Guest Editors (Names, emails, affiliations, phones, links)
Leading Guest Editor:
Dr. John Adinya Odey
Lecturer,
Department of Computer Science,
University of Calabar,
Nigeria.
Email Id: johnodey@unical.edu.ng , John.A.Odey@outlook.com
RESEARCH GATE: https://www.researchgate.net/profile/John-Odey
Co-Guest Editors:
Dr. Victor Eshiet Ekong
Professor,
Department of Computer Science,
University of Uyo,
Nigeria.
Email Id: victoreekong@uniuyo.edu.ng
RESEARCH GATE: https://www.researchgate.net/profile/Victor-Ekong-2
Dr. Hydara Mbemba
Lecturer,
Department of Information Technology and Communications,
University of the Gambia,
The Gambia.
Email Id: hmbemba@utg.edu.gm
RESEARCH GATE: https://www.researchgate.net/profile/Mbemba-Hydara
AIMS AND SCOPE or INTRODUCTION
The recent increasing adoption of renewable energy sources has highlighted the importance of developing advanced electrochemical energy storage systems to ensure the stability of the energy grid and efficiency for its performance. The development of these systems is based on batteries and supercapacitors, which have the ability to provide fast power delivery, power density and long-term energy reliability. The application of embedded power management solutions is essential in the optimization of safe and efficient operation of these systems, charging and discharging cycles, voltage and current measurements and modification of operating modes to minimize energy loss. Energy efficiency, thermal stability and system lifespan are directly influenced by the choice of high-performance electrochemical materials, such as next-generation battery chemistries and supercapacitor electrodes. The energy can be controlled effectively through low-power embedded design and adaptive control strategies which minimize parasitic losses and improves the overall performance of storage systems. This smart management can extend the longevity of the device, as well as provide the sustainability and reliability of operation, which is critical to materials-oriented research and practice in modern energy storage.
Furthermore, a unified coordination of the power grid with the sources of energy and storage units is necessary when integrating these storage systems. Embedded power management allows monitoring energy streams in real-time, adjusting the supply and demand accordingly and anticipating control over the use of the storage to ensure grid stability. Moreover, Artificial Intelligence (AI) enhanced algorithms can be used to optimize battery and supercapacitor-based energy dispatch and enhance efficiency and responsiveness to changing renewable inputs. These systems have better energy density, lower thermal stress and reliable integration with current grids by integrating high-performance electrochemical materials with energy-efficient embedded control and intelligent system-level optimization. This interplay of materials development, smart power and control is a significant milestone towards next generation energy storage systems that are sustainable, high performance and entirely grid compatible.
Despite the huge potential of energy-efficient embedded power management in advanced battery and supercapacitor systems, many challenges need to be addressed for reliable grid integration and sustainable energy storage. The aim of this research is to investigate recent progress and disseminate advanced research on low-power embedded control, high-performance electrochemical materials and AI-assisted energy dispatch for batteries and supercapacitors, which will enable efficient coordination with the power grid. The aim of this research includes advanced architectures, system optimization, adaptive control strategies and performance models for next-generation grid-compatible energy storage systems.
LIST OF TOPICS:
- Adaptive Embedded Control Techniques for Low-Power Electrochemical Storage Devices
- Intelligent Energy Dispatch Algorithms for Renewable-Integrated Supercapacitor Networks
- High-Performance Electrochemical Materials for Next-Generation Energy Storage Systems
- Dynamic Voltage and Power Optimization in Embedded Controllers for Grid Storage
- Low-Power Embedded Circuit Designs for Advanced Hybrid Energy Storage Units
- Energy Harvesting and Adaptive Power Management for Grid-Connected Storage Systems
- Smart Scheduling and Load Balancing in Embedded-Controlled Battery-Supercapacitor Networks
- Next-Generation Battery Chemistries and Embedded Algorithms for Efficient Grid Operation
- System-Level Optimization Techniques for Embedded Energy Storage Controllers
- Hybrid Energy Storage Solutions Using AI-Based Predictive Power Management
- Multi-Source Renewable Energy Coordination with Intelligent Storage Management
- Integration of Embedded Low-Power Control and Materials Innovation for Smart Grids
- Sustainable and High-Performance Energy Storage Through Intelligent Embedded Architectures
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: John.A.Odey@outlook.com
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: 08.2026
- First round of reviews completed: 10.2026
- Revised manuscripts due: 12.2026
- Final manuscripts due: 02.2027