Detection of acetone in the human breath as diabetes biomarker based on PPy/WO3 nanocomposite sensor by FFT continuous cyclic voltammetry method

This research represents a novel detection method of acetone level in the exhaled breath samples (RH=88 %) based on polypyrrole/tungsten oxide (PPy/WO₃) nanocomposite sensor. The PPy/WO₃ sensor was fabricated by the deposition of nanocomposite on/between interdigitated electrodes (IDEs) through electrospray coating and was then characterized by FE-SEM imaging. In this detection method, the coulometric signal of the sensor was calculated using Fast Fourier Continuous Cyclic Voltammetry (FFTCCV), where cyclic voltammetry (CV) was applied to the sensor in the defined potential rang and then charge changes of the sensor was obtained by integration of the current in all scanned potential ranges. FFTCCV method enhances the sensitivity of the sensor when exposed to the gas mixtures containing acetone. In addition to its fast coulometric response time (≤5 s) in the two linear ranges of 0.7–2.8 ppm and 2.8–28.2 ppm (R²=0.99), FFTCCV method provides the low detection limit of 70 ppb, and high sensitivity toward acetone at the optimum values of the parameters. The fabricated sensor showed great selectivity toward acetone when exposed to humid air and some exhaled gas like carbon dioxide, ammonia, methanol, ethanol and alkyl amines. The results were very satisfying as the sensor was capable to detect different acetone levels in human exhaled breath as non-invasive diagnosis of diabetes with a good correlation (R²≃0.9) to the routine blood sugar test taken by different commercial glucometers results.