Computational intelligence approaches for hydrogen storage material design Abdulhalim Musa Abubakar, Mahlon Kida Marvin Canadian Journal of Chemical Engineering, 2026 Hydrogen is increasingly recognized as a clean energy carrier in the transition toward low‐carbon and sustainable energy systems. However, the development of safe, efficient, and cost‐effective hydrogen storage technologies remains a major barrier to its large‐scale deployment. This paper presents a review of how advanced computational intelligence encompassing machine learning (ML), deep learning (DL), high‐throughput screening, and multi‐scale modelling is transforming the discovery, design, and optimization of hydrogen storage materials. The integration of graph neural networks (GNNs), inverse material design, and Bayesian optimization is enabling accelerated screening and performance prediction across diverse material classes such as metal hydrides, complex hydrides, porous frameworks, and carbon nanostructures. Materials informatics platforms and autonomous discovery pipelines, including self‐driving laboratories and active learning workflows, are further streamlining the experimental validation of computationally designed materials. In addition, the application of quantum ML and multi‐fidelity modelling is improving accuracy while reducing simulation costs. Through a series of case study reviews, this paper demonstrates the critical role of these tools in enhancing thermodynamic tuning, adsorption capacity, and kinetic response in next‐generation hydrogen storage systems. This review study highlight that computational intelligence is central to the hydrogen materials innovation cycle.
Non-Newtonian Fluids in Environmental Engineering Abdulhalim Musa Abubakar, Suleiman A. Wali, Abubakar Mohammed, Vivek Kumar Pandey Non Newtonian Fluids for Industrial Applications Modeling and Simulations, 2026 Non-Newtonian fluids play a supportive role in various environmental engineering applications, due to the fact that it influences processes such as wastewater treatment, sediment transport, and pollutant dispersion. Understanding the complex flow behavior of the fluids is essential for effective modeling and simulation. In this review, key non-Newtonian fluid characteristics are examined, including shear-thinning, shear-thickening, and viscoelastic behaviors. Various models, such as Bingham plastic and power-law models, are discussed for their applicability in environmental contexts. Case studies illustrate the impact of non-Newtonian behavior on sediment transport in rivers and estuaries, and emphasizes how rheological properties affect sediment deposition and erosion processes. For that reason, the study explores the role of non-Newtonian fluids in biofilm development and the implications for nutrient and pollutant removal in wastewater treatment facilities. Advanced simulation techniques, including computational fluid dynamics (CFD), are highlighted for their ability to capture the intricacies of flow in complex environmental systems. Moreover, challenges in measuring non-Newtonian properties and the influence of environmental factors are addressed, which provided insights into improving predictive models. As environmental engineering increasingly seeks sustainable solutions, understanding non-Newtonian fluid dynamics becomes essential for optimizing processes and enhancing the performance of engineered systems. Chapter 15 thus serves as a comprehensive resource for researchers and practitioners aiming to leverage the unique properties of non-Newtonian fluids to address contemporary environmental challenges.
Case Studies of Artificial Intelligence in Industrial Fluid and Thermal Processes Abdulhalim Musa Abubakar, Kiran Batool, Muhammad Asif, Baudilio Coto Artificial Intelligence and Computational Modeling in Heat Transfer and Fluid Dynamics, 2026 This review discusses the application of artificial intelligence (AI) in industrial fluid flow and heat transfer operations. It provides a critical overview of case studies demonstrating the effectiveness of AI-based applications. Ab initio , the scope is set, and it is on various industrial applications such as chemical processing, power generation, and manufacturing, where fluid dynamics and heat transfer are significant. The overarching goal is to harness AI to automate processes, lower energy consumption, improve system efficiency, and predict maintenance needs, thereby reducing operational costs and promoting sustainability. Machine learning (ML), neural networks (NN), and predictive modeling are the AI approaches employed. These methods are utilized in conjunction with computational fluid dynamics (CFD) simulations as well as online data analysis to gain a better understanding of process control and decision making. To a greater extent, the review is focused on specific industrial case studies where AI has been utilized efficiently, such as heat exchanger optimization, improvement in reactor fluid mixing, and electronic component thermal management. All case studies are analyzed on the grounds of problem definition, the development of the AI model, and evaluation. Key findings from the case studies that were conducted were that AI could potentially increase prediction accuracy for heat transfer and fluid flow, and could lead to better process optimization and planning of resources. Issues associated with quality data demand and integrating AI with existing installed industrial systems were noted, and recommendations were provided on how to work around these drawbacks.
Removal of heavy metals, phenol, azo, and non-azo dyes from industrial effluents Abdulhalim Musa Abubakar, Irnis Azura Zakarya, Kishan Chand Mukwana, Ahmed Abdo Data Driven Environmental Intelligence, 2026 Industrial effluents often contain a complex mix of toxic contaminants that pose significant risks to ecosystems and human health. This study explores advanced methods for the efficient removal of heavy metals, azo, non-azo dyes, and phenolic pollutants from industrial wastewater, in addition to emphasizing the integration of data analytics and machine learning to optimize treatment processes. It begins by detailing the characteristics and environmental impact of heavy metals and various dyes in industrial wastewater. It then discusses the conventional and emerging technologies used for their removal, including adsorption, coagulation-flocculation, membrane filtration, and advanced oxidation processes. Special attention is given to the role of data-driven techniques in enhancing the effectiveness of several methods, such as predictive modeling for process optimization and real-time monitoring systems. Case studies are provided to illustrate successful applications of data-driven strategies in industrial wastewater treatment, also highlighting improvements in efficiency, cost-effectiveness, and environmental compliance. Challenges in achieving an effective separation of contaminants from industrial effluents are currently a setback. Thus, the critical role of data-driven approaches in advancing industrial effluent treatment technologies, ultimately contributing to safer and more sustainable environmental practices, is demonstrated. We recommend the inclusion of intelligent systems for continuous monitoring and adaptive control in future practical works.
Utilization of Industrial Wastes to Strengthen Bio-Based Composites/Biocomposites Abdulhalim Musa Abubakar, Mohd Hakimi, Atef Chibani, Ayankoya Yemi Ayankunle, Muhammad Adeel, Sergij Vambol Sustainable Utilization of Industrial Wastes as Reinforcement in Composite Materials, 2026 Industrial wastes offer a promising avenue for enhancing the mechanical properties and sustainability of bio-based composites. This chapter explores the integration of various industrial by-products, such as fly ash, slag, agricultural residues, and waste plastics, as reinforcement materials in biocomposites. Combining these waste materials with biopolymers results in composites that not only exhibit improved strength, durability, and thermal stability but also provide an eco-friendly alternative to traditional composites. Emphasizing the dual benefit of waste minimization and material enhancement, the review highlights innovative methods of incorporating industrial wastes into bio-based matrices. Advanced processing techniques, such as extrusion, injection molding, and additive manufacturing, enable the efficient blending of waste materials with biopolymers, ensuring compatibility and uniform dispersion of reinforcement particles. Sustainable utilization of industrial waste reinforces the shift toward circular economy models, reducing dependency on virgin raw materials while promoting waste valorization. Case studies on specific waste-biocomposite combinations demonstrate their potential applications in automotive, construction, and packaging industries, where both mechanical performance and environmental considerations are critical. Challenges related to the compatibility of waste materials with biopolymer matrices, standardization, and performance testing are also discussed. Thus, addressing these challenges is key to unlocking the full potential of industrial waste-reinforced biocomposites. With continued research and innovation, waste-reinforced biocomposites could play a vital role in driving sustainable material development and reducing the environmental impact of industrial waste disposal.
Fuzzy Multi-Criteria Decision-Making Models for Strengthening University–Government– Industry Collaboration in AI Development Ajoy Kanti Das, Nandini Gupta, Abdulhalim Musa Abubakar, Ebenezer Aquisman Asare, Rajat Das, Mithun Datta, Nageswara Rao Lakkimsetty, Ilyas Khan Applied Triple Helix University Government Industry Models for AI Innovation, 2026 This chapter describes how fuzzy multi-criteria decision-making (MCDM) might enhance collaboration between government, business, and academic institutions. It demonstrates why cooperation in AI development entails ambiguity and conflicting viewpoints. Vague judgments are transformed into usable values with the use of fuzzy sets and triangular fuzzy numbers. Fuzzy numbers are used to assess various factors, including research strength, finance, policy flexibility, technology preparedness, and social impact. The shifting significance of each criterion for various partners is displayed by fuzzy weights. All viewpoints are combined into a single meaningful score using aggregation and defuzzification techniques. Fuzzy soft sets highlight areas of agreement and aid in identifying areas of disagreements between partners. Partners can select AI laboratories, internships, and ethical committees, as demonstrated by several cases. The chapter demonstrates how fuzzy models improve the clarity and fairness of collaborative judgments in AI development.
Biogas Production from Sargassum Collected from a Coast of the Gulf of Mexico Using Ruminal Fluid as Inoculum Jorge E. Álvarez-Ley, Luis A. Landero-Godoy, Abdulhalim Musa Abubakar, Ali Bassam, Germán Giácoman-Vallejos, Liliana San-Pedro Energies, 2025 The massive arrival of pelagic sargassum on the Gulf of Mexico coast has become an environmental and socioeconomic challenge, generating high management costs and affecting tourism, fisheries, and coastal ecosystems. In this context, its valorization through anaerobic digestion represents a sustainable alternative for renewable energy production. This study assessed its valorization through anaerobic digestion as a renewable energy route. Pelagic sargassum (Sargassum natans/Sargassum fluitans) was collected, mechanically pretreated, and digested in batch mode using ruminal fluid as inoculum. Two inoculum:substrate ratios (2:1 and 3:1, v/v) were operated for 7 days, and daily cumulative biogas production was recorded. The 3:1 ratio reached 10.6 mL of cumulative biogas, approximately twice the 5.0 mL obtained at 2:1, and its production curve did not plateau by day 7, suggesting ongoing activity. Elemental analysis of the sargassum showed a low C/N ratio (6.9:1) and high moisture (~95%), both of which constrain performance. Boyle’s model was used to estimate theoretical CH4 and CO2 yields and as expected, largely overpredicted the experimental volumes because it assumes ideal conversion. These results indicate that ruminal fluid enhances early-stage biogas formation but also highlight process limitations associated with biomass quality and short retention time. Future work should include extended digestion, co-digestion strategies to adjust the C/N ratio, and full monitoring of pH, soluble COD, VFAs, and volatile solids consumption.
Potential breakthroughs in environmental monitoring and management Abdulhalim Musa Abubakar, Irnis Azura Zakarya, Mohammad Hasnain, Zakiyyu Muhammad Sarkinbaka, Kishan Chand Mukwana, Ahmed Abdo Harnessing AI in Geospatial Technology for Environmental Monitoring and Management, 2024
Engineering non-noble bifunctional catalysts for alkaline hydrogen and oxygen evolution B Lawan, LB Umdagas, AM Abubakar, HM Shettima Discover Chemistry 3 (1), 289 , 2026 2026
Microplastics in Water Management AM Abubakar Microplastics and Nanoplastics: Environmental Risks, Impact Assessment, and … , 2026 2026
Non‐Newtonian Fluids in Environmental Engineering AM Abubakar, SA Wali, A Mohammed, VK Pandey Non‐Newtonian Fluids for Industrial Applications: Modeling and Simulations … , 2026 2026 Citations: 1
Case Studies of Artificial Intelligence in Industrial Fluid and Thermal Processes AM Abubakar, K Batool, M Asif, B Coto Artificial Intelligence and Computational Modeling in Heat Transfer and … , 2026 2026
Removal of heavy metals, phenol, azo, and non-azo dyes from industrial effluents AM Abubakar, IA Zakarya, KC Mukwana, A Abdo Data-Driven Environmental Intelligence, 113-145 , 2026 2026
Advancements in LiDAR technology for precision water resource management AM Abubakar, S Hussain, SR Kafle, AY Waziri, AA Mustapha, EC Nneka Elsevier , 2026 2026
Microbial Fermentation Strategy for Converting Organic Waste to Value-Added Product AM Abubakar, H Mamoudou, R Shamsuddin, SR Kafle Advances in Organic Waste Conversion Through Industrial Biotechnology, 443-467 , 2026 2026 Citations: 1
Computational intelligence approaches for hydrogen storage material design AM Abubakar, MK Marvin The Canadian Journal of Chemical Engineering , 2026 2026
Sustainable bioproduct processing via microwave-assisted green extraction AM Abubakar, M Laghari, AY Waziri, N Elboughdiri, E Schieferstein Applications in Microwave Processing, 79-119 , 2026 2026
Fuzzy Multi-Criteria Decision-Making Models for Strengthening University–Government–Industry Collaboration in AI Development AK Das, N Gupta, AM Abubakar, EA Asare, R Das, M Datta, ... Applied Triple Helix (University-Government-Industry) Models for AI … , 2026 2026
Ajoy Kanti Das N Gupta, AM Abubakar, EA Asare, M Datta, NR Lakkimsetty, I Khan 2026
Leveraging adaptive artificial intelligence and sensor fusion for enhanced process optimization and monitoring in chemical engineering AM Abubakar, I Ferhoune, S Ndaba, MT Bilal, AZ Abdul Adaptive AI in Sensor Informatics, 77-132 , 2026 2026
Life cycle assessment of wastewater treatment options for small towns and communities AM Abubakar, MA Abubakar, SI Okoye, MJ Aliyu Water Remediation Methods and Wastewater Treatment, 465-500 , 2026 2026
Metabolic engineering for biohydrogen production AM Abubakar, Z Nayem, EA Idama, AB Ngulde, M Laghari, B Coto, ... Next Generation Renewable Thermal Energy Harvesting, Conversion and Storage … , 2026 2026
EFFECTS OF CYATHUS STERCOREUS-TREATED BALANITE AEGYTIACA SEED MEAL ON HAEMATOLOGICAL INDICES AND SERUM BIOCHEMICAL PARAMETERS OF SAHELIAN BUCKS A Maidala, A Lawan, D Mohammed, U Abdullahi, A Abubakar BW Academic Journal 2 , 2025 2025
Radiative Heat Transfer in Nanofluids AM Abubakar, I Ferhoune, EM Mansour, WC Ulakpa Nanofluid Heat Transfer, 319-373 , 2025 2025
Green Thermodynamics for Biofuel Synthesis using Bambara Nutshell Catalyst: Toward Sustainable Energy Solutions AM Abubakar, S Vambol, R Shamsuddin, M AlHedrewy, J Yakubu Innovative Energy Systems and Technologies 1 (2), 12-27 , 2025 2025
Numerical analysis of polyethylene glycol 1500 integrated with AlSi10Mg foam for electronic component cooling: Combined effects of pore size, porosity and heating orientation … MAN Haddad, A Chibani, C Boucetta, FL Rashid, AM Abubakar, ... International Communications in Heat and Mass Transfer 169, 109659 , 2025 2025 Citations: 1
Modeling Anaerobic Decomposition: JMP Application with Biomass Data AM Abubakar, N Elboughdiri, A Chibani, EC Nneka, MU Yunus, ... Portugaliae Electrochimica Acta 43 (6), 377-394 , 2025 2025 Citations: 1
Biogas Production from Sargassum Collected from a Coast of the Gulf of Mexico Using Ruminal Fluid as Inoculum JE Álvarez-Ley, LA Landero-Godoy, AM Abubakar, A Bassam, ... Energies 18 (23), 6232 , 2025 2025 Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
Control for hydrogen recovery in pressuring swing adsorption system modeling AI Zannah, S Rachakonda, AM Abubakar, S Devkota, EC Nneka FMDB Transactions on Sustainable Energy Sequence 1 (1), 1-10 , 2023 2023 Citations: 51
Biodigester and feedstock type: Characteristic, selection, and global biogas production AM Abubakar J. Eng. Res. Sci 1 (3), 170-187 , 2022 2022 Citations: 35
Biosorption as technique for remediation of heavy metals from wastewater using microbial biosorbent Y Luka, BK Highina, A Zubairu, AJ Adeleke, M Hamadou, YA Musti, ... Biological Sciences 4 (1), 564-574 , 2024 2024 Citations: 31
An overview on deep leaning application of big data R Abada, AM Abubakar, MT Bilal Mesopotamian Journal of Big Data 2022, 31-35 , 2022 2022 Citations: 28
Bioactive peptides derived from the enzymatic hydrolysis of cowhide collagen for the potential treatment of atherosclerosis: a computational approach H Mamoudou, B Başaran, MAM Mune, AM Abubakar, JO Nandwa, ... Intelligent Pharmacy 2 (4), 456-466 , 2024 2024 Citations: 23
An elaborate breakdown of the essentials of biogas production AM Abubakar, K Silas, MM Aji Journal of Engineering Research and Sciences 1 (4), 93-118 , 2022 2022 Citations: 23
Ways of thinking 3D geometry: exploratory case study in junior high school students S Sudirman, CA Rodríguez-Nieto, ZB Dhlamini, AS Chauhan, U Baltaeva, ... Polyhedron International Journal in Mathematics Education 1 (1), 15-34 , 2023 2023 Citations: 20
Artificial intelligence applications in engineering: a focus on software development and beyond AM Abubakar Doupe Journal of Top Trending Technologies 1 (1) , 2025 2025 Citations: 19
Estimation of biogas potential of liquid manure from kinetic models at different temperatures AM Abubakar, LB Umdagas, AY Waziri, E Irene Int J Sci Res Comp Sci Eng 10 (2) , 2022 2022 Citations: 19
Analysis of microbial growth models for microorganisms in chicken manure digester AM Abubakar, Z Soltanifar, Y Luka, EW Udoh, M Hamadou International Journal of Research In Science & Engineering 12, 1-24 , 2021 2021 Citations: 18
Refinery off-gas as feed to a hydrogen production facility: performance lifting of the steam reforming technique AI Zannah, I Ferhoune, AM Abubakar, AM Al-Khudafi, AA Bitrus, ... Archives of Advanced Engineering Science 2 (1), 53-63 , 2024 2024 Citations: 17
Neural network based performance evaluation of a waterflooded oil reservoir MM Kida, ZM Sarkinbaka, AM Abubakar, AZ Abdul International Journal of Recent Engineering Science-IJRES 8 , 2021 2021 Citations: 14
Review on municipal solid waste, challenges and management policy in Pakistan M Asif, M Laghari, AM Abubakar, SK Suri, A Wakeel, M Siddique Portugaliae Electrochimica Acta 43 (4), 249-258 , 2025 2025 Citations: 10
Medium chain carboxylate production from cassava wastes pretreated by ensiling J Undiandeye, S Kiman, AM Abubakar, SO Dahunsi Biofuels, Bioproducts and Biorefining 17 (4), 933-943 , 2023 2023 Citations: 10
Reporting biogas data from various feedstock AM Abubakar, MU Yunus International Journal of Formal Sciences: Current and Future Research Trends … , 2021 2021 Citations: 10
Biogas production from chicken manure: Characterization and kinetic models AMA Abubakar, KS Silas, MMA Aji, UHT Taura, JU Undiandeye Bayero Journal of Engineering and Technology 17 (3), 1-13 , 2022 2022 Citations: 9
Potential breakthroughs in environmental monitoring and management AM Abubakar, IA Zakarya, M Hasnain, ZM Sarkinbaka, KC Mukwana, ... Harnessing AI in Geospatial Technology for Environmental Monitoring and … , 2025 2025 Citations: 8
Soil Washing to Eliminate Polycyclic Aromatic Hydrocarbons from Petroleum Contaminated Soil-Temperature Effect D Muhammad, BG Mustafa, AM Abubakar, AI Jellah, AM Al-Khudafi, ... Journal of Innovative Research 1 (3), 1-13 , 2023 2023 Citations: 8
Optimized production of high purity sulphuric acid via contact process T Mperiju, T Sylvain, MN Arowo, T Dhanda, AM Abubakar, BA Goriya, ... Logist. Oper. Manag. Res 2 (1), 1-13 , 2023 2023 Citations: 8
Molecular underpinning of plants hormonal signaling to abiotic stressors using plant chemical and synthetic biology approaches GK Pandit, AM Abubakar, H Mamoudou, M Tariq, M Abdulrazak, SA Wali, ... Role of Antioxidants in Abiotic Stress Management, 383-393 , 2025 2025 Citations: 7
