Guest Editors (Names, emails, affiliations, phones, links)
Dr. Rabiu Aliyu Abdulkadir (MGE)
Department of Mechatronics,
Aliko Dangote University of Science and Technology, Kano, Nigeria
Center for Cyber Security,
Faculty of Information Science and Technology, UKM, BANGI, Malaysia
Email: dr.rabialiyu@gmail.com; raabdulkadir@ukm.edu.my
Research Page: https://scholar.google.com/citations?user=OSV0I5MAAAAJ&hl=en
Profile Page: https://research-nexus.net/author/1000519075/
Dr. Auwalu Saleh Mubarak
Operational Research Centre in Healthcare,
Near East University, Nicosia, Turkey
Department of Electrical Engineering,
Aliko Dangote University of Science and Technology,Kano, Nigeria
Email: auwalusaleh.mubarak@neu.edu.tr
Research Page:
https://scholar.google.com/citations?user=WJrEH5cAAAAJ&hl=en
IEEE Page: https://ieeexplore.ieee.org/author/37088997508
Dr. Sani Isah Abba
Department of Civil Engineering,
Prince Mohammad Bin Fahd University,
Al Khobar, Saudi Arabia
Email: sabba@pmu.edu.sa
Research Page: https://scholar.google.com/citations?user=4h2JX7YAAAAJ&hl=en
IEEE Page: https://ieeexplore.ieee.org/author/37086995513
AIMS AND SCOPE or INTRODUCTION
The global transition toward sustainable energy systems has intensified the demand for advanced electrochemical technologies, including batteries, fuel cells, supercapacitors, and hydrogen-based systems. Central to these innovations is the development of novel materials with enhanced efficiency, stability, and scalability. Recent advances in electrochemical materials science, coupled with growing energy needs, highlight the importance of interdisciplinary approaches that integrate material design with system-level optimization.
Artificial intelligence, machine learning, and data-driven modeling are increasingly transforming the way electrochemical materials and systems are designed, characterized, and optimized. These techniques enable accelerated discovery of high-performance materials, predictive analysis of electrochemical behavior, and intelligent control of energy systems. By bridging computational intelligence with experimental and applied electrochemistry, new pathways are emerging for improving system durability, reducing costs, and enhancing overall performance.
This special issue aims to bring together cutting-edge research on the development and application of new materials for electrochemical systems, with a particular emphasis on AI-driven methodologies. Contributions are invited that address both fundamental and applied aspects, including material synthesis, characterization, system integration, and commercialization. The issue seeks to foster collaboration between researchers in materials science, electrochemistry, and computational intelligence to advance next-generation energy solutions.
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LIST OF TOPICS:
• AI-driven design and optimization of battery and supercapacitor materials • Advanced materials for fuel cells and biofuel cells • Hydrogen production, storage, and electrochemical conversion technologies • Machine learning for electrochemical material characterization and performance prediction • Electrochemical nanotechnology and functional materials • Sensors and biosensors for electrochemical applications • Photoelectrochemical systems and solar fuel generation • Materials durability, degradation analysis, and lifecycle assessment • Integration of electrochemical systems with renewable energy sources • Data-driven modeling and simulation of electrochemical processes • Smart control and optimization of electrochemical energy systems • Techno-economic analysis and commercialization of electrochemical technologies
INSTRUCTIONS TO AUTHORS ARE AT: Journal homepage: https://www.newmaterials.ca/instructions-for-authors/
COMMUNICATIONS AND SEND THE MANUSCRIPTS TO: Managing guest editor emails address: raabdulkadir@ukm.edu.my Or download the manuscript at: https://www.newmaterials.ca/submit-your-article/ by indicating the title of the Special issue. The submitted manuscripts should not have been previously published, nor should they be currently under consideration for publication elsewhere.
IMPORTANT DATES: • Manuscript submissions due: 20.09.2026 • First round of reviews completed: 20.11.2026 • Revised manuscripts due: 25.01.2027 • Final manuscripts due: 30.03.2027
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