Porous Nanostructured Chromium-Doped Tungsten Oxide Electrocatalysts for Flutamide and Nilutamide Detection
Bibliographic record
Abstract
In the present study, an electrochemical sensor based on a Cr-doped WO 3 nanostructure was designed and exploited for pharmaceutical drug analysis. Cr-doped WO 3 nanostructures were prepared by treating the W and Cr precursors with hydrothermal condensation. A thorough characterization was conducted for structural and elemental insights using scanning electron microscopy, X-ray powder diffraction, transmission electron microscopy, and X-ray photoelectron spectroscopy methods. The optimized electrochemical response was obtained with 1.68 atom % of Cr in the WO 3 lattice. The developed nanoparticles were employed in the electrochemical detection of antiandrogen drugs such as flutamide (FLTM) and nilutamide (NLTM) using cyclic voltammetry and square wave voltammetry techniques. The developed sensor was employed to evaluate the physiochemical and thermodynamical parameters of the voltammetric process by investigating the effect of scan rates and temperatures on the quasi-reversible signals of FLTM and NLTM. The Cr-WO 3 /CPE shows a sensitivity of 24.9 and 49.1 μA μM –1 cm –2 for FLTM and NLTM with detection limits of 4.2 and 3.07 nM, respectively. The sensor was employed to detect the desired drug moiety in the urine samples (real and synthetic) and pharmaceutical drugs; the good recovery values demonstrating the applicability and selectivity of the sensor were supported by excipient interference investigation. Thus, the developed sensor and methods hold potential for future research in identifying additional bioactive molecules in pharmaceutical and clinical trials.
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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".