Tritium Removal and Separation Technology Developments
Bibliographic record
Abstract
Recent increased interest from regulators and the public has led more organizations to consider the environmental impact and safety considerations of tritium handling. Examples include the significance of the tritium isotope separation system on ITER licensing, remediation of ground water from power utilities and government facilities and concerns of high tritium concentrations within operational CANDU reactors.GE Healthcare, formerly Amersham plc, has been producing tritium-labelled chemicals since the late 1940s. GE’s manufacturing site located near Cardiff, UK has installed a tritium waste treatment and enrichment facility to radically reduce tritium discharges to the environment. This facility employs a continuous processing plant that recovers tritium from a complex mixture of tritiated organic and aqueous waste compounds. Two isotope separation techniques are used to achieve a final pure tritium product, which is used in the manufacturing of labelled compounds.Building upon this experience, together with Special Separations Applications Inc. (SSAI), GE has developed a large-scale diffusion-based isotope separation process as an alternative to conventional cryogenic distillation. Having a tritium inventory an order of magnitude lower than conventional cryogenic distillation, this process is attractive for heavy water detritiation, applicable to single and multi-unit CANDU reactors and research reactors as well as fusion applications. Additionally, the new process has advantages of being cryogen-free, less complex, simple to operate and having improved conventional and radiological safety.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".