Guest editors:
Dr. Eseosa Omorogiuwa (MGE)
Institute of Engineering Technology and Innovation
University of Port Harcourt, Nigeria.
Email-ID: eseosa.omorogiuwa@uniport.edu.ng , eseomorogiuw12@yahoo.com
Google Scholar link: https://scholar.google.com/citations?user=mVOelx8AAAAJ&hl=en
Dr. Daniel Aikhuele
Department of Mechanical Engineering, University of Port Harcourt, Nigeria.
Email-ID: daniel.aikhuele@uniport.edu.ng
Google Scholar Link: https://scholar.google.com/citations?hl=en&user=5no2WykAAAAJ
Dr. Khuliso Sigama
Tshwane University of Technology, South Africa.
Email id: Sigamak1@gmail.com
Google scholar Link: https://scholar.google.co.za/citations?user=DYrrF70AAAAJ&hl=en
Prof. Roland Uhunmwangho
University of Port Harcourt, Nigeria.
Email id: roland.uhunmwangho@uniport.edu.ng
Google Scholar Link: https://scholar.google.com/citations?user=mCu8_uYAAAAJ&hl=en
AIMS AND SCOPE
Description: The rising global demand for renewable energy has intensified interest in biofuels derived from biomass such as algae, agricultural residues, and lignocellulosic materials. However, large-scale biofuel production still faces inefficiencies, inconsistent yields, and high costs. Smart bioreactors integrated with real-time sensing technologies offer a transformative solution by enabling continuous monitoring and control of key parameters like temperature, pH, dissolved oxygen, nutrients, microbial activity, and biomass growth. Using biosensors, electrochemical and optical sensors including spectrophotometric and fluorescence-based systems these advanced platforms ensure optimal process conditions and support remote, IoT-enabled supervision. Intelligent bioreactors also improve sustainability by reducing energy use, water consumption, and raw material inputs, while enabling waste recycling in closed-loop systems. Long-term data collection supports predictive modelling, anomaly detection, and process optimization. Despite their promise, challenges remain in sensor standardization, biocompatibility, data handling, and affordability for smaller producers. This research collection explores the design, optimization, and application of smart bioreactors and real-time sensing technologies to advance efficient and sustainable biofuel production through interdisciplinary contributions in biotechnology, engineering, and data science.
LIST OF TOPICS
- Nanotechnology-Driven Sensor Integration in Smart Bioreactors for Algal Biofuel Production
- Multi-Omics Fusion for Adaptive Feedback Control in Intelligent Biofuel Bioreactors
- Wireless Sensor Networks for Autonomous Bioreactor Environmental Regulation
- Cyber-Physical Systems for Closed-Loop Biofuel Manufacturing Platforms
- Machine Vision Applications in Biomass Tracking for Smart Bioreactor Systems
- Self-Learning Bioreactor Controllers Using Reinforcement Learning Algorithms
- Quantum-Inspired Optimization for Biofuel Process Efficiency in Smart Reactors
- BioMEMS-Based Real-Time Sensing for Precision-Controlled Fermentation Environments
- Smartphone-Connected Portable Bioreactor Systems for Rural Bioenergy Deployment
- Robotics-Assisted Sampling and Sensing in Modular Bioreactor Farms
- Electrochemical Biosensor Arrays for Continuous Metabolite Monitoring in Bioreactors
- Sustainable Biofuel Scaling Using Swarm Intelligence for Bioreactor Coordination
- Low-Cost Printed Electronics for Affordable Real-Time Sensing in Microbial Fuel Bioreactors
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: eseosa.omorogiuwa@uniport.edu.ng
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: 20/10/2026
- First round of reviews completed: 15/11/2026
- Revised manuscripts due: 15/02/2027
- Final manuscripts due: 15/03/2027