Machine learning boosts graphene oxide and reduced graphene oxide sensing abilities
Researchers at Concordia University have developed nanocomposites using graphene oxide and reduced graphene oxide embedded in a nanocellulose matrix, achieving high accuracy in predictive modeling with R² > 0.99. This advancement is significant for the field of advanced carbon materials as it demonstrates the potential of these composites in applications such as wearable electronics and biosensors, leveraging the unique properties of graphene oxide and reduced graphene oxide.
The PhD thesis by Ghazaleh Ramezani at Concordia University explores the development of eco-friendly nanocomposites using graphene oxide (GO) and reduced graphene oxide (rGO) embedded in a nanocellulose matrix. The study highlights the potential of these materials for sustainable, high-performance applications. Nanocellulose, available as cellulose nanocrystals and nanofibers, offers a high surface area, flexibility, and enhanced mechanical and chemical reactivity, making it an ideal matrix for integrating functional nanomaterials.
Graphene oxide and reduced graphene oxide provide complementary properties. GO's oxygen-containing groups enhance surface modification and dispersion in aqueous solutions, while rGO restores the electrical conductivity crucial for biosensing and flexible electronics. The synthesis and reduction of GO and rGO were achieved using green agents such as citric and L-ascorbic acids, presenting scalable and safer alternatives to traditional methods.
The experimental analysis of nanocellulose/GO and nanocellulose/rGO films revealed exceptional electrical conductivity, mechanical strength, and environmental stability, essential for applications in wearable electronics and biosensors. Spectroscopic, microscopic, and electrochemical studies identified the significance of hydrogen bonding, π–π interactions, and composite architecture in enhancing performance.
Predictive modeling using Lasso regression and neural networks demonstrated strong composition–property relationships with high accuracy (R² > 0.99). This research confirms that nanocellulose composites with GO and rGO are renewable, recyclable, and functional under ambient conditions, offering promising applications in biosensing, smart packaging, and health monitoring. The findings contribute to the advancement of sustainable functional materials at the nanoscale.
Source: Graphene Feed