative analysis of machine learning algorithms in predicting rate of penetration during drilling
    OA Olafadehan, ID Ahaotu
    Journal of Petroleum Chemistry and Engineering 1 (1), 32-47 , 2023
    2023
    Citations: 6
  • Production and characterization of composite nanoparticles derived from chitosan, CTAB and bentonite clay
    OA Olafadehan, VE Bello, KO Amoo
    Chemical Papers 76 (8), 5063-5086 , 2022
    2022
    Citations: 10
  • Evaluation of Heterocyclic Aromatic Compound Dye (Methylene Blue) on Chitosan Adsorbent Sourced from African Snail Shell: Modelling and Optimization Studies
    OAO Victor Ehigimetor Bello
    Journal of Applied Science & Process Engineering 9 (1), 1054–1090 , 2022
    2022
    Citations: 4
  • Comparative Studies of RSM, RSM–GA and ANFILS for Modeling and Optimization of Naphthalene Adsorption on Chitosan–CTAB–Sodium Bentonite Clay Matrix
    VEB Olaosebikan Abidoye Olafadehan
    Journal of Applied Science & Process Engineering 9 (2), 1242–1280 , 2022
    2022
    Citations: 2
  • Mechanistic Kinetic Models for Catalytic Alkylation of Toluene with Methanol for Xylene Production
    LSDBAM Olafadehan OA
    Petroleum and Petrochemical Engineering Journal 6 (1), 1–16 , 2022
    2022
  • Binary Adsorption of Phenol and 2-Chlorophenol on Chitosan Derived from Pink Shrimp Shell
    BVEASG Olafadehan O. A., Amoo K. O, Oyedeko K. F. K., Bello A. M.
    Petroleum and Petrochemical Engineering Journal 6 (1), 1–18 , 2022
    2022
    Citations: 4
  • Isotherms, kinetic and thermodynamic studies of methylene blue adsorption on chitosan flakes derived from African giant snail shell
    OA Olafadehan, VE Bello, KO Amoo, AM Bello
    African Journal of Environmental Science and Technology 16 (1), 37-70 , 2022
    2022
    Citations: 20
  • Modeling and simulation of partial oxidation of methanol to formaldehyde on feo/moo3 catalyst in a catalytic fixed bed reactor
    AO Olatunde, OA Olafadehan, MA Usman
    Iranian Journal of Chemistry and Chemical Engineering 40 (6), 1800-1813 , 2021
    2021
    Citations: 7
  • Comparative investigation of RSM and ANN for multi-response modeling and optimization studies of derived chitosan from Archachatina marginata shell
    VE Bello, OA Olafadehan
    Alexandria Engineering Journal 60 (4), 3869-3899 , 2021
    2021
    Citations: 51
  • Kinetic studies of corrosion of mild steel in acidic medium using grewa venusta leaves extract as inhibitor.
    L Salami, OA Olafadehan, RJ Patinvoh, NA Folami
    2021
  • Characterization and Beneficiation of Clays from Ewekoro for use as Drilling Mud
    AO Olatunde, OA Olafadehan, MA Usman, TA Adeosun
    World Scientific News 159, 45-58 , 2021
    2021
    Citations: 3
  • Extraction and characterization of chitin and chitosan from Callinectes amnicola and Penaeus notialis shell wastes
    OA Olafadehan, KO Amoo, TO Ajayi, VE Bello
    Journal of Chemical Engineering and Materials Science 12 (1), 1-30 , 2021
    2021
    Citations: 61
  • Optimum Conditions for Extraction of Chitin and Chitosan from Callinectes amnicola Shell Waste
    OA Olafadehan, TO Ajayi, KO Amoo
    Theoretical Foundations of Chemical Engineering 54 (6), 1173-1194 , 2020
    2020
    Citations: 19

MOST CITED SCHOLAR PUBLICATIONS

  • Improvement of rheological properties of drilling fluid using locally based materials.
    AO Olatunde, MA Usman, OA Olafadehan, TA Adeosun, OE Ufot
    Petroleum & Coal 54 (1) , 2012
    2012
    Citations: 108
  • Treatment of brewery wastewater effluent using activated carbon prepared from coconut shell
    OA Olafadehan, OW Jinadu, L Salami, LT Popoola
    International Journal of Applied Science and Technology 2 (1), 165-178 , 2012
    2012
    Citations: 72
  • Extraction and characterization of chitin and chitosan from Callinectes amnicola and Penaeus notialis shell wastes
    OA Olafadehan, KO Amoo, TO Ajayi, VE Bello
    Journal of Chemical Engineering and Materials Science 12 (1), 1-30 , 2021
    2021
    Citations: 61
  • Characterisation study of solid wastes: a case of Lagos state
    L Salami, AA Susu, RJ Patinvoh, OA Olafadehan
    International Journal of Applied Science and Technology 1 (3) , 2011
    2011
    Citations: 53
  • Comparative investigation of RSM and ANN for multi-response modeling and optimization studies of derived chitosan from Archachatina marginata shell
    VE Bello, OA Olafadehan
    Alexandria Engineering Journal 60 (4), 3869-3899 , 2021
    2021
    Citations: 51
  • Treatment of industrial wastewater effluent
    OA Olafadehan, DS Aribike
    Journal of Nigerian Society of Chemical Engineers 19, 50-53 , 2000
    2000
    Citations: 35
  • Optimization studies of chitin and chitosan production from Penaeus notialis shell waste
    KO Amoo, OA Olafadehan, TO Ajayi
    African Journal of Biotechnology 18 (27), 670-688 , 2019
    2019
    Citations: 31
  • Adsorption of cobalt (II) ions from aqueous solution using cow bone and its derivatives: Kinetics, equilibrium and thermodynamic comparative studies
    KO Amoo, TE Amoo, OA Olafadehan, EE Alagbe, AJ Adesina, ...
    Results in Engineering 20, 101635 , 2023
    2023
    Citations: 25
  • Equilibrium, kinetic and thermodynamic studies of biosorption of zinc ions from industrial wastewater using derived composite biosorbents from walnut shell
    OA Olafadehan
    African Journal of Environmental Science and Technology , 2018
    2018
    Citations: 23
  • Modeling of fixed bed adsorption of phenols on granular activated carbon
    DS Aribike, OA Olafadehan
    Theoretical Foundations of Chemical Engineering 42 (3), 257-263 , 2008
    2008
    Citations: 21
  • Isotherms, kinetic and thermodynamic studies of methylene blue adsorption on chitosan flakes derived from African giant snail shell
    OA Olafadehan, VE Bello, KO Amoo, AM Bello
    African Journal of Environmental Science and Technology 16 (1), 37-70 , 2022
    2022
    Citations: 20
  • Modeling and simulation of liquid-phase ternary adsorption in activated carbon column
    OA Olafadehan, AA Susu
    Industrial & engineering chemistry research 43 (25), 8107-8116 , 2004
    2004
    Citations: 20
  • Optimum Conditions for Extraction of Chitin and Chitosan from Callinectes amnicola Shell Waste
    OA Olafadehan, TO Ajayi, KO Amoo
    Theoretical Foundations of Chemical Engineering 54 (6), 1173-1194 , 2020
    2020
    Citations: 19
  • Mechanistic kinetic models for steam reforming of concentrated crude ethanol on Ni/Al2O3 catalyst
    OA Olafadehan, AA Ayoola, OO Akintunde, VO Adeniyi
    Journal of Engineering Science and Technology 10 (5), 633-653 , 2015
    2015
    Citations: 18
  • Production and characterization of derived composite biosorbents from animal bone
    OA Olafadehan, KE Abhulimen, AI Adeleke, CV Njoku, KO Amoo
    African Journal of Pure and Applied Chemistry 13 (2), 12-26 , 2019
    2019
    Citations: 17
  • Modelling and simulation of an industrial RFCCU-riser reactor for catalytic cracking of vacuum residue
    OA Olafadehan, OP Sunmola, A Jaiyeola, V Efeovbokhan, OG Abatan
    Applied Petrochemical Research 8 (4), 219-237 , 2018
    2018
    Citations: 17
  • Prediction of concentration profiles of contaminants in groundwater polluted by leachates from a landfill site
    L Salami, OA Olafadehan, G Babagana, AA Susu
    Int. J. Res. Rev. App. Sci 15 (3), 365-378 , 2013
    2013
    Citations: 14
  • Modelling and simulation of methanogenic phase of an anaerobic digester
    OA Olafadehan, AT Alabi
    Journal of Engineering Research 13 (2), 1-16 , 2009
    2009
    Citations: 14
  • Mechanistic Kinetic Models for n-Heptane Reforming on Platinum/Alumina Catalyst
    AASAJ O. A. Olafadehan
    Petroleum Science and Technology 26, 1459–1480 , 2008
    2008
    Citations: 13
  • Production and characterization of composite nanoparticles derived from chitosan, CTAB and bentonite clay
    OA Olafadehan, VE Bello, KO Amoo
    Chemical Papers 76 (8), 5063-5086 , 2022
    2022
    Citations: 10