Document Type



Doctor of Philosophy (PhD)


Electrical and Computer Engineering

First Advisor's Name

Nezih Pala

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Chunlei Wang

Second Advisor's Committee Title

Committee co-chair

Third Advisor's Name

Shekhar Bhansali

Third Advisor's Committee Title

Committee member

Fourth Advisor's Name

Pulugurtha Markondeya Raj

Fourth Advisor's Committee Title

Committee member

Fifth Advisor's Name

Lidia Kos

Fifth Advisor's Committee Title

Committee member


Cancer, point-of-care, aptasensor, carbon, label-free, electrochemical

Date of Defense



Cancer is the second cause of death, with millions of fatalities every year. The early detection of cancer can tremendously increase the survival chances of the patients. An effective approach for early detection of cancer is developing reliable and relatively cheap biosensors that can quantify the cancer biomarkers from blood samples. These classes of the biosensor are commonly referred to as point-of-care (POC) cancer biomarker biosensors. The label-free electrochemical biosensors based on carbon dravite materials can be feasible for POC cancer biomarker biosensors. The present dissertation aims to design, develop, and optimize carbon-based biosensors for label-free detection of lactic acid and platelet-derived growth factor-BB (PDGF-BB) cancer biomarkers. Two carbon-based materials are used for developing the biosensor: carbon-micro electrotechnical systems (aka. C-MEMS) and bipolar exfoliated graphene. In the first phase of this dissertation, enzymatic biosensors based on interdigitated C-MEMS microelectrodes were investigated. The achieved results confirmed that the C-MEMS-based sensing platform functionalized with oxygen-plasma treatment could provide a stable sensing system with low background noise, which can be used for label-free detection. In the next phase of the dissertation, for the first time, the C-MEMS electrode functionalized with oxygen-plasma was adopted for ssDNA aptamer-based biosensors (aka. aptasensors). The attained results confirmed that the developed aptasensors are highly sensitive, selective, and robust, and the developed system is adaptable for turn-on and turn-off sensing strategies. In the following phase of the dissertation, the adaptability of the bipolar exfoliated graphene for aptasensors was investigated. The achieved results revealed that the graphene deposited on a negative feeding electrode (i.e., reduced graphene oxide) is more suitable for label-free electrochemical aptasensing. Hence, POC PDGF-BB aptasensors based on bipolar reduced graphene oxide were developed and investigated for the first time. The achieved results were highly promising for feasible POC cancer aptasensors. The last phase of this dissertation explores the in-situ integration of bipolar exfoliated graphene on C-MEMS microelectrodes. The biosensor developed based on this integration showed enhanced sensitivity. In the present dissertation, novel carbon-based biosensors were developed and optimized. The achieved results show the high potential of C-MEMS and bipolar exfoliated graphene-based biosensors for label-free POC cancer biomarker biosensing.




Previously Published In

Shahrzad Forouzanfar, Nezih Pala, Marc Madou, Chunlei Wang, Perspectives on C-MEMS and C-NEMS Biotech Applications, 2021, Biosensors and Bioelectronics, doi:10.1016/j.bios.2021.113119

Shahrzad Forouzanfar, Fahmida Alam, Nezih Pala, Chunlei Wang, Highly Sensitive Label-Free Electrochemical Aptasensors Based on Photoresist Derived Carbon for Cancer Biomarker Detection, 2020, Biosensors and Bioelectronics, doi: 10.1016/j.bios.2020.112598

Shahrzad Forouzanfar, Fahmida Alam, Nezih Pala, Chunlei Wang, A Review of Electrochemical Aptasensors for Label-Free Cancer Diagnosis, 2020, Journal of The Electrochemical Society, doi: 10.1149/1945-7111/ab7f20

Shahrzad Forouzanfar, Fahmida Alam, Iman Khakpour, Amin Rabiei Baboukani, Nezih Pala, and Chunlei Wang, Highly Sensitive Lactic Acid Biosensors Based on Photoresist Derived Carbon, IEEE Sensors Journal, 2020, doi: 10.1109/JSEN.2020.2988383


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