Effect of hydroxypropyl methylcellulose and ferric chloride on hypergolic ignition of solidified ethanol fuels
Bibliographic record
Abstract
• Hypergolic ignition of reaction-driven solidified fuels with varying concentrations of hydroxylpropyl methylcellulose and ferric chloride has been investigated for the first time. • FTIR and TGA techniques has been used to study molecular interactions between hydroxylpropyl methylcellulose and ferric chloride. • Hypergolic ignition delay tests with 90 % H 2 O 2 reduced ignition delay with increase in the concentration of gellant and dopant. • Higher fuel temperature improved spreading and wetting behavior of H 2 O 2 droplets. • Solidification of ethanol using HPMC with FeCl 3 eliminates the need for a separate catalyst. This study investigates the hypergolic ignition of reaction-driven solidified ethanol (RDSE) fuels, focusing on the effects of varying concentrations of hydroxypropyl methylcellulose (HPMC) gellant and ferric chloride (FeCl 3 ) dopant. Fourier Transform Infrared Spectroscopy (FTIR) and thermogravimetric analysis (TGA) are employed to examine molecular interactions and thermal properties. FTIR results indicate that no new covalent bonds are formed upon adding FeCl 3 , whereas interactions primarily governed by weak hydrogen and ionic bonds. The apparent activation energy ( E a ) has been determined for the fuel samples using iso-conversional model-free kinetics approach and found that E a decreased with HPMC and FeCl 3 concentrations. Hypergolic ignition delay tests were attempted with the droplet study rocket grade hydrogen peroxide (90 % RGHP; H 2 O 2 ) as an oxidizer, demonstrated that increasing HPMC concentration by 3 wt.% reduced ignition delay by ∼20 %, while a 5 wt.% increase in FeCl 3 concentration led to a ∼25 % reduction. Higher fuel temperatures enhanced the wetting and spreading behavior of H 2 O 2 droplets, improving oxidizer-fuel interaction and reducing ignition delay. Overall, solidification of ethanol using HPMC with FeCl 3 eliminates the catalyst as FeCl 3 acts as both catalyst and binding agent.
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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 | 0.000 |
| 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".