Performance Characterization of Hydrogen Isotope Exchange and Recombination Catalysts for Tritium Processing
Bibliographic record
Abstract
AECL’s hydrogen isotope exchange catalyst and recombination catalysts have been successfully applied to a wide range of industrial tritium-removal applications. The catalysts are used for Liquid Phase Catalytic Exchange (LPCE) and for gas-phase and trickle-bed recombination of hydrogen isotopes and have led to process simplification, improved safety and operational advantages.Catalyst performance design equations derived from laboratory testing of these catalysts have been validated against performance under industrial conditions. In a Combined Electrolysis and Catalytic Exchange (CECE) demonstration plant analyses of LPCE and recombiner efficiency were carried out as a function of catalyst activity over a wide range of operation. A steady-state process simulation used to model and design the hydrogen-water isotopic exchange processes, such as the CECE detritiation plant, was validated using the results of this demonstration.Catalyst development for isotope-exchange and recombination applications has continued over the last decade. As a result, significant improvements in catalyst performance have been achieved for these applications. This paper outlines the uniqueness of AECL’s specialized catalysts and process designs for these applications with examples from laboratory and industrial case studies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".