Nanopore sensing platform development

Despite many years’ research, there are still a lot to be studied in solid-state nanopore sensing. Conventionally, the most popular nanopore platform is made of silicon nitride (SiN) membranes on Si substrates, because of its well-established fabrication processes. However, this nanopore architecture faces intrinsic challenges in producing thin and stable membranes for high signal detection, and has a high substrate-related large capacitive noise. One thrust in my lab is to create sapphire-supported nanopores towards low-noise high-speed molecular sensing.

Triangular membranes in sapphire

We decided to study sapphire over fragile lipid bilayer or conventional silicon as the nanopore substrate for its high structural stability and low conductivity. This low conductivity significantly reduces device capacitance at the electrolyte interface by more than two orders of magnitude compared to Si. This accordingly decreases the capacitive noise that becomes dominant at high frequency and challenges high-speed sensing. Yet, creating a suspended membrane on sapphire requires bulk etching, which is very challenging and previously unavailable due to high chemical resistance of sapphire. To this end, we have spent great efforts to develop a technique for wet sapphire etching in boiling sulfuric and phosphoric acids, which is a batch-processing-compatible and wafer-scale MEMS process not attainable on other non-crystalline insulators (e.g., glass). In particular, we introduced novel triangular- and hexagonal-shaped etching windows to create triangular-shaped dielectric membranes. With this new design strategy, we demonstrate successfully tunable control of the membrane dimension in a wide range from ~200 μm to as small as 5 μm, which corresponds to <1 pF membrane capacitance for a hypothetical 1-2 nm thick membrane. Further, we have demonstrated that a sapphire nanopore chip has more than two-order-of-magnitude smaller device capacitance (2 to 10 pF) compared to a float-zone Si based nanopore chip (~1.3 nF), despite having a 100 times larger membrane area. The sapphire chip has a current noise a few times smaller than that from the Si chip and only slightly larger than the open-headstage system noise (~11 pA). The sapphire nanopore chip outperforms the Si chip with a higher signal-to-noise ratio, and have great promise in nucleic acids and protein sensing.

Reference:

1. Pengkun Xia, Jiawei Zuo, Pravin Paudel, Shinhyuk Choi, Xiahui Chen, Md Ashiqur Rahman Laskar, Jing Bai, Weisi Song, JongOne Im, and Chao Wang *, “Sapphire-Supported Nanopores for Low-Noise DNA Sensing,” Biosensors and Bioelectronics, v 174, pp. 112829, 2021.
2. Pengkun Xia, Md Ashiqur Rahman Laskar, and Chao Wang*, “Wafer-Scale Fabrication of Uniform, Micrometer-Sized, Triangular Membranes on Sapphire for High-Speed Protein Sensing in a Nanopore,” ACS Appl. Mater. Interfaces, v 15, pp. 2656–2664, 2023.

Ongoing work: single-molecule protein sequencing

Despite the success in development of nucleic acids sequencing technologies, there is a lack of fast, low-cost, and accessible technologies for rapid identification and quantification of proteins. Proteins are more complex in structure compared to DNA, with 20 distinctive amino acids (AAs) as the building blocks, making it challenging to directly translate DNA sequencing technologies (e.g. by four-color fluorescence imaging) into AA detection. Further, proteomic analysis is complicated by the large dynamic range in protein expression levels, lack of polymerase chain reaction-like amplification methods, cellular heterogeneity, post-translational modifications, and inter-individual variations due to mutations. Single-molecule protein sequencing (SMPS) is an emerging research direction that directly reads AA sequence from individual protein or peptide molecules. It has the potential to revolutionize proteomics research, providing ultimate sensitivity for the detection of low-abundance proteins at single-cell level. With the recent NIH Director’s New Innovator Award (DP2 GM149552, $1.5M direct cost, or about >$2.2M in total cost), I will develop an electronic SMPS system that incorporates nano-opto-fluidic structures to transduce protein fingerprints into electronic signals at a high speed, a low cost and a small system foot-print. Our platform features a sapphire-supported nanopore fluidic device that is suited for high-speed, low-noise, electronic detection. Further, we will create an ultrathin nitride-based metasurface-integrated circuit (MIC) structure on the nanopore to optically interrogate the fluorescently tagged AAs passing through the nanopore. MIC functionally replaces bulky microscopes by converting the optical signals of tagged AAs into electronic readout at single molecule level.  The optoelectronic channel (for AA tags) and ionic current channel (for protein primary structure) will be synchronously recorded to determine the AA sequences. On the system level, we aim to build a portable instrument incorporating circuitry with a footprint of a USB dongle that integrates fluidic cell for sample handling and electronic circuits for signal processing (digitation, amplification, storage, data transfer, etc.). The SMPS platform will provide high-quality and low-cost data in proteomic information, with broad applications in drug discovery, disease diagnosis, and personalized medicine.

Reference:

1. ASU researcher advances the science of protein sequencing with NIH Innovator Award | ASU News
2. New Innovator Award Recipients (nih.gov)

Ongoing and future work

In addition, we will seek to work on novel material and device architecture designs for nanopore sensors in other applications. For example, we will investigate the feasibility of integrate III-nitride semiconductor materials, such as gallium nitride and aluminum nitride, as stable and ultrathin (5 to 10 nm) membranes on sapphire. Such III-nitride materials can be deposited with precisely controlled thicknesses using well-established techniques for electronic devices, including molecular beam epitaxy (MBE), atomic layer deposition (ALD), etc. We will explore different manufacturing techniques, including photolithography, electron-beam lithography (EBL), controlled dielectric breakdown, and laser drilling, to scalarly create nanopores in the membranes. We will also explore the integration of microfluidic channels with nanopores to improve the fluidic control and enhance the molecular detection rates. The use of standard semiconductor manufacturing techniques will ensure reproducible and inexpensive manufacturing of the proposed nanopore sensors. On the other hand, we will work to chemically functionalize the fabricated nanopore sensors for selective peptide, protein, antibody, and nucleic acids detection. Lastly, machine learning techniques, such as convolutional neural network (CNN) and recurrent neural networks (RNN), will be used to improve the detection accuracy.