Tritiation of Semiconductor Materials for Micropower Application
Bibliographic record
Abstract
We report on a simple and versatile method for the integration of tritium in semiconductor materials. A variety of semiconductor materials are exposed to tritium (T2) gas at pressures of up to 120 bar and temperatures of up to 250 °C. Tritiated materials include hydrogenated amorphous silicon (a-Si:H), crystalline silicon (c-Si), silica and carbon nanotubes (CNT). Deep ultra-violet laser irradiation was used to lock tritium in silica films. Effusion measurements show the presence of stable tritium in silicon, silica and CNTs up to 400 °C. IR absorption spectra show a Si-T stretching mode at 1200 cm-1 indicating the formation of stable Si-T bonds in a-Si:H. SIMS measurements show that the penetration depth of tritium in a-Si:H and c-Si is 150 and 10 nm, respectively; the concentration of tritium locked in a-Si:H and c-Si is 20 and 4 at.%, respectively. In tritiated silica, 248-nm UV laser irradiation locks the permeated tritium at stable chemical bonding sites in the silica lattice. Thermal effusion measurement shows that 0.5 wt.% tritium can be stably immobilized in CNTs. The application of tritiated silicon as a cold electron source is demonstrated.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".