2014
DOI: 10.1109/jsen.2014.2316117
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A Variable Response Phosphine Sensing Matrix Based on Nanostructure Treated p and n-Type Porous Silicon Interfaces

Abstract: We study the dynamic interplay as PH 3 interacts at room temperature to contribute electrons to nanostructure modified p and n-type porous silicon (PS) interfaces. A nanopore coated microporous interface is treated to form TiO 2 , SnO x , Cu x O, and Au x O (x 1) nanostructured centers deposited in fractional coverage on the PS interface. Relative sensitivities of the surface sites are measured under 2-5 and 10 ppm PH 3 exposure. The interaction with two p-type nanostructure decorated boron-doped interfaces de… Show more

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Cited by 11 publications
(9 citation statements)
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References 33 publications
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“…In Figure S10, we demonstrate that the metal oxide nanostructures greatly affect the complex impedance. However, it should be noted that this effect is size dependent limited to nanoscale particles. , Therefore, the size and level of deposition of the metal oxide nanostructures must be at a level low enough to produce electronically independent particles . Husairi et al have investigated the influence of a layer of ZnO nanostructures on the interactions of a PSi interface with liquid ethanol.…”
Section: Results and Discussion: Signatures Of Organic Solventsmentioning
confidence: 99%
See 1 more Smart Citation
“…In Figure S10, we demonstrate that the metal oxide nanostructures greatly affect the complex impedance. However, it should be noted that this effect is size dependent limited to nanoscale particles. , Therefore, the size and level of deposition of the metal oxide nanostructures must be at a level low enough to produce electronically independent particles . Husairi et al have investigated the influence of a layer of ZnO nanostructures on the interactions of a PSi interface with liquid ethanol.…”
Section: Results and Discussion: Signatures Of Organic Solventsmentioning
confidence: 99%
“…7,11 Therefore, the size and level of deposition of the metal oxide nanostructures must be at a level low enough to produce electronically independent particles. 24 Husairi et al 13 have investigated the influence of a layer of ZnO nanostructures on the interactions of a PSi interface with liquid ethanol. Through an analysis of the complex impedance curves and complementary equivalent circuit elements, Husairi et al 13 demonstrated that the ZnO nanostructures increased both the real and imaginary parts of the complex impedance.…”
Section: Acs Sensorsmentioning
confidence: 99%
“…This required interaction is varied for a given system by studyng the conductometric sensor response as a function of metal oxide deposition concentration. 9 Typical nanostructured metal oxide deposited island sites range between 10 and 20 nm as, within the constraints, the size range influences the observed interactions. 8,10 the highly accurate repeat placement of the depositions is not required.…”
Section: Methodsmentioning
confidence: 99%
“…2,4 "Deposited" nanostructured island sites serve the role of guiding gateways to force a dominant electron transduction (vs. chemisorption) at the decorated extrinsic semiconductor interface. The selection of these nanostructures and the reversible interaction they introduce for sensor applications is predicted by the IHSAB model, 2,[4][5][6][9][10][11][12][13][14] which complements the tenants of the HSAB concept, 15 and couples analyte/interface acid-base interactions with the properties of the majority charge carriers in an extrinsic semiconductor. Based on the reversible interaction of hard acids and bases with soft bases and acids, the IHSAB principle enables the selection of interacting materials that do not form strong covalent or ionic chemical bonds, thus it represents the inverse of the HSAB model 15 for significant bond formation based on strong ionic (hard acid/base) or covalent (soft acid/base) interactions and chemical bond formation.…”
mentioning
confidence: 99%
“…In order to remove the noise, a moving average is used. 31,32 The moving average works by taking the average of a fixed number of previous points in the data set and using this averaging to smooth the data. The moving average reduces the high frequency noise in the system, smoothing out the derivatives.…”
Section: Simulation-diffusionmentioning
confidence: 99%