Molecularly modified silicon nanowire field effect transistors (SiNW FETs) are starting to appear as promising devices for sensing various volatile organic compounds (VOCs). Understanding the connection between the molecular layer structure attached to the SiNWs and VOCs is essential for the design of high performance sensors. Here, we explore the chain length influence of molecular layers on the sensing performance to polar and nonpolar VOCs. SiNW FETs were functionalized with molecular layers that have similar end (methyl) group and amide bridge bond, but differ in their alkyl chain lengths. The resulting devices were then exposed to polar and nonpolar VOCs in various concentrations. Our results showed that the sensing response to changing the threshold voltage (ΔVth) and changing the relative hole mobility (Δμh/μh-a) have a proportional relationship to the VOC concentration. On exposure to a specific VOC concentration, ΔVth response increased with the chain length of the molecular modification. In contrast, Δμh/μh-a did not exhibit any obvious reliance on the chain length of the molecular layer. Analysis of the responses with an electrostatic-based model suggests that the sensor response in ΔVth is dependent on the VOC concentration, VOC vapor pressure, VOC-molecular layer binding energy, and VOC adsorption-induced dipole moment changes of molecular layer.
Rapid component separation and robust surface-enhanced Raman scattering (SERS) identification of drugs in real human urine remain an attractive challenge because of the sample complexity, low molecular affinity for metal surface, and inefficient use of hotspots in one- or two-dimensional (2D) geometries. Here, we developed a 5 min strategy of cyclohexane (CYH) extraction for separating amphetamines from human urine. Simultaneously, an oil-in-water emulsion method is used to assemble monodisperse Ag nanoparticles in the CYH phase into spherical colloidal superstructures in the aqueous phase. These superstructures create three-dimensional (3D) SERS hotspots which exist between every two adjacent particles in 3D space, break the traditional 2D limitation, and extend the hotspots into the third dimension along the z-axis. In this platform, a conservative estimate of Raman enhancement factor is larger than 10(7), and the same CYH extraction processing results in a high acceptability and enrichment of drug molecules in 3D hotspots which demonstrates excellent stability and reproducibility and is suitable for the quantitative examination of amphetamines in both aqueous and organic phases. Parallel ultraperformance liquid chromatography (UPLC) examinations corroborate an excellent performance of our SERS platform for the quantitative analysis of methamphetamine (MA) in both aqueous solution and real human urine, of which the detection limits reach 1 and 10 ppb, respectively, with tolerable signal-to-noise ratios. Moreover, SERS examinations on different proportions of MA and 3,4-methylenedioxymethamphetamine (MDMA) in human urine demonstrate an excellent capability of multiplex quantification of ultratrace analytes. By virtue of a spectral classification algorithm, we realize the rapid and accurate recognition of weak Raman signals of amphetamines at trace levels and also clearly distinguish various proportions of multiplex components. Our platform for detecting drugs promises to be a great prospect for a rapid, reliable, and on-spot analyzer.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.