Aluminum-ceramic composites for thermal management in energy-conversion systems
Bibliographic record
Abstract
Abstract The most important property of energy-conversion ceramics in high-power lighting devices based on laser diodes (LDs) is thermal durability because high-energy LDs act as excitation and heat sources for ceramics. Herein, aluminum-ceramic composites (ACCs) are introduced for the manipulation of heat generated during high-power lighting. The cerium-doped aluminum garnet (YAG:Ce) phosphor is selected as the energy-conversion ceramic material. The ACCs have an all-in-one structure bridged by a low-melting glass material. In ACCs, the heat flow from the ceramic to Al is manipulated by a heat-flux throttling layer (TL) comprised of Al and glass. During high-power lighting operation, the input-output temperature differences (Tin − Tout) between the ceramic layer (input heat) and end face of the Al layer (output heat) are 13 and 3.9 °C in the absence and presence of the TL, respectively. A lower Tin − Toutmeans less heat is loss during heat flow from the ceramic to the metal due to the temperature gradient created by inserting the TL. The results provide a potential application for multi-energy-conversion systems, i.e., optical to heat and heat to electric energy, in terms of heat flow manipulation.
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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) | 0.000 | 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 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".