Hemicyanine-based fluorescent probes with ratiometric and turn-on responses for selective and sensitive detection of Hg2+: A combined experimental and DFT study
Bibliographic record
Abstract
Mercury and its compounds are among the most well-known toxic heavy metal pollutants. Even trace amounts of mercury are known cause severe health effects by irreversibly targeting the central nervous system in humans. In particular, Hg 2+ has been extensively researched to improve its detection in a variety of matrixes. Due to their high sensitivity, small-molecule fluorescent probes that can rapidly and accurately detect Hg 2+ ions are of particular interest. In the present study, two new fluorescent probes (PN-PTC and PN-DMTC) were designed and synthesized for selective Hg 2+ detection. PN-PTC features a pyridinium-naphthalene-phenyl thiocarbonate structure, while PN-DMTC incorporates a pyridinium-naphthalene-dimethyl thiocarbamate motif. Upon Hg 2+ binding, PN-PTC exhibited a ratiometric fluorescence response accompanied by a visible color transition from blue to yellow, whereas PN-DMTC showed a significant fluorescence turn-on effect. The Hg 2+ recognition mechanism, involving a Hg 2+ -promoted desulfurization-hydrolysis reaction, was confirmed through 1 H NMR, HRMS and FT-IR analysis of the hydrolysis products. Both probes showed excellent fast response times, large Stokes shifts, high sensitivity (nM limits of detection), and excellent selectivity for Hg 2+ . Additionally, density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations were conducted to elucidate the electronic basis of the Hg 2+ sensing. Frontier molecular orbital (FMO) analysis, molecular electrostatic potential (MEP) mapping, and simulated absorption/emission spectra corroborated the experimental results. The combined data confirmed that both intramolecular charge transfer (ICT) and photoinduced electron transfer (PET) are involved in the sensing mechanism. Finally, both probes demonstrated reliable performances in detecting Hg 2+ in real water samples, highlighting their practical utility for environmental monitoring. • Two hemicyanine probes enable Hg 2+ detection via desulfurization-hydrolysis. • Different recognition groups lead to distinct Hg 2+ sensing performances. • High selectivity, excellent sensitivity and rapid responses, with low LODs. • Density functional theory calculations verified the sensing behavior.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".