Bibliographic record
Abstract
The ability to integrate ceramics with other materials has been limited by the high temperature s (>800degC) associated with ceramic processing. A novel process , known as aerosol deposition (AD), capable of preparing ceramic films at room temperature (RT) has been the subject of recent interest in the thermal spray and microelectronics communities. In this process, ceramic part icles are accelerated using pressurized gas, impacted on a substrate and form a dense film under vacuum. This revolutionary process eliminates high temperature processing, enabling new coatings and microelectronic device integration as a back end of line p rocess, in which ceramics can be deposited on metals, plastics, and glass es . Future impact s of this technology on Sandia's mission could include improved ceramic integration, miniaturized magnetic circulators in radar applications, new RF communication pro ducts, modification of commercial - off - the - shelf electronics, fabrication of conformal capacitors, thin batteries, glass - to - metal seals, and transparent electronics. Currently, optimization for RT solid - state deposition of ceramics is achieved empirically and fundamental mechanisms for ceramic particle - particle bonding are not well understood. Obtaining this knowledge will allow process - microstructure - propert y relation ship realization and will enable a differentiating ceramic integration capability. This LDRD leveraged Sandia's existing equipment and capabilities in simulation, experimentation, and materials characterization to discover the fundamental mechanisms for ce ramic particle deformation, particle - substrate bonding, and particle - particle bonding in RT consolidated films. RT deformation of individual Al 2 O 3 particles was examined computationally and experimentally as a model system for understanding the complex dyn amics associated with in vacuo RT deposition conditions associated with AD. Subsequently, particle - substrate bonding and particle - particle bonding in AD Al 2 O 3 consolidated films were examined computationally and experimentally. Fundamental mechanisms behin d the AD process were proposed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.973 | 0.980 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".