Enhanced simultaneous adsorption of As(<scp>iii</scp>), Cd(<scp>ii</scp>), Pb(<scp>ii</scp>) and Cr(<scp>vi</scp>) ions from aqueous solution using cassava root husk-derived biochar loaded with ZnO nanoparticles
Bibliographic record
Abstract
, while the best isothermal description followed the Langmuir model. As a result, the adsorption process of heavy metals onto biochars was chemisorption on homogeneous monolayers, which was mainly controlled by cation exchange and surface precipitation mechanisms due to enriched oxygen-containing surface groups with ZnO-NP modification of biochar. The FTIR and EDS analysis data confirmed the important role of oxygen-containing surface groups, which significantly contributed to removal of heavy metals with extremely high adsorption capacities, comparable with other studies. In conclusion, due to very high adsorption capacities for metal cations, the cassava root husk-derived biochar modified with ZnO-NPs can be applied as the alternative, inexpensive, non-toxic and highly effective adsorbent in the removal of various toxic cations.
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 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) | 0.001 | 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) | 0.001 | 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".