Deepam Gangopadhyay;Sumit Kundu;Mahuya Bhattacharyya Banerjee;Shreya Nag;Panchanan Pramanik;Runu Banerjee Roy
{"title":"分子印迹石英晶体微平衡传感器可靠检测各种松木精油中α -松油醇","authors":"Deepam Gangopadhyay;Sumit Kundu;Mahuya Bhattacharyya Banerjee;Shreya Nag;Panchanan Pramanik;Runu Banerjee Roy","doi":"10.1109/JSEN.2025.3583871","DOIUrl":null,"url":null,"abstract":"<inline-formula> <tex-math>$\\alpha $ </tex-math></inline-formula>-terpineol (A-Te), a bioactive monoterpenoid, is widely used in cosmetics and aroma therapy for its appeasing fragrance and flavor. Recent studies have acknowledged its immense potential in biological applications and naturopathy. This study aims to develop a low-cost detection mechanism of A-Te using a sensitive quartz crystal microbalance (QCM) sensor, employing a highly selective molecularly imprinted polymer (MIP) of methyl methacrylate (MMA) and acrylic acid (AA). Frequency deviation of the sensor has been utilized for A-Te detection in four commercial-grade pine essential oils (PEOs). This has yielded a remarkable sensitivity of 0.149 Hz/ppm with a wide linear range of 5–800 ppm. Reliability of the sensor has been assessed in terms of a reproducibility and repeatability study, showcasing promising values of 90.70% and 92.32%, respectively. The limit of detection (LOD) has been achieved at 1.33 ppm. Polymer characterization and surface morphology of the sensor have been analyzed through Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM), respectively. Furthermore, responses obtained from PEO samples were correlated with the conventional gas chromatographic method using principal component regression (PCR) and random forest regression (RFR) models. Notably, a high prediction accuracy (96.38%) has been achieved from PCR.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"27966-27973"},"PeriodicalIF":4.3000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Molecular Imprinted Quartz Crystal Microbalance Sensor for Reliable Detection of Alpha-Terpineol in Various Pine Essential Oils\",\"authors\":\"Deepam Gangopadhyay;Sumit Kundu;Mahuya Bhattacharyya Banerjee;Shreya Nag;Panchanan Pramanik;Runu Banerjee Roy\",\"doi\":\"10.1109/JSEN.2025.3583871\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<inline-formula> <tex-math>$\\\\alpha $ </tex-math></inline-formula>-terpineol (A-Te), a bioactive monoterpenoid, is widely used in cosmetics and aroma therapy for its appeasing fragrance and flavor. Recent studies have acknowledged its immense potential in biological applications and naturopathy. This study aims to develop a low-cost detection mechanism of A-Te using a sensitive quartz crystal microbalance (QCM) sensor, employing a highly selective molecularly imprinted polymer (MIP) of methyl methacrylate (MMA) and acrylic acid (AA). Frequency deviation of the sensor has been utilized for A-Te detection in four commercial-grade pine essential oils (PEOs). This has yielded a remarkable sensitivity of 0.149 Hz/ppm with a wide linear range of 5–800 ppm. Reliability of the sensor has been assessed in terms of a reproducibility and repeatability study, showcasing promising values of 90.70% and 92.32%, respectively. The limit of detection (LOD) has been achieved at 1.33 ppm. Polymer characterization and surface morphology of the sensor have been analyzed through Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM), respectively. Furthermore, responses obtained from PEO samples were correlated with the conventional gas chromatographic method using principal component regression (PCR) and random forest regression (RFR) models. Notably, a high prediction accuracy (96.38%) has been achieved from PCR.\",\"PeriodicalId\":447,\"journal\":{\"name\":\"IEEE Sensors Journal\",\"volume\":\"25 15\",\"pages\":\"27966-27973\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Journal\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11069266/\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/11069266/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
A Molecular Imprinted Quartz Crystal Microbalance Sensor for Reliable Detection of Alpha-Terpineol in Various Pine Essential Oils
$\alpha $ -terpineol (A-Te), a bioactive monoterpenoid, is widely used in cosmetics and aroma therapy for its appeasing fragrance and flavor. Recent studies have acknowledged its immense potential in biological applications and naturopathy. This study aims to develop a low-cost detection mechanism of A-Te using a sensitive quartz crystal microbalance (QCM) sensor, employing a highly selective molecularly imprinted polymer (MIP) of methyl methacrylate (MMA) and acrylic acid (AA). Frequency deviation of the sensor has been utilized for A-Te detection in four commercial-grade pine essential oils (PEOs). This has yielded a remarkable sensitivity of 0.149 Hz/ppm with a wide linear range of 5–800 ppm. Reliability of the sensor has been assessed in terms of a reproducibility and repeatability study, showcasing promising values of 90.70% and 92.32%, respectively. The limit of detection (LOD) has been achieved at 1.33 ppm. Polymer characterization and surface morphology of the sensor have been analyzed through Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM), respectively. Furthermore, responses obtained from PEO samples were correlated with the conventional gas chromatographic method using principal component regression (PCR) and random forest regression (RFR) models. Notably, a high prediction accuracy (96.38%) has been achieved from PCR.
期刊介绍:
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