Synthesis and Characterization of Ethyl Formate Precursor for Activated Release Application
Bibliographic record
Abstract
Ethyl formate (EF) is a generally recognized-as-safe flavoring agent commonly used in the food industry. It is a naturally occurring volatile with insecticidal and antimicrobial properties, promising as an alternate fumigant to methyl bromide which is undesirable due to its ozone depletion in the stratosphere and toxic properties. However, EF is highly volatile, flammable, and susceptible to hydrolytic degradation. These properties present considerable end-use challenges. In this study, a precursor of EF was synthesized via the condensation reaction of adipic acid dihydrazide and triethyl orthoformate to form diethyl N,N′ -adipoyldiformohydrazonate, as confirmed by Fourier transformed infrared and solid-state nuclear magnetic resonance spectroscopies. Differential scanning calorimetry analysis showed that the precursor had a melting point of 174 °C. The physical properties of the precursor were studied using scanning electron microscopy and dynamic light scattering analysis, which showed that the precursor was made up of agglomerated particulates with irregular shapes and sizes. The resulting precursor was nonvolatile and remained stable under dry conditions but could be hydrolyzed readily to trigger the release of EF. The release behaviors of EF from the precursor was evaluated by citric acid-catalyzed hydrolysis, showing that 0.38 ± 0.008 mg EF/mg precursor was released after 2 h at 25 °C, representing about 98% of the theoretical loading. Both EF release rate and its total release amount decreased significantly ( p < 0.05) with decreasing temperature and relative humidity. The conversion of the highly volatile EF into a solid-state precursor, in conjunction with the activated release strategy, can be useful for controlled release of EF for fumigation and other applications in destroying insect pests and inhibiting the proliferation of spoilage microorganisms.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".