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Record W2021694666 · doi:10.1002/zaac.201000202

Using Taguchi Robust Design Method to Develop an Optimized Synthesis Procedure for Nanocrystals of ZSM‐5 Zeolite

2010· article· en· W2021694666 on OpenAlex
Maryam Abrishamkar, Seyed Naser Azizi, Hossein Kazemian

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

VenueZeitschrift für anorganische und allgemeine Chemie · 2010
Typearticle
Languageen
FieldChemistry
TopicZeolite Catalysis and Synthesis
Canadian institutionsWestern University
Fundersnot available
KeywordsTaguchi methodsZeoliteCrystallizationMaterials scienceNanocrystalOrthogonal arrayScanning electron microscopeZSM-5DiffractionChemical engineeringSpectroscopyAnalytical Chemistry (journal)NanotechnologyComposite materialChromatographyChemistryCatalysisOpticsOrganic chemistryEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The effects of TPAOH/SiO 2 , H 2 O/SiO 2 , SiO 2 /Na 2 O and SiO 2 /Al 2 O 3 ratios in the initial synthetic mixture on the crystallization of nanoparticles of ZSM‐5 zeolite under atmospheric pressure were studied. A Taguchi orthogonal experimental design with three levels of the above‐mentioned parameters was used to optimize the experiment parameters by the analysis of variances (ANOVA). Applying the Taguchi method significantly reduced the time and cost for optimization. The obtained products were characterized by scanning electron microscopy, X‐ray diffraction and FT‐IR spectroscopy. As a result of the Taguchi analysis TPAOH/SiO 2 followed by SiO 2 /Al 2 O 3 was the most influencing parameters for the synthesis of nanosized ZSM‐5 crystals.

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)0.002
metaresearch head score (Gemma)0.004
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: Methods · Consensus signal: none
Teacher disagreement score0.205
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.326
Teacher spread0.279 · 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