Plasmonic Gold Decorated MWCNT Nanocomposite for Localized Plasmon Resonance Sensing
Bibliographic record
Abstract
The synergism of excellent properties of carbon nanotubes and gold nanoparticles is used in this work for bio-sensing of recombinant bovine growth hormones (rbST) by making Multi Wall Carbon Nanotubes (MWCNT) locally optically responsive by augmenting it optical properties through Localized Surface Plasmon Resonance (LSPR). To this purpose, locally gold nano particles decorated gold-MWCNT composite was synthesized from a suspension of MWCNT bundles and hydrogen chloroauric acid in an aqueous solution, activated ultrasonically and, then, drop-casted on a glass substrate. The slow drying of the drop produces a "coffee ring" pattern that is found to contain gold-MWCNT nanocomposites, accumulated mostly along the perimeter of the ring. The reaction is studied also at low-temperature, in the vacuum chamber of the Scanning Electron Microscope and is accounted for by the local melting processes that facilitate the contact between the bundle of tubes and the gold ions. Biosensing applications of the gold-MWCNT nanocomposite using their LSPR properties are demonstrated for the plasmonic detection of traces of bovine growth hormone. The sensitivity of the hybrid platform which is found to be 1 ng/ml is much better than that measuring with gold nanoparticles alone which is only 25 ng/ml.
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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".