Preparation and Characterization of Aqueous Nanothermite Inks for Direct Deposition on SCB Initiators
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Nanothermites are a promising replacement energetic for many devices but their use has been limited by high sensitivity during processing, hazardous processing solvents, and time consuming deposition. Incorporating processing and deposition into a single step, especially if no organic solvents were used, could allow nanothermites to be applied safely in a wider range of applications. This work reports on the performance and characterization of direct‐deposited water processed nanothermite inks on semiconductor bridge (SCB) initiators. Specifically, it investigates the replacement of nanothermites processed by resonant mixing (Resodyn LabRAM) in the solvent N , N ‐dimethylformamide (DMF) with nanothermites processed in water. Processing safety and mixture performance were then characterized. It was found that water processed nanothermites were stable for up to 480 min in a water bath at 50 °C only if both metal and metal oxide particles were coated with palmitic acid. In addition, water processed nanothermites were found to have better mixing intimacy, which resulted in better performance than nanothermite processed in DMF. Direct deposition of water processed nanothermites also mitigates electrostatic discharge (ESD) sensitivity, while the material remains wetted, improving processing safety dramatically. For the system investigated, it was found that processing at a solids loading of 30 vol.% resulted in a high density, high performance ink that was deposited directly onto the SCBs. This resulted in a 25 % reduction in the all fire threshold over traditional energetics. This mixing approach uses an environmentally friendly mixing medium, can result in a higher density final material, and allows safe one‐step mixing and deposition.
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.
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 it