A nanostructure-based mechanism was developed for sensing the presence of, and estimating concentration values of, specified chemical components in a sample gas to which the mechanism is exposed, where the concentrations may be as low as five parts per billion. The mechanism receives a sample gas, converts the gas information received to a change in an electrical parameter value (EPV) sensed at each of an array of separately functionalized carbon nanotubes (CNTs), estimates which of a group of specified chemical components is present and the associated chemical concentrations in the sample gas, formats information concerning the chemical components sensed in the sample gas, and transmits this information to selected recipients. The specified chemical components and the corresponding concentration values are displayed on a cellphone screen, a tablet screen, or a computer screen. Optionally, the information is compensated by removing the effects of the presence of ambient gas components that are not of concern in the sample gas.

The mechanism is based on functionalized carbon nanostructures (NSs) for sensing presence of one or more specified chemical components in a sample gas and for estimating non-negligible concentration values for the sensed components. The mechanism compensates for the presence of baseline contributions to the concentration values from chemicals that are present where the sample gas is absent. Changes in EPVs, possibly time varying, are measured when the NSs are exposed to the sample gas. Constitutive equations using calibration coefficients relate concentration values to the EPV for different specified components that may be in the sample gas.

An error function provides a measure of a difference between a predicted constitutive model of EPVs and measured EPVs for the sample gas. Minimum-error concentration values are estimated. Where the error function numerical value is no greater than a threshold value, this condition is interpreted as indicating that at least one of the specified components is present and the corresponding concentration value estimate is reasonably accurate. Asymptotic limits for one or more concentration values are estimated and compared with alarm limits for one or more gases of concern.

This work was done by Jing Li of Ames Research Center. NASA invites companies to inquire about partnering opportunities and licensing this patented technology. Contact the Ames Technology Partnerships Office at 1-855-627-2249 or This email address is being protected from spambots. You need JavaScript enabled to view it.. Refer to ARC-17110-1.