Interfacial Super-Assembly of Nanofluidic Heterochannels from Layered Graphene and Alumina Oxide Arrays for Label-Free Histamine-Specific Detection
Bibliographic record
Abstract
Nanofluidic devices with well-defined channels have shown great potential for biosensing, separation and, energy conversion. Recently, two-dimensional (2D) materials have been widely used for constructing novel nanofluidic devices owing to their high specific surface, abundant surface charge, and low cost. However, 2D-based nanofluidic devices for highly sensitive biosensing have drawn little attention. Herein, we developed a 2D material-based nanofluidic heterochannel with an asymmetric T-mode nanochannel structure and surface charge polarization distribution. This heterochannel was composed of layered graphene oxide modified with Nα, Nα-bis(carboxymethyl)-l-lysine (containing metal-nitrilotriacetic chelates, NTA) and an oxide array (NTA-GO/AAO), which can achieve remarkable selectivity, specificity, and label-free detection of the neurotransmitter histamine based on a metal ion displacement mechanism. A detection limit of 1 nM can be obtained using the NTA-GO/AAO heterochannel. This study provides a simple and label-free platform for developing a 2D-based nanofluidic heterochannel for specific molecular detection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".