Mechanical and Materials Engineering Department: Aref Aasi, Mechanical Engineering PhD Thesis Defense, "Early Detection of Disease Biomarkers in Exhaled Breath through Nanomaterials-Based Sensors: A Comprehensive Investigation"

Friday, April 7, 2023
2:00 pm to 4:00 pm
Floor/Room #
Room 102 / E-mail for Zoom link

Abstract: Although small compounds can also be extremely powerful cancer biomarkers, early illness detection, particularly cancer detection, mostly focuses on the precise recognition of large-sized molecules, such as proteins or DNA. Clinical trials have shown the potential of breath analysis for detecting various serious illnesses including cancer.

The non-invasive and early identification of physiological diseases using gas analysis of exhaled breath has gained popularity. The identification and monitoring of diseases may benefit greatly from the development of gas sensing of volatile organic compounds (VOCs) and inorganic gases in exhaled breath. These substances can give insight into a person's metabolic state and numerous medical disorders, including cancer. For instance, studies have shown that breath analysis can identify particular VOCs linked to various cancers, including lung, breast, liver, and colorectal cancers. Moreover, breath analysis has demonstrated potential in the diagnosis of multiple sclerosis, Parkinson's disease, and other neurodegenerative disorders.

The use of nanomaterial-based sensors has shown great potential for the development of highly selective, sensitive, and cost-effective sensors for breath analysis. These sensors can detect and quantify specific biomarkers present in exhaled breath samples that are indicative of different physiological disorders. Hence, the principal objectives of this project are to comprehensively investigate the biosensing capabilities of diverse families of nanomaterials toward specific disease biomarkers.

We studied the sensing capability of a Carbon Nanotube (CNT)-based sensor toward toluene as a well-known lung cancer biomarker and tuned its properties. Later, liver cancer biomarkers (octenol, decane, and hexanal) detection was explored employing the CNT sensor. The results disclosed that the targets were physisorbed on the bare single-walled CNT, however, their adsorption was enhanced by surface modifications, and they were chemisorbed on the modified sensor substrate.

Then, in search of new disease biomarkers, we looked at other popular nanomaterials including black phosphorene and transition metal dichalcogenides (MoS2, WS2). For instance, the MoS2 biosensor was used to study the detection of biomarkers for colorectal cancer, such as benzaldehyde and indole. The outcomes demonstrated that the sensor could effectively capture biomarker molecules after increasing the sensor's sensing capabilities.

Next, the sensing behavior of novel nanomaterials such as BC6N, and PdPS/Se toward organic and inorganic molecules was scrutinized. For example, the body releases inorganic compounds such as Ammonia (NH3) through the breath and urine during the metabolism of proteins. Nonetheless, elevated levels of NH3 in the breath can be a sign of renal disease.

Finally, point-of-care (POC) diagnostics were developed based on single-walled CNTs. An experimental test setup was assembled, along with these chips and devices for this purpose. Their ability to sense molecules was investigated, with formaldehyde serving as a key indicator for lung cancer. It was divulged that the sensitivity of fabricated field-effect transistor (FET) SWCNT toward formaldehyde in presence of humidity (mimicking human breath) can be improved after its surface functionalization.

All in all, biomarkers play an important role in clinical practice, and cancer research, and the development of new biomarkers and technologies for their detection and analysis have the potential to improve cancer diagnosis and treatment outcomes. Ergo, our findings will enable us to comprehend nanomaterial-based biosensors and platforms more fully and identify the disease biomarkers. It might also pave the way for a novel approach to early disease diagnosis and especially cancer monitoring.

Advisor: Professor Balaji Panchapakesan

Committee Member: Prof. Adam Clayton Powell

Committee Member: Prof. Ahmet Can Sabuncu

Committee Member: Prof. Mehul Bhatia