An Azomethine-H-Based Fluorogenic Sensor for Formic Acid
Bibliographic record
Abstract
Formic acid (FA) is an important C 1 -containing feedstock that serves as a masked source of dihydrogen gas (H 2 ). To encourage the adoption of cleaner (noncarbonaceous) energy sources, FA detection and sensing is thus of considerable interest. Here, we examine the use of a commercially available dye, azomethine-H (Az-H), for FA sensing. Solution studies confirm that FA quenches both the absorbance and the luminescence properties of Az-H. FA was additionally found to attenuate a known Az-H ( E )-to-( Z ) conformational change, suggesting an Az-H/FA interaction, possibly through hydrogen bonding; this phenomenon was probed using 1 H NMR spectroscopy. Moving toward a solid-state sensor, the Az-H probe was incorporated into a gelatin-based matrix. On exposure to FA, the luminescence of this system was found to increase in a FA-dependent manner, attributed to the formation of stable hydrogen-bonded structures, facilitating a ( Z )-to-( E ) isomerization via imine protonation, allowing for production of the more luminescent ( E )-isomer. This fluorogenic signal was used as a FA sensor with an estimated detection limit of ca. 0.4 ppb FA vapor. This work constitutes an important step toward a highly sensitive FA sensor in both the solution and solid state, opening new space for the detection of organic acids in differing chemical environments.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".