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Record W3201300030 · doi:10.1139/cjc-2021-0201

Recent developments in metal-doped SBA-15 catalysts for heterogeneous catalysis and sustainable chemistry

2021· article· en· W3201300030 on OpenAlexvenueno aff
Birendra Nath Mahato, T. Krithiga

Bibliographic record

VenueCanadian Journal of Chemistry · 2021
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsnot available
Fundersnot available
KeywordsCatalysisChemistryMesoporous materialEnvironmental remediationPhotocatalysisNanotechnologySurface modificationAdsorptionHeterogeneous catalysisNanomaterialsChemical engineeringMesoporous silicaHydrothermal circulationHuman decontaminationOrganic chemistryMaterials scienceWaste management

Abstract

fetched live from OpenAlex

The development of new advanced sustainable materials for heterogeneous catalysis requires control of the structural parameters of the active sites. Mesoporous silica, especially SBA-15, has some unique and important features such as highly ordered mesopores, greater hydrothermal stability, greater wall thickness, large surface area, and adjustable pore volume. All these properties render it a promising material for catalysis, adsorption, supporting materials, biomedical applications, and environmental remediation. However, pure SBA-15 lacks acidic characteristics, which hinders its catalytic activity. Therefore, the functionalized SBA-15 improves the catalytic activity for versatile applications. Thus, in this study, we attempted to summarize the synthesis procedures, various functionalization processes, and application of metal-modified SBA-15 in organic synthesis, fine chemical synthesis, photocatalysis, and decontamination of water. Furthermore, the physicochemical properties, sustainability, and efficacy are discussed in detail for future reference and scope of studies.

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 categoriesInsufficient 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 score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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