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Teslim Olayiwola
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A review on clay chemistry, characterization and shale inhibitors for water-based drilling fluids
NS Muhammed, T Olayiwola, S Elkatatny
Journal of Petroleum Science and Engineering 206, 109043, 2021
1072021
Insights into the application of surfactants and nanomaterials as shale inhibitors for water-based drilling fluid: A review
NS Muhammed, T Olayiwola, S Elkatatny, B Haq, S Patil
Journal of Natural Gas Science and Engineering 92, 103987, 2021
712021
Data-driven model for ternary-blend concrete compressive strength prediction using machine learning approach
BA Salami, T Olayiwola, TA Oyehan, IA Raji
Construction and Building Materials 301, 124152, 2021
662021
Application of Artificial Intelligence-based predictive methods in Ionic liquid studies: A review
F Yusuf, T Olayiwola, C Afagwu
Fluid Phase Equilibria 531, 112898, 2021
662021
Carbon dioxide sequestration in underground formations: review of experimental, modeling, and field studies
S Kalam, T Olayiwola, MM Al-Rubaii, BI Amaechi, MS Jamal, ...
Journal of Petroleum Exploration and Production 11, 303-325, 2021
632021
A data-driven approach to predict compressional and shear wave velocities in reservoir rocks
T Olayiwola, OA Sanuade
Petroleum 7 (2), 199-208, 2021
282021
A review of pressure transient analysis in reservoirs with natural fractures, vugs and/or caves
I Mohammed, TO Olayiwola, M Alkathim, AA Awotunde, SF Alafnan
Petroleum Science 18, 154-172, 2021
202021
Evolving strategies for shear wave velocity estimation: smart and ensemble modeling approach
T Olayiwola, Z Tariq, A Abdulraheem, M Mahmoud
Neural Computing and Applications 33 (24), 17147-17159, 2021
182021
Molecular simulation of kerogen-water interaction: Theoretical insights into maturity
LO Lawal, T Olayiwola, S Abdel-Azeim, M Mahmoud, AO Onawole, ...
Journal of Molecular Liquids 299, 112224, 2020
182020
Modeling the acentric factor of binary and ternary mixtures of ionic liquids using advanced intelligent systems
T Olayiwola, O Ogolo, F Yusuf
Fluid Phase Equilibria 516, 112587, 2020
142020
Determining ion activity coefficients in ion-exchange membranes with machine learning and molecular dynamics simulations
HK Gallage Dona, T Olayiwola, LA Briceno-Mena, CG Arges, R Kumar, ...
Industrial & Engineering Chemistry Research 62 (24), 9533-9548, 2023
112023
Surfactant-Specific AI-Driven Molecular Design: Integrating Generative Models, Predictive Modeling, and Reinforcement Learning for Tailored Surfactant Synthesis
M Nnadili, AN Okafor, T Olayiwola, D Akinpelu, R Kumar, JA Romagnoli
Industrial & Engineering Chemistry Research 63 (14), 6313-6324, 2024
62024
A data-driven approach to predict compressional and shear wave velocities in reservoir rocks. Petroleum 7 (2), 199–208
T Olayiwola, OA Sanuade
62021
Application of artificial neural network to estimate permeability from nuclear magnetic resonance log
T Olayiwola
SPE Annual Technical Conference and Exhibition?, D023S099R012, 2017
62017
Empowering capacitive devices: harnessing transfer learning for enhanced data-driven optimization
T Olayiwola, R Kumar, JA Romagnoli
Industrial & Engineering Chemistry Research 63 (27), 11971-11981, 2024
42024
Graph-Based Modeling and Molecular Dynamics for Ion Activity Coefficient Prediction in Polymeric Ion-Exchange Membranes
P Naghshnejad, G Theis Marchan, T Olayiwola, R Kumar, JA Romagnoli
Industrial & Engineering Chemistry Research 64 (1), 599-612, 2024
12024
Synergizing data-driven and knowledge-based hybrid models for ionic separations
T Olayiwola, LA Briceno-Mena, CG Arges, JA Romagnoli
ACS ES&T Engineering 4 (12), 3032-3044, 2024
12024
Feature Embedding of Molecular Dynamics-Based Descriptors for Modeling Electrochemical Separation Processes
HKG Dona, T Olayiwola, LA Briceno-Mena, CG Arges, R Kumar, ...
Computer Aided Chemical Engineering 52, 1451-1456, 2023
12023
A New Mathematical Workflow to Predict Permeability Variation using Flowing Gas Material Balance
B Haq, DA Al Shehri, I Mohammed, T Olayiwola, NS Muhammed, Z Hasan
Offshore Technology Conference Asia, D012S001R080, 2020
12020
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Y Zimmermann, A Bazgir, Z Afzal, F Agbere, Q Ai, N Alampara, ...
arXiv preprint arXiv:2411.15221, 2024
2024
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