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Record W2903753306 · doi:10.3390/catal8120654

Application of Uniform Design Method in the Optimization of Hydrothermal Synthesis for Nano MoS2 Catalyst with High HDS Activity

2018· article· en· W2903753306 on OpenAlexafffund
Haiping Zhang, Hongfei Lin, Ying Zheng

Bibliographic record

VenueCatalysts · 2018
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsWestern UniversityUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCatalysisHydrodesulfurizationHydrothermal circulationMaterials scienceNano-Hydrothermal synthesisChemical engineeringNanotechnologyComposite materialChemistryOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

The optimization of catalyst synthesis conditions using traditional single factor method involves extensive experimental time and costs. To overcome the drawbacks, a uniform design method was applied in the hydrothermal synthesis of nano MoS2 catalyst. An optimal synthesis condition is reached with only a few trials. Catalyst synthesis temperature is reduced to 200 °C. The catalyst synthesized at the screened condition shows high hydrotreating activities. The results conclude that the catalyst has thread-like slabs with a lattice structure that is less mature than fully developed MoS2. The characterization results indicate that the appearance of such structure may be due to the weak links of successive MoS2 nuclei. The high catalytic activity is a result of the layered structure and a significantly large number of defects on the slabs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.244
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations8
Published2018
Admission routes2
Has abstractyes

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