Magnesium germanium oxide hydrate nanowires with outstanding surface stability for selective cationic dye removal
Bibliographic record
Abstract
Physical adsorption is one of the most promising methods for organic dye removal in wastewater. However, existing adsorbent materials lack a combination of selectivity, efficiency, stable performance over a wide pH range, and reusability after repeated regeneration. In this work, we presented a novel adsorbent, magnesium germanium oxide hydrate (MGOH) nanowires. Utilizing electrochemical and acid-base titration methods, we found that MGOH possesses a unique crystal structure that is rich in hydroxyl (-OH) groups. These -OH groups keep the surface of MGOH negatively charged over a wide pH range from 0 to 10.6, which hasn’t been achieved by any adsorbent to date. Using rhodamine B (RhB) as a model cationic dye, we demonstrated that a 97.4 % removal efficiency can be achieved within 15 min in contact with MGOH at room temperature. The adsorption selectivity of MGOH toward cationic dyes was further demonstrated by effective removal of target dyes in dye mixtures. In addition, MGOH can be easily regenerated through solvent washing and thermal annealing for multiple cycles without losing its adsorption capability.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".