Nanoscale Patterning of Graphene Field-Effect Transistors for Single-Molecule Functionalization and Time Series
Bibliographic record
Abstract
With the discovery of low-dimensional materials, the extreme miniaturization of field-effect transistors (FETs) has revealed such devices as powerful sensors for experiments at the single-molecule scale. In particular, FET devices functionalized with an individual molecule have been able to record, via fluctuations in the electrical conductance, various types of single-molecule dynamic changes, for example enzymatic activity 1 DNA hybridization 2,3 or DNA folding 4 . So far, such studies have mostly been carried out with FETs based on 1D materials such as carbon nanotubes (CNTs) or silicon nanowires (SiNWs). The 1D geometry of these materials facilitates the capture of a 0D molecule and provides enhanced sensitivity of the conductance to the functionalized site. However, FETs based on 1D materials often present scalability issues, due to challenges in controlling their growth and/or assembly. Here, we propose an approach based on nanoscale patterning of a 2D material to assemble FET arrays compatible for single-molecule capture and detection. First, we report wafer-scale microfabrication of arrays of graphene field-effect transistors (GFETs) with micron-scale channels. Like its 1D counterpart, graphene presents a high and sensitive electrical conductivity as well as carbon-based surface chemistry for single-molecule functionalization. GFET arrays were built from high-quality graphene synthesized by chemical vapor deposition (CVD) and transferred using a custom automated process on patterned electrodes. Then, we describe the nanoscale patterning of graphene channels in nanoconstrictions suitable for single-molecule functionalization and sensitivity. Using electron-beam lithography (EBL) and deep reactive ion etching (DRIE), we were able to produce a combination of high-resolution features in graphene (<100nm) as well as nanofluidics reactions chambers (<50nm), to promote single-molecule chemistry on the graphene. We will present our recent results in functionalizing these nanoconstrictions with single-stranded DNA and in collecting high-resolution electrical time series from these constructs. Finally, we will discuss the performance of such graphene-based devices for single-molecule experiments. Bibliography Choi, Y., Weiss, G. A. & Collins, P. G. Single molecule recordings of lysozyme activity. Physical Chemistry Chemical Physics (2013). doi:10.1039/c3cp51356d Sorgenfrei, S. & Shepard, K. L. Label-free field-effect-based single-molecule detection of DNA hybridization kinetics. Nat. Nanotechnol. 6 , 126–132 (2011). Vernick, S. et al. Electrostatic melting in a single-molecule field-effect transistor with applications in genomic identification. Nat. Commun. 8 , 1–9 (2017). Bouilly, D. et al. Single-molecule reaction chemistry in patterned nanowells. Nano Lett. 16 , 4679–4685 (2016).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".