The Effect of Counterions on the Detection of Cu2+ Ions in Aqueous Solutions Using Quartz Tuning Fork (QTF) Sensors Modified with L-Cysteine Self-Assembled Monolayers: Experimental and Quantum Chemical DFT Study
Bibliographic record
Abstract
In this study, a sensing device employing a gold-coated quartz tuning fork (QTF) modified with a self-assembled monolayer (SAM) of L-cysteine was evaluated for the sensitive detection of Cu2+ ions in aqueous solutions. Three copper (II) salts, CuSO4, CuCl2, and Cu(NO3)2, at four different concentrations (10−12, 10−10, 10−8, and 10−6 M) in small (100 μL) water sample amounts were each used as analytes to investigate the influence of their counterions in the detection of the Cu2+ ions. It was found that, among the counterions, the sulfate anion had the largest effect upon the detection of Cu2+ in water, in the following order: SO42− > Cl− > NO3−. The lower limit of detection of the Cu2+ ions detected was in the 10−12 M range. The frequency shifts measured with the QTFs relative to deionized water were inversely proportional to the concentration/mass of the analytes. Density functional theory calculations were conducted to understand the effect of the counterions on the respective electronic interaction energies for the apparent host–guest binding of the analytes with L-cysteine and with gold surface-bound L-cysteine molecules. Gas phase (both with and uncorrected BSSE) and solution phase interaction energies (ΔIE) calculated at the B3LYP/LANL2DZ and ωB97XD levels of theory showed that the stability for the complexes were in the following order: [L-cysteine]⊃[CuSO4] > [L-cysteine]⊃[CuCl2] > [L-cysteine]⊃[Cu(NO3)2], which supports our experimental findings, as they were in the same order as the experimentally observed order for the copper salts tested: CuSO4 > CuCl2 > Cu(NO3)2.
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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 | 0.001 |
| 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".