Hygroscopicity of nitrocellulose with different nitrogen content
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Research on the hygroscopic behavior of NC is essential because it affects the mechanical properties, combustion properties, and safe storage of NC‐based products. In this study, Fourier transform infrared spectroscopy (FTIR), X‐ray diffraction (XRD), and scanning electron microscopy (SEM) are used to characterize the chemical structure, crystal structure, and microscopic morphology of NC, respectively. The moisture adsorption isotherms of NC fibers with different nitrogen content are determined by dynamic vapor sorption (DVS) and fitted with Hailwood‐Horrobin (H−H) and Guggenheim‐Anderson‐de Boer (GAB) models. The specific surface area and surface energy of NC are also measured by inverse gas chromatography (IGC). The results show that as the nitrogen content of NC increases, the intensity of the −OH characteristic absorption peak is weakened, the crystallinity does not change much, the number of cracks and pores on the NC fiber surface increases, and the equilibrium moisture content (EMC) of the NC decreases in general. In addition, the fitting results based on the H−H and GAB models show that, under low humidity conditions, the EMC value of NC is determined by the adsorbed water content of the monolayer, which is mainly related to the −OH content in NC. However, with the increase of humidity, the EMC value of NC is gradually determined by the multilayer adsorbed water content, which is influenced by both the nitrogen content and the fiber cleavage structure. Meanwhile, the IGC results show that the surface energy of the NC consists mainly of the dispersive surface energy (values >46 mJ m −2 ), with the specific surface energy contributing approximately 25 mJ m −2 . The total surface energy of NC and the bonding strength between NC molecules and water molecules decrease with increasing nitrogen content.
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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) | 0.001 | 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 it