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Development of a Sensing Array for Human Breath Analysis Based on SWCNT Layers Functionalized with Semiconductor Organic Molecules
Author(s) -
Freddi Sonia,
Emelianov Aleksei V.,
Bobrinetskiy Ivan I.,
Drera Giovanni,
Pagliara Stefania,
Kopylova Daria S.,
Chiesa Maria,
Santini Giuseppe,
Mores Nadia,
Moscato Umberto,
Nasibulin Albert G.,
Montuschi Paolo,
Sangaletti Luigi
Publication year - 2020
Publication title -
advanced healthcare materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.288
H-Index - 90
eISSN - 2192-2659
pISSN - 2192-2640
DOI - 10.1002/adhm.202000377
Subject(s) - breath gas analysis , materials science , copd , sensor array , exhaled air , hydrogen sulfide , pulmonary disease , nitrogen dioxide , sodium hydrosulfide , biomarker , nanotechnology , chemistry , chromatography , medicine , computer science , organic chemistry , biology , biochemistry , toxicology , sulfur , machine learning , metallurgy
A sensor array based on heterojunctions between semiconducting organic layers and single walled carbon nanotube (SWCNT) films is produced to explore applications in breathomics, the molecular analysis of exhaled breath. The array is exposed to gas/volatiles relevant to specific diseases (ammonia, ethanol, acetone, 2‐propanol, sodium hypochlorite, benzene, hydrogen sulfide, and nitrogen dioxide). Then, to evaluate its capability to operate with real relevant biological samples the array is exposed to human breath exhaled from healthy subjects. Finally, to provide a proof of concept of its diagnostic potential, the array is exposed to exhaled breath samples collected from subjects with chronic obstructive pulmonary disease (COPD), an airway chronic inflammatory disease not yet investigated with CNT‐based sensor arrays, and breathprints are compared with those obtained from of healthy subjects. Principal component analysis shows that the sensor array is able to detect various target gas/volatiles with a clear fingerprint on a 2D subspace, is suitable for breath profiling in exhaled human breath, and is able to distinguish subjects with COPD from healthy subjects based on their breathprints. This classification ability is further improved by selecting the most responsive sensors to nitrogen dioxide, a potential biomarker of COPD.