FePt Alloy Nanoparticles for Biosensing: Enhancement of Vitamin C Sensor Performance and Selectivity by Nanoalloying
Bibliographic record
Abstract
Electrocatalytic activity of supported FePt alloy nanoparticles (NPs) with different compositions (Fe25Pt75, Fe30Pt70, Fe35Pt65) for the electro-oxidation of vitamin C is investigated. These spherical FePt NPs with nanocrystallite size of 7-9 nm are found to consist of a nanoalloy core with a more Pt-rich shell. The FePt alloy NPs are superior catalysts than Pt NPs for vitamin C electro-oxidation, with a linear concentration range of 0.01-1 mM, a high sensitivity of 4.347 mA cm(-2) mM(-1), and a low detection limit of 0.1 μM (S/N = 3). By effectively reducing the overpotential for the electro-oxidation, these alloy NPs are significantly more selective to the detection of vitamin C against other common interference species, including dopamine, citric acid, uric acid, glucose, and NaCl. Enhancement in sensor performance can be attributed to the increase in surface area due to reduction of nanocrystallite size and to modification in the Pt electronic structure as a result of nanoalloying. These are supported by the X-ray diffraction data and binding energy shifts as observed by X-ray photoelectron spectroscopy, respectively. Alloying therefore represents a powerful approach to introduce synergetic properties for new biosensor applications.
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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".