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Record W3164543339 · doi:10.1039/d1ra01599k

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

2021· article· en· W3164543339 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRSC Advances · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsOptech (Canada)Environment and Climate Change Canada
Fundersnot available
KeywordsAdsorptionChemistryBiocharAqueous solutionMetal ions in aqueous solutionLangmuir adsorption modelMetalNuclear chemistryHuskIon exchangeChemisorptionIonOrganic chemistryPyrolysis

Abstract

fetched live from OpenAlex

, 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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.237
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it