Ultrasensitive electrochemical phosphate detection by pyridine–zinc(II) complex
Bibliographic record
Abstract
Phosphorous is an important environmental health parameter as the availability of phosphorus within water systems plays an essential role in the prevalence of harmful algal blooms (cyanobacteria blooms). Currently, phosphates are detected using sensitive chromatographic and colorimetric techniques; however, major disadvantages stem from the lack of anion selectivity in samples with complex matrices, as well as the high cost of analysis. Electrochemical techniques utilizing self-assembled monolayers can provide a cheaper yet sensitive method of detection. This work explores the modification of a gold working electrode using pyridine–zinc(II) complexes. The implementation of self-assembled monolayers allows for an ultrasensitive and selective method of indirect detection of the H2PO4 − species, ranging in concentrations between 0.0 and 1.2 fmol/L phosphate. Electrochemical techniques such as cyclic voltammetry and square-wave voltammetry were explored for their phosphate-detection abilities, with detection limits of 4.0 × 10−16 and 9.0 × 10−17 mol/L H2PO4 −, respectively. X-ray photoelectron spectroscopy measurements were also taken to confirm the modification of the electrode. The selectivity of this sensor towards phosphate anions was successfully explored for this sensor in the presence of potential interfering agents (sulfate, chlorine, carbonate, fluoride, nitrite, and hypochlorite ions), and applicability of sensor was also explored through the detection of phosphate in a tap and lake water sample.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".