Bimetallic CoFe Borides: A New Pathway for the Transformation of Amorphous Borates to Metallic Borides for the Determination of Paracetamol
Bibliographic record
Abstract
The development of transition metals as electrode materials that can exhibit good conductivity and fast electron transfer ability through electroactive sites is highly desirable because high sensitivity and selectivity can be achieved. When compared to other nonmetals, boron (B) possesses a lower electronegativity (χB-2.04) than carbon (χC-2.55), nitrogen (χN-3.04), and oxygen (χO-3.44) and thus forms a covalent linkage with electron-rich transition metals (Co or Fe) to form monometallic or bimetallic borides (CoB/FeB or CoFeB). However, the formation of crystalline bimetallic borides using conventional synthesis approaches is highly challenging. In this regard, for the first time in the present work, we developed crystalline bimetallic cobalt–iron boride (CoFeB) with nanostructure features via a chemical reduction and thermal annealing process as an efficient electrode material for the electrochemical detection of paracetamol. After the postannealing process, the obtained amorphous borates (CoFeOBO 3 ) are transformed into a highly crystalline form composed of bimetallic borides as revealed from X-ray diffraction (XRD) analysis. The resultant CoFeB coated on a screen-printed electrode (SPE) showed well-defined oxidation and reduction peaks with potentials of about E pa = +0.51 V and E pc = +0.44 V (vs Ag/AgCl) for paracetamol (pH = 7.2). At an optimized applied potential of +0.60 V (vs Ag/AgCl), a linear i – t response for paracetamol was observed from 0.01 μM to 2.7 mM with a good sensitivity of 64.79 μA mM –1 cm –2 and a low detection limit of 3.8 nM. In addition, CoFeB/SPE is found to be tolerable against interference species and shows agreeable repeatability and durability. Based on these results, the present work could develop a facile approach to producing a variety of metallic borides by tuning the composition of various transition elements, where high conductivity and stability are required in various electrocatalytic and electrochemical applications.
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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".