کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10410458 894437 2005 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Cryptand/metal ion coated piezoelectric quartz crystal sensors with artificial back propagation neural network analysis for nitrogen dioxide and carbon monoxide
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
Cryptand/metal ion coated piezoelectric quartz crystal sensors with artificial back propagation neural network analysis for nitrogen dioxide and carbon monoxide
چکیده انگلیسی
Titanium(IV)/cryptand22 and Zinc(II)/cryptand22-coated piezoelectric (PZ) quartz crystal detection systems with home-made computer interfaces for data acquisition and processing were developed and successfully applied for the detection of nitrogen dioxide (NO2) and carbon monoxide (CO), respectively. Among the 20 metal ion/cryptand22 complexes, e.g. Mn2+/cryptand22, Ti4+/cryptand22, Zn2+/cryptand22, Al3+/cryptand22, Cr3+/cryptand22, Cu2+/cryptand22 and Ru3+/cryptand22, Ti4+/cryptand22 and Zn2+/cryptand22 were found to be the best adsorbents to adsorb the NO2 and CO in the air respectively. The Ti4+/cryptand22 coated PZ crystal NO2 sensor exhibited a good linear response to the concentration of NO2 with excellent sensitivity (9.10 Hz/ppm), detection limit (0.16 ppm NO2) and reproducibility with relative standard deviation (RSD) of 2.09%. The Zn2+/cryptand22 coated CO sensor also showed a good sensitivity of approximately 1.6 Hz/ppm to CO with a detection limit of 0.91 ppm and reproducibility with RSD of 2.15%. The coating load effects on the frequency responses of these cryptand22/metal ion coated PZ crystal NO2 and CO sensors were also investigated. The frequency responses of the PZ crystal sensors increased with the coating load. The cryptand22/metal ion coated PZ crystal sensors were also successfully applied as gas chromatographic (GC) detectors to detect NO2, CO and some organic compounds, e.g. propyl amine and propanoic acid. The Ti4+/cryptand22 coated PZ crystal GC detector compared well with the thermal conductivity detector (TCD) for NO2 vapor which TCD did not response. An artificial back propagation neural (BPN) network with a two-channel PZ crystal flow sensor was prepared and applied to recognize and distinguish each component (NO2 and CO) in a mixed NO2/CO sample and it showed quite good distinction of NO2 and CO in the mixed gas sample. The concentrations of NO2 and CO were also computed by multivariate linear regression analysis (MLR).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Sensors and Actuators B: Chemical - Volume 106, Issue 1, 29 April 2005, Pages 468-476
نویسندگان
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