Removal of urea in ultrapure water system by urease-coated reverse osmosis membrane
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Among the various substances found in the feed source for the production of ultrapure water (UPW), urea is challenging to remove because it is a small molecular weight molecule that is not easily oxidized and does not carry a charge under neutral pH conditions. Urease enzyme, found in various organisms such as plants and bacteria, catalyze the hydrolysis of urea into carbon dioxide and ammonia. In this study, urease was immobilized on the polyamide layer of a reverse osmosis (RO) membrane to remove urea in UPW systems. The removal efficiency of urea by urease-coated RO membrane showed up to 27.9 % higher urea removal efficiency compared to the pristine membrane. This increase in urea removal can be attributed to both physical and biological effects from the urease coating on the membrane. Firstly, urease on the membrane surface can act as an additional physical barrier for urea to pass through. Secondly, urea can be hydrolyzed by the enzyme when it passes through the urease-coated RO membrane. In a two-pass RO system typical for UPW production, the removal of urea by a urease-coated membrane would be enhanced by twofold. This overall method can significantly increase the removal efficiency of urea in UPW systems, especially when considering the compounded removal by the urease coating, rejection by RO, and additional reactions by other treatment processes. Moreover, urea in UPW systems can be removed without the installment of additional processes by simply coating urease on the existing RO membranes.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it