Addressing Scalability, Stability, and Sensitivity in Nanomaterial-based Electronic Biosensors
Abstract
The inaccessibility of medical facilities in remote locations has pushed for scientific advances in the development of point-of-care (POC) systems that would enable timely and accurate detection of diseases. Currently, diagnostic tests rely heavily on the use of centralized primary care facilities due to the need for expensive, bulky, and complex diagnostic tools, leading to greater disparity in outlook between individuals with access to centralized medical facilities and those in remote or underserved locations. Electrical biosensors, including transistor-based devices (i.e., BioFETs), have the potential to offer versatile biomarker detection in a simple, low-cost, and POC manner. Semiconducting carbon nanotubes (CNTs) are among the most explored nanomaterial candidates for BioFETs owing to their high electrical sensitivity and compatibility with diverse fabrication approaches such as direct-write printing, which enables rapid and low-cost fabrication of electronics. However, while CNT-based BioFETs have the power to transform the medical landscape by providing early and POC disease detection, they face several key challenges that have hindered their mass proliferation as diagnostic tools. Among these, challenges in scalability, stability, and sensitivity present a significant hinderance to their utility.
The work presented in this dissertation focuses on tackling these three key BioFET issues. The issue of scalability in printed BioFETs means that to date, there has been difficulty in achieving down-scaled printing of the transistor (the transduction component of the BioFET), particularly to submicron dimensions, due to the limited resolution of current printing techniques (10-30 µm). Overcoming this limitation is important for BioFETs as a large device area means that large patient samples (i.e., blood) are required, with a greater likelihood for differences in signal across various regions of the BioFET, preventing accurate detection. In this dissertation, a novel capillary flow printing (CFP) technique is used to repeatably create fully printed submicron carbon nanotube thin-film transistors (CNT-TFTs). The versatility of this printing technique is demonstrated by printing conducting, semiconducting, and insulating inks – the three necessary components for creating BioFETs – on several types of substrates (SiO2, Kapton, and paper) and through the fabrication of various device architectures. Notably, CFP of these submicron CNT-TFTs yielded on-currents of 1.12 mA/mm, demonstrating the strong transistor performance achievable with CFP. This work highlights the ability of CFP as a viable fabrication method for down-scaled printed transistors (and thus BioFETs), helping overcome BioFET scaling limitations.
Next, stability limitations of BioFETs are addressed through exploration of various passivation strategies. The incompatibility of electronic devices with ionic liquids (including blood, saliva, etc.) presents a challenge to the stability of BioFETs, and this is especially evident in the presence of detrimental leakage currents in solution-gated devices, which often obscure signal detectability. The work presented in this dissertation highlights this often-ignored incompatibility, and points to its responsibility in creating instability for BioFETs in ionic solutions as well as hindered performance characteristics. By exploring the effects of various passivation strategies on the performance and stability of a CNT BioFET, this work finds that encapsulating metal contacts with a thick photoresist (SU-8) and a thin high-k dielectric (HfO2) over the entire chip provides the lowest average leakage current in solution (~2 nA), best initial performance metrics, large-scale device yield, and stability throughout long-duration cycling in phosphate buffered saline. This finding not only provides insight into the importance of passivation strategy in solution-gated devices, particularly with BioFETs, but also enabled the creation of a robust CNT-based biosensing platform that was then used to tackle another stability limitation: signal drift. As binding events take place in a complex milieu above a BioFET, time-based drift of the sensor response can occur, obscuring biomarker detection and adversely affecting device performance. However, as shown in this work, these effects are drastically mitigated through the implementation of a rigorous testing methodology. Thus, by highlighting these often-ignored sources of BioFET instability and demonstrating ways of overcoming them, this work paves the way toward stable and reliable BioFETs.
Finally, BioFET sensitivity is improved using a Debye length extending polymer in conjunction with a novel D4-TFT device architecture. One of the main hindrances to electronic biosensing is Debye length screening, where counterions in an ionic solution form an electrical double layer around the BioFET and obscure charge detection. By growing a polyethylene glycol-like polymer brush interface (POEGMA) above the BioFET surface, the Debye length is significantly increased (from ~0.7 nm to upwards of 25 nm), allowing for accurate detection of large antibody-antigen complexes. When combined with a self-amplifying D4-TFT structure, this enabled realization of one of the highest sensitivities demonstrated in a stable antibody-based BioFET to date (22 aM).
The findings of this dissertation present a key step toward solving a few of the most pertinent issues to the field of electronic biosensing. While BioFETs hold high promise in changing the medical landscape through the widespread use of POC biosensors, they can only be achieved if fundamental issues like scalability, stability, and sensitivity are addressed. Combined, the contributions outlined in this dissertation make significant progress toward that goal, paving the way toward the development of a robust, dependable, and accurate POC BioFET.
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Albarghouthi, Faris Maher (2024). Addressing Scalability, Stability, and Sensitivity in Nanomaterial-based Electronic Biosensors. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/31942.
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