Metal oxide sensor arrays for the detection, differentiation, and quantification of volatile organic compounds at sub-parts-per-million concentration levels

Wolfrum, Edward J.; Meglen, Robert M.; Peterson, Darren J.; Sluiter, Justin

doi:10.1016/j.snb.2005.09.026

Cited by 105 publications

(53 citation statements)

References 11 publications

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“…Used in the laboratory, in combination with calibration models and multivariate regression it is possible to differentiate and semi-quantify VOCs 5,14,15 . Several studies have shown that MOS sensors often exhibit nonlinear responses towards VOCs 3,5,8 , although their response does become linear at VOC concentrations below 100 ppb, a value reasonably representative of ambient air 1,5 .…”

Section: Introductionmentioning

confidence: 99%

“…Nonlinear relationships exist between MOS VOC sensitivity and other variables, for example RH and temperature, further complicating calibration and ambient use. Sensitivities and response times can be different for notionally identical sensors 3,14,16 therefore transferring a single calibration model from the laboratory to deployment, and indeed from sensor to sensor is difficult 5 . There is an emerging literature showing that corrections for both chemical and environmental factors can be improved using more complex statistical models 13 that go beyond simple linear regressions, for example, using Partial Least Squares 14 , neural networks 17 or Gaussian process emulation 1 .…”

Section: Introductionmentioning

confidence: 99%

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Clustering approaches to improve the performance of low cost air pollution sensors

et al. 2017

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Article:Smith, Katie R., Edwards, Peter M. orcid.org/0000-0002-1076-6793, Evans, Mathew J. orcid.org/0000-0003-4775-032X et al. (5 more Low cost air pollution sensors have substantial potential for atmospheric research and for the applied control of pollution in the urban environment, including more localized warnings to the public. The current generation of single-chemical gas sensors experience degrees of interference from other co-pollutants and have sensitivity to environmental factors such as temperature, wind speed and supply voltage. There are uncertainties introduced also because of sensor-to-sensor response variability, although this is less well reported. The sensitivity of Metal Oxide Sensors (MOS) to volatile organic compounds (VOCs) changed with relative humidity (RH) by up to a factor of five over the range 19-90%RH and with an uncertainty in the correction of a factor two at any given RH. The short-term (second to minute) stabilities of MOS and electrochemical CO sensor responses were reasonable. During more extended use inter-sensor quantitative comparability was degraded due to unpredictable variability in individual sensor responses (to either measurand or interference or both) drifting over timescales of several hours to days. For timescales longer than a week identical sensors showed slow, often downwards, drifts in their responses which diverged across six CO sensors by up to 30% after two weeks. The measurement derived from the median sensor within clusters of 6, 8 and up to 21 sensors was evaluated against individual sensor performance and external reference values. The clustered approach maintained the cost competitiveness of a sensor device, but the median concentration from the ensemble of sensor signals largely eliminated the randomised hour-to-day response drift seen in individual sensors and excluded the effects of small numbers of poorly performing sensors that drifted significantly over longer time periods. The results demonstrate that for individual sensors to be optimally comparable to one another, and to reference instruments, they would likely require frequent calibration. The use of a cluster median value eliminates unpredictable medium term response changes, and other longer term outlier behaviours, extending the likely period needed between calibration and making a linear interpolation between calibrations more appropriate. Through the use of sensor clusters rather than individual sensors existing low cost technologies could deliver significantly improved quality of observations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Clustering approaches to improve the performance of low cost air pollution sensors

et al. 2017

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“…The EN can compare and analyze the scent information of different samples as well as establish an information database using standard samples, by adopting stoichiometry to qualify and quantitatively analyze unknown samples (Gardner & Bartlett, 1994). Currently, the EN has been extensively applied in food analysis (Dutta et al, 2003;Thi et al, 2004;Gan et al, 2005;Wolfrum et al, 2006), environmental quality monitoring (Zhang et al, 2003), scent pattern analysis (Been, 2010), disease diagnosis (Di et al, 2003), and in other fields. This study used the EN to detect the changes in the volatile components of R. laevigata samples harvested at different periods to provide a reference for quantifiable scent indicators for R. laevigata.…”

Section: Discussionmentioning

confidence: 99%

Scent analysis of Rosa laevigata through metal oxide sensor array electronic nose

Chen¹,

Jian²,

Han³

et al. 2011

Rev. bras. farmacogn.

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Abstract:The scent fingerprint of Rosa laevigata Michx., Rosaceae, samples harvested at different periods was investigated. Principal component analysis (PCA) and discriminant factor analysis (DFA) were done on the scent response values measured by an electronic nose (EN) sensor. Statistical quality control (SQC) analysis was also conducted. The R. laevigata samples were clustered into two categories after being analyzed by PCA and DFA. One cluster consisted of samples No. 1 to No. 6, and the other consisted of samples No. 7 to No. 10. The combination of EN, PCA, and DFA for scent analysis can be used for the quality control of traditional Chinese medicines.

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“…Nafion membrane was used as active film for the detection of methanol [1]. Recently, significant attention has been paid to PS, particularly, for its use in various sensing devices [2][3][4]. In fact, due to its large specific surface area, PS gives the ability to react with gases and sense them readily.…”

Section: Introductionmentioning

confidence: 99%

“…They are low cost and low power consumption. However, metal oxides gas sensors work at rather high temperatures [2][3][4]. Most studies performed on porous silicon (PS) focused essentially on its optical properties.…”

Section: Introductionmentioning

confidence: 99%

Aluminum-mesoporous silicon coplanar type structure for methanol gas sensing

Khardani

Bouaïcha

Boujmil

et al. 2010

Microporous and Mesoporous Materials

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Metal oxide sensor arrays for the detection, differentiation, and quantification of volatile organic compounds at sub-parts-per-million concentration levels

Cited by 105 publications

References 11 publications

Clustering approaches to improve the performance of low cost air pollution sensors

Clustering approaches to improve the performance of low cost air pollution sensors

Scent analysis of Rosa laevigata through metal oxide sensor array electronic nose

Aluminum-mesoporous silicon coplanar type structure for methanol gas sensing

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