R. Leghrib

Gas Sensing with Au-Decorated Carbon Nanotubes

The sensing properties of carbon nanotubes (CNTs) decorated with gold nanoparticles have been investigated by means of combined theoretical and experimental approaches. On one hand, first-principles and nonequilibrium Greens functions techniques give access to the microscopic features of the sensing mechanisms in individual nanotubes, such as electronic charge transfers and quantum conductances. On the other hand, drop coating deposition of carbon nanotubes decorated with gold nanoparticles onto sensor substrates and their characterization in the detection of pollutants such as NO(2), CO, and C(6)H(6) provide insight into the sensing ability of nanotube mats. Using the present combined approaches, the improvement in the detection of some specific gases (NO(2) and CO) using Au-functionalized nanotubes is explained. However, for other gases such as C(6)H(6), the Au nanoparticles do not seem to play a crucial role in the sensing process when compared with pristine CNTs functionalized with oxygen plasma. Indeed, these different situations can be explained by identifying the relationship between the change of resistance (macroscopic feature) and the shift of the Fermi level (microscopic feature) after gas adsorption. The understanding of the sensing ability at the atomic level opens the way to design new gas sensors and to tune their selectivity by predicting the nature of the metal that is the most appropriate to detect specific molecular species.

Carbon nanotubes randomly decorated with gold clusters: from nano2hybrid atomic structures to gas sensing prototypes.

Carbon nanotube surfaces, activated and randomly decorated with metal nanoclusters, have been studied in uniquely combined theoretical and experimental approaches as prototypes for molecular recognition. The key concept is to shape metallic clusters that donate or accept a fractional charge upon adsorption of a target molecule, and modify the electron transport in the nanotube. The present work focuses on a simple system, carbon nanotubes with gold clusters. The nature of the gold-nanotube interaction is studied using first-principles techniques. The numerical simulations predict the binding and diffusion energies of gold atoms at the tube surface, including realistic atomic models for defects potentially present at the nanotube surface. The atomic structure of the gold nanoclusters and their effect on the intrinsic electronic quantum transport properties of the nanotube are also predicted. Experimentally, multi-wall CNTs are decorated with gold clusters using (1) vacuum evaporation, after activation with an RF oxygen plasma and (2) colloid solution injected into an RF atmospheric plasma; the hybrid systems are accurately characterized using XPS and TEM techniques. The response of gas sensors based on these nano(2)hybrids is quantified for the detection of toxic species like NO(2), CO, C(2)H(5)OH and C(2)H(4).

Quantitative trace analysis of benzene using an array of plasma-treated metal-decorated carbon nanotubes and fuzzy adaptive resonant theory techniques.

The functionalization of carbon nanotube sidewalls with metal nanoparticles is exploited here to improve the sensitivity and selectivity of gas sensors operated at room temperature. An array of sensors using oxygen plasma treated multiwalled carbon nanotubes (bare and decorated with Pt, Pd or Rh nanoparticles) is shown to selectively detect traces of benzene (i.e., 100 ppb) in the presence of carbon monoxide, hydrogen sulfide or nitrogen dioxide at different humidity levels. Employing a quantitative fuzzy adaptive resonant theory (ART) network whose inputs are the responses of the sensor array, it is possible to accurately estimate benzene concentration in a changing background. The quantitative fuzzy ART is especially suited for compensating the nonlinear effects in sensor response caused by changes in ambient humidity, which explains why this method clearly outperforms partial least squares calibration models at estimating benzene concentration. These results open the way to design new affordable, wearable, sensitive and selective detectors aimed at the personal protection of workers subject to occupational exposure to benzene, toluene, ethyl benzene and xylenes.