Researchers map AI electronic nose built on metal-organic frameworks
A DGIST-led team reviewed how MOF materials, sensors and AI could support artificial systems for recognizing large numbers of odors.
By Priya Raghavan · Science Reporter
2 min read
Researchers have outlined a roadmap for an AI-powered electronic nose designed to identify large numbers of odors. The work matters because it links three pieces of the problem — odor-sensitive materials, sensor hardware and pattern-recognition software — in a single development plan.
The research was led by Hyuk-Jun Kwon in the Department of Electrical Engineering & Computer Science at Daegu Gyeongbuk Institute of Science and Technology, according to the team. The study was published in the journal Progress in Materials Science.
The team describes an “artificial olfactory system” that would detect odors in a way modeled on the human nose and then use artificial intelligence to analyze the signals, according to the researchers. The approach relies on metal-organic frameworks, known as MOFs, as a central part of the system.
According to the team, the review organizes major research trends in electronic nose technology, starting with MOF material design. It then follows the work through sensor implementation and AI-based recognition of odor patterns.
How the proposed system is framed
The roadmap treats odor sensing as a chain of connected tasks, according to the researchers. Materials must first interact with odor molecules, sensors must convert those interactions into signals, and AI systems must interpret the resulting patterns.
The team’s description places MOFs at the materials stage and artificial intelligence at the analysis stage. In that structure, the electronic nose is not just a detector; it is a system meant to classify odor information after the sensor produces data.
The research also points to the scale of the challenge. The project is described as an AI-powered electronic nose capable of distinguishing tens of thousands of odors, according to the research summary.
What the review covers
The study is presented as a systematic review and roadmap rather than a report on a single finished device. According to the team, it brings together work on MOF design, sensor construction and AI odor-pattern recognition.
That organization gives researchers a way to compare progress across the main parts of electronic nose development. It also frames future work around how materials, hardware and AI methods can be designed together rather than treated as separate problems.
The publication in Progress in Materials Science places the work in a materials-focused research context. Kwon’s team at Daegu Gyeongbuk Institute of Science and Technology presents the roadmap as a guide for developing artificial olfactory systems that combine MOFs with AI analysis.
This story draws on original reporting from Phys.org.