ArticleACS omega2021
Electronic Nose Based on Temperature Modulation of MOS Sensors for Recognition of Excessive Methanol in Liquors.
Article in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 28 citations in OpenAlex.
- Portable and Digital MOX Sensor Electronic Nose with Thermal Modulation: Design, Stability Analysis, and Long-Term Validation.Sensors (Basel, Switzerland) · 2026Article
- Rapid on-site methanol screening in distilled spirits via BME688 MOX sensor array and machine learning.Scientific reports · 2026Article
- Exploring the Influence of Pottery Jar Formula Variables on Flavor Substances Through Feature Ranking and Machine Learning: Case Study of Maotai-Flavored Baijiu.Foods (Basel, Switzerland) · 2025Article
- Response Surface Modeling of the Steady-State Impedance Responses of Gas Sensor Arrays Comprising Functionalized Carbon Nanotubes to Detect Ozone and Nitrogen Dioxide.Sensors (Basel, Switzerland) · 2023Article
- Analysis of the Response Signals of an Electronic Nose Sensor for Differentiation betweenSensors (Basel, Switzerland) · 2023Article
- Nanosensor Based on Thermal Gradient and Machine Learning for the Detection of Methanol Adulteration in Alcoholic Beverages and Methanol Poisoning.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An electronic nose based on metal oxide semiconductor (MOS) sensors has been used to identify liquors with excessive methanol. The technique for a square wave temperature modulated MOS sensor was applied to generate the response patterns and a back-propagation neural network was used for pattern recognition. The parameters of temperature modulation were optimized according to the difference in response features of target gases (methanol and ethanol). Liquors with excessive methanol were qualitatively and quantitatively identified by the neural network. The results showed that our electronic nose system could well identify the liquors with excessive methanol with more than 92% accuracy. This electronic nose based on temperature modulation is a promising portable adjunct to other available techniques for quality assurance of liquors and other alcoholic beverages.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.