Litvinenko S V, Bielobrov D O, Lysenko V, Skryshevsky V A
Institute of High Technologies, Taras Shevchenko National University of Kyiv, 64, Volodymyrs'ka St., 01601, Kyiv, Ukraine.
Nanotechnology Institute of Lyon (INL) UMR 5270, CNRS, INSA, University of Lyon, Lyon, Villeurbanne, 69621, France.
Nanoscale Res Lett. 2016 Dec;11(1):374. doi: 10.1186/s11671-016-1589-0. Epub 2016 Aug 23.
The electronic tongue based on the array of low selective photovoltaic (PV) sensors and principal component analysis is proposed for detection of various alcohol solutions. A sensor array is created at the forming of p-n junction on silicon wafer with porous silicon layer on the opposite side. A dynamical set of sensors is formed due to the inhomogeneous distribution of the surface recombination rate at this porous silicon side. The sensitive to molecular adsorption photocurrent is induced at the scanning of this side by laser beam. Water, ethanol, iso-propanol, and their mixtures were selected for testing. It is shown that the use of the random dispersion of surface recombination rates on different spots of the rear side of p-n junction and principal component analysis of PV signals allows identifying mentioned liquid substances and their mixtures.
提出了一种基于低选择性光伏(PV)传感器阵列和主成分分析的电子舌,用于检测各种酒精溶液。通过在硅片上形成p-n结,并在其对面形成多孔硅层来创建传感器阵列。由于该多孔硅侧表面复合率的不均匀分布,形成了一组动态传感器。通过激光束扫描该侧时会感应出对分子吸附光电流敏感的信号。选择水、乙醇、异丙醇及其混合物进行测试。结果表明,利用p-n结背面不同位置表面复合率的随机分散以及PV信号的主成分分析,可以识别上述液体物质及其混合物。