Tight-Anchoring of Gold Nanoparticles to Polymer-Wrapped Semiconducting Single-Walled Carbon Nanotubes for Biosensor Applications
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Conjugated polymer-sorted semiconducting single-walled carbon nanotubes (sc-SWCNTs) are excellent materials for electronic biosensors due to their high electrical conductivity and sensitivity and can be integrated into electrolyte-gated field-effect transistor (EGFET) sensors. Operation of electronic biosensors in bodily fluids is challenging because of the short Debye length (λ D ) in high ionic strength media. The receptor attached to the sc-SWCNT is a crucial component of the biosensor, and sensor performance depends on efficient signal transduction between the receptor and the sc-SWCNT. In this work, we grew Au nanoparticles (NPs) on sc-SWCNTs wrapped with a copolymer of fluorene and 2,2’-bipyridine (BPy), poly(9,9-di- n -dodecylfluorenyl-2,7-diyl- alt -2,2′-bipyridine-5,5′) (PFBPy-5,5′). AuNPs were anchored to the BPy ligands in the polymer backbone, realizing an efficient electrical connection between the AuNPs and the sc-SWCNTs. Cortisol sensors were prepared by coupling a thiol-terminated cortisol aptamer to the AuNPs and integrating the Aptamer/AuNP/sc-SWCNT@PFBPy-5,5′ complex into an EGFET. The sensor exhibited a concentration-dependent increase in source-drain current upon increasing cortisol concentration from 1 to 1000 nM. A control sensor was prepared using sc-SWCNTs wrapped with a fluorene homopolymer, poly(9,9-dodecylfluorene) (PFDD), which does not have a ligand that AuNPs can anchor. The control Aptamer/AuNP/sc-SWCNT@PFDD sensor showed only a weak concentration-dependent response. A further control was prepared using sc-SWCNTs@PFDD with the aptamer covalently attached to the nanotube’s sidewall. The Covalent-Aptamer/sc-SWCNT@PFDD control sensor exhibited a concentration-dependent response, albeit to a lesser extent than the Aptamer/AuNP/sc-SWCNT@PFBPy-5,5′ system. The results indicate that tight-anchoring of AuNPs in the Aptamer/AuNP/sc-SWCNT@PFBPy-5,5′ system provides a crucial contribution to the proposed sensing mechanism: (1) upon cortisol recognition, the aptamer undergoes a structure-switch where the negatively charged backbone is brought within or near the Debye length at the AuNP surface, altering the interfacial capacitance and electrostatically gating the AuNP and (2) efficient signal transfer between the AuNPs and sc-SWCNTs@PFBPy-5,5′.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".