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Title
Japanese: 
English:A Robust Odor Mixture Quantification Method Based on Active Sensing Using Both QCM Frequency Shifts and Resistance Changes of Multiple Harmonics 
Author
Japanese: Bao Ziteng, Manuel Aleixandre, 長谷川 晶一, 中本 高道.  
English: Ziteng Bao, Manuel Aleixandre, Shoichi Hasegawa, Takamichi Nakamoto.  
Language English 
Journal/Book name
Japanese: 
English:Institute of Electrical and Electronics Engineers (IEEE) 
Volume, Number, Page Vol. 25    Issue 23    pp. 42482-42489
Published date Dec. 1, 2025 
Publisher
Japanese: 
English:IEEE 
Conference name
Japanese: 
English: 
Conference site
Japanese: 
English: 
Official URL http://xplorestaging.ieee.org/ielx8/7361/11273036/11215594.pdf?arnumber=11215594
 
DOI https://doi.org/10.1109/jsen.2025.3622147
Abstract This work improves a previously proposed quantification framework by expanding its applicability to quaternary odor mixtures and optimizing the active-sensing process. The approach employs four quartz crystal microbalance (QCM) sensors, where both frequency shifts and resistance changes at multiple odd harmonics—measured by vector network analyzers (VNWA)—serve as virtual sensors to enhance selectivity. A selection strategy based on the condition number was introduced to identify informative harmonic responses. Experiments validated that the proposed method reduced the average root-mean-square error (RMSE) by 47.44%, with a statistically significant improvement (p = 0.0070) compared with the only fundamental responses. Among three feedback control algorithms, finite horizon linear–quadratic regulator (LQR) with time-varying gains achieved the best active-sensing performance. The experimental evaluations further confirmed short-term and long-term repeatabilities, as well as the capability to handle unstable sensor responses. Overall, the proposed method enables accurate and robust quantification of quaternary odor mixtures across a wide recipe range, demonstrating its potential as an easy-to-use solution for future odor recording systems.

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