Trends in the Development of Electronic Noses Based on Carbon Nanotubes Chemiresistors for Breathomics

Abstract

The remarkable potential of breath analysis in medical care and diagnosis, and the consequent development of electronic noses, is currently attracting the interest of the research community. This is mainly due to the possibility of applying the technique for early diagnosis, screening campaigns, or tracking the effectiveness of treatment. Carbon nanotubes (CNTs) are known to be good candidates for gas sensing, and they have been recently considered for the development of electronic noses. The present work has the aim of reviewing the available literature on the development of CNTs-based electronic noses for breath analysis applications, detailing the functionalization procedure used to prepare the sensors, the breath sampling techniques, the statistical analysis methods, the diseases under investigation, and the population studied. The review is divided in two main sections: one focusing on the e-noses completely based on CNTs and one reporting on the e-noses that feature sensors based on CNTs, along with sensors based on other materials. Finally, a classification is presented among studies that report on the e-nose capability to discriminate biomarkers, simulated breath, and animal or human breath.

Targeting biomarkers in the gas phase through a chemoresistive electronic nose based on graphene functionalized with metal phthalocyanines

“…Of note, the tested concentrations of almost all gases are relevant for breathomics, where the biomarkers in the exhaled breath can be found in a concentration in a low-/sub-ppm range. 11,13,14,57,60,91,92 All tested gases are clearly discriminated in a 3-dimensional PCA space. In particular, it is worth noting the capability of the array to detect VOCs that are usually poorly discriminated with chemiresistors, unless novel approaches for detection schemes and data handling are devised.…”

“…Of note, the tested concentrations of almost all gases are relevant for breathomics, where the biomarkers in the exhaled breath can be found in a concentration in a low-/sub-ppm range. 11,13,14,57,60,91,92…”

A Chemiresistor Sensor Array Based on Graphene Nanostructures: From the Detection of Ammonia and Possible Interfering VOCs to Chemometric Analysis

“…For several applications, including breathomics, food quality tracking, or environmental monitoring, a single sensor’s high selectivity is particularly important, since the analyte under investigation should be recognized and detected among many interfering gases [ 17 , 18 ]. Additionally, some applications specifically required the capability of a device to simultaneously monitor different compounds [ 17 , 19 ].…”

“…For these application fields, the development of a single chemiresistor sensor may not be the ultimate solution, on one hand due to the difficulties to maintain a high selectivity in presence of many interfering gases [ 17 , 18 , 20 ], on the other hand because of the inability of a single chemiresistor sensor to detect more than one specific analyte at the same time [ 20 , 21 , 22 , 23 ]. In turn, the development of a sensor array, or electronic nose, is preferable and it has very recently increased in popularity [ 17 , 18 , 20 , 21 , 22 , 23 ].…”

“…For these application fields, the development of a single chemiresistor sensor may not be the ultimate solution, on one hand due to the difficulties to maintain a high selectivity in presence of many interfering gases [ 17 , 18 , 20 ], on the other hand because of the inability of a single chemiresistor sensor to detect more than one specific analyte at the same time [ 20 , 21 , 22 , 23 ]. In turn, the development of a sensor array, or electronic nose, is preferable and it has very recently increased in popularity [ 17 , 18 , 20 , 21 , 22 , 23 ]. Indeed, the sensors inside an array do not necessarily need to be highly selective, since statistical treatment, as well as chemometric methods based on pattern recognition and/or multivariate data analysis, could be exploited as an alternative resource to properly analyze the data whenever experimental data alone do not offer the necessary selectivity.…”