Point-of-care health monitoring is still a challenging technology under development. Various sensors can be integrated into wearable devices for the monitoring of different health parameters like temperature and pulse rate. However to provide deep health analyses and a prediction for the existence of disease still requires the use of complicated diagnostic tools like MRI, computer tomography, etc, or body liquids analysis from blood, saliva, etc.

Breath is one of the main sources of human health parameters that can be used for predicting the state of different internal organs. Exhaled breath composition is very complex and the existence of disease marker molecules can be as low as 1 ppm (one part per million). That means that using breath for health monitoring purposes requires highly sensitive tools with a recognition ability down to single molecules.

Among a number of methods for breath analysis, the most promising one is based on the concept of an electronic nose. Here, the task for certain disease pattern recognition is moves from hardware to software using advanced methods of data analysis. This concept provides both miniaturizations of sensor designs and fast response times. Yet the development of sensor platforms that provide high sensitivity to the informative molecules with high humidity background in the exhaled breath is still challenging.

A team of researchers from Università Cattolica del Sacro Cuore (Italy), Skolkovo Institute of Science and Technology (Russia) and National Research University of Electronic Technology (Russia), has developed a method for fast, on-site and still accurate breath analysis that does not need special preparation of breath samples. The method is based on an electronic nose platform that uses a set of single-walled carbon nanotube (SWCNTs) sensors deposited on flexible substrates and modified by different semiconducting organic molecules. Carbon nanotubes are widely used for electronic nose development because of their high sensitivity to environmental gases, high stability, and intrinsic variations in electronic properties that make them perfect for use in electronic nose platforms. The researchers suggested improving the recognition properties of the SWCNT sensors by additional functionalization that increases the sensors' specificity to different gases, making sub-ppm analysis possible.

The researchers demonstrated the performance of this method by analyzing Various gases and vapors (ammonia, ethanol, acetone, 2-propanol, sodium hypochlorite, benzene, hydrogen sulfide, and nitrogen dioxide). The sensitivity was demonstrated down to 0.25 ppm for each nanotube sensor area of about 1 cm2 with high level of discrimination between gases. The best detection limit was demonstrated for ammonia for nanotubes covered by PANI molecules and hydrogen sulfide for CNT covered by TCTA molecules of 0.014 and 0.064 ppm, respectively.

Moreover, the team demonstrated that these sensors can be used for chronic obstructive pulmonary disease (COPD) recognition based on breath analyses of 21 individuals. Advanced data analysis methods based on principle component analyses provided a clear distinction between subjects with and without COPD.

The research team, led by Prof. L. Sangaletti, has demonstrated the high performance of their proposed sensing platform in-breath recognition with relatively fast response times without the need for complicated breath treatment. In the case of COPD, they observed that the analysis can be improved by properly targeting the molecules specific to the decease.

The main benefit of such an electronic nose platform is the possibility of future miniaturization and integration on a chip compatible with conventional microelectronics technologies, paving the way for on-site analysis using smartphones.

This project was funded in part by the ANAPNOI project (Catholic University of the Sacred Heart) and the Russian Science Foundation.

Nanowerk May 13, 2020

A Nanowerk exclusive provided by National Research University of Electronic Technology

 

 

 

 

 

 

 

 

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