Intelligent Olfactory System Utilizing In Situ Ceria Nanoparticle-Integrated Laser-Induced Graphene

Area of Science:

• Materials Science
• Nanotechnology
• Sensor Technology

Background:

• Digitizing human senses drives technological innovation, but artificial olfaction remains a challenge.
• Electronic noses (e-noses) show promise for various applications, yet sensor array fabrication is complex and costly.
• Mimicking olfactory receptors requires advanced sensor integration.

Purpose of the Study:

• To develop a novel, easily fabricated sensor array for artificial olfaction.
• To create a diverse sensor array using laser-induced graphene (LIG) and cerium oxide nanoparticles.
• To accurately classify odorant molecules for applications in perfumes and cosmetics.

Main Methods:

• Fabrication of a porous laser-induced graphene (LIG) sensor array with in situ-doped cerium oxide nanoparticles.
• Tuning laser irradiation parameters to achieve physical and chemical diversity in LIG and CeO2.
• Utilizing t-distributed stochastic neighbor embedding (t-SNE) and support vector machine (SVM) for machine learning analysis.

Main Results:

• A one-step fabrication process for a sensor array with diverse response patterns.
• Accurate prediction of odorant molecule type and concentration (>95% accuracy).
• Successful classification of nine odorant molecules relevant to perfumes and cosmetics.

Conclusions:

• This study presents a rapid and straightforward method for creating olfactory receptor-mimicking arrays.
• The developed e-nose technology advances artificial olfaction systems.
• The approach offers a cost-effective solution for complex sensor fabrication.