Biofilm thickness restraint carriers enhance free nitrous acid inhibition for partial nitritation
Bibliographic record
Abstract
Abstract Ammonia is a deleterious pollutant present in municipal wastewater that can be hazardous if released into the environment. There is a need for the development of novel processes to advance ammonium removal technologies. Partial nitritation (PN) and anaerobic ammonia oxidation (anammox) are modern treatment processes that can be combined to provide energy-efficient ammonia removal; however, these processes have been shown to be challenging to implement as a two-stage system. New methods to achieve steady PN need to be discovered. Free nitrous acid (FNA) exposure has been explored as a possible strategy for achieving PN; however, exposure time to FNA and FNA dosage is dependent on the treatment system. For biofilm technologies, such as the moving bed biofilm reactor and biofilm characteristics, including biofilm thickness, can cause inconsistent results. Therefore, this study compares defined maximal biofilm thickness with undefined biofilm thickness and their capacity to achieve PN using FNA. This study found that a defined maximal biofilm thickness designed carrier maintained a thin biofilm capable of achieving PN after FNA exposure while the undefined biofilm thickness designed carrier was not suitable for stable PN.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".