pH Modeling to Predict SWCNT-COOH Gas Sensor Response to Multiple Target Gases

Carboxylated single-walled carbon nanotubes (SWCNT-COOH) have long been studied for gas/vapor sensing. Controlling the pH during the carboxylation process by adding an acid or a base yields inks with different pH values, enabling an array of sensors that can give orthogonal responses to target gases and vapors. The gas detection mechanism for these sensors under prevailing humidity is via protonation or deprotonation of the carboxylate groups induced by pH changes. Here, we have developed a computational model, as a design tool, to control the pH and test various target acidic (CO2, H2S, HCl, and HF) and basic [NH3, CH3NH2, (CH3)(2)NH, and (CH3)(3)N] gases. The results confirm the utility of the model in decision-making on sensor design as well as to develop multiple sensor arrays for constructing an electronic nose with the aid of machine learning, in advance of actual fabrication.

Automated summary

Carboxylated single-walled carbon nanotubes have been studied for gas and vapor sensing, with controlled pH values enabling an array of sensors that can give orthogonal responses to target gases and vapors. The gas detection mechanism for these sensors under prevailing humidity is via protonation or deprotonation of the carboxylate groups induced by pH changes. A computational model has been developed to control pH and test various target gases, confirming its utility in decision-making on sensor design and developing multiple sensor arrays for constructing an electronic nose with machine learning.