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Phosphate removal from aqueous solution using ytterbium oxide supported mesoporous silicas (SBA-15, KIT-6 & MCM-41)

2025· article· en· W4410362368 on OpenAlexfundno aff
Mozhdeh Gholami, James Tardio

Bibliographic record

VenueMicroporous and Mesoporous Materials · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsnot available
FundersRoyal Melbourne Institute of TechnologyOntario Ministry of Natural Resources and Forestry
KeywordsYtterbiumAqueous solutionMesoporous materialPhosphateChemistryMCM-41Inorganic chemistryNuclear chemistryOxideChemical engineeringMaterials scienceOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

In this study, a series of ytterbium supported mesoporous silicas, SBA-15, KIT-6 and MCM-41 (containing different amounts of Yb) were studied for phosphate removal from aqueous solution. The prepared materials were characterized by X-ray diffraction, N2 adsorption/desorption (BET), HRTEM and XPS. All of the materials prepared were found to possess an ordered hexagonal mesoporous structure. The best performing materials under the conditions used (in terms of maximum adsorption capacity) for each of the silica supports were 0.3Yb SBA-15, 0.1Yb KIT-6, and 0.1Yb MCM-41 which had maximum adsorption capacities of 20.1 mg P/g, 20.9 mg P/g and 20.5 mg P/g respectively. The aforementioned best performing materials were found to have slightly higher maximum adsorption capacities at lower pH (pH 3 and 5, compared to pH 6) whilst the coexistence of chloride, sulphate and nitrate, were found to have no significant effect on phosphate adsorption. Bicarbonate ion was found to have a significant negative effect on adsorption capacity – this however was most likely due to this ion increasing the solution pH which in turn causes reduced adsorption. It was found that adsorbed phosphate could be readily desorbed from the materials studied using HNO 3 (5%) at room temperature. Reuse tests showed a slightly reduced adsorption capacity for the materials for which regeneration studies were conducted.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.288
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.239
Teacher spread0.228 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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