(Invited) Effect of Gaseous Tritium Environments on Betavoltaic Device Longevity
Bibliographic record
Abstract
Direct betavoltaic energy conversion is a specialized energy harvesting technology, converting beta radiation from a radiation source directly into electricity using a semiconductor. Of the most common beta emitting isotopes, tritium betavoltaics hold promise owing to the high specific activity of solid tritium compounds, low shielding requirements and relatively high availability. Betavoltaic devices offer great promise to produce continuous quantities of nanowatt to microwatt power over the course of several years, particularly for low-power sensor, medical, and space applications where sunlight is too sparse for solar cell use or where battery replacement is challenging. Canadian Nuclear Laboratories (CNL) is currently developing betavoltaic devices based on tritium. CNL has unique facilities to produce, fabricate and test betavoltaic devices. Computational techniques have been used to address challenges of longevity and electron-hole pair generation in semiconductor materials, in particular (In,Ga)P. Long-term studies on test wafers in different tritium-containing environments and the effects on power output and longevity will also be discussed.
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.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".