Experimental and Numerical Analysis of Biological Regeneration of Perchlorate Laden Ion-Exchange Resins in Batch Reactors
Bibliographic record
Abstract
Removal of perchlorate ions from ion-exchange resins is essential for the economical treatment of perchlorate contaminated water. The objectives of this study were to prove that single-use ion-exchange resins could be regenerated in biological batch systems and to develop a numerical model that could be used to predict the time for regeneration of perchlorate from exhausted ion-exchange resins under varying conditions. This research uniquely addresses both the biological and physical/chemical aspects of the regeneration of single-use resins. Experimental studies demonstrated that perchlorate exhausted resin was effectively regenerated by a salt-tolerant, perchlorate-reducing culture. A numerical model was developed that incorporates physical desorption and biodegradation parameters. Results suggest that the model generates an acceptable correlation to experimental data and can predict the time to regeneration when no perchlorate is detectable in the aqueous phase in equilibrium with the ion exchange resin. A sensitivity study showed that biological activities have the most significant effects on the biological regeneration process. Results of this research can be directly applied to process design for biological regeneration of perchlorate exhausted single-use ion-exchange resins.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".