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Record W4391569662 · doi:10.1007/s43979-024-00080-0

Structure–activity relationships over Ru/NiAl2O4 catalysts in anisole demethoxylation: spectroscopic and kinetic studies

2024· article· en· W4391569662 on OpenAlexafffund
Lingxiao Li, Zhiruo Guo, Xiaohui Liu, Mohsen Shakouri, Yongfeng Hu, Yong Guo, Yanqin Wang

Bibliographic record

VenueCarbon Neutrality · 2024
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsCanadian Light Source (Canada)
FundersNational Key Research and Development Program of ChinaScience and Technology Commission of Shanghai MunicipalityNational Natural Science Foundation of ChinaCanadian Light Source
KeywordsAnisoleCatalysisChemistryKinetic energyComputational chemistryOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Demethoxylation was kinetically and spectroscopically studied over three catalysts with different Ru 0 /Ru δ+ ratios. In-situ spectroscopic tests demonstrated that the synergy between Ru 0 and Ru δ+ was crucial, and Ru 0 was in charge of H 2 activation and adsorption of aromatic ring while Ru δ+ adsorbed with O in methoxyl. A Langmuir–Hinshelwood kinetic model was proposed, and ratio of Ru 0 /Ru δ+ was the key in deciding the rate-determining step (RDS): i) desorption of toluene was RDS over catalyst with high Ru 0 ratio; ii) dissociation of H 2 was RDS over Ru δ+ enriched catalyst; iii) demethoxylation was rate-determined by CO water–gas shift (WGS) when Ru 0 /Ru δ+ approached ~ 1. The best performance was obtained over Ru/NiAl 2 O 4 -200, which effectively enabled both C-O bond activation and rapid recovery of adsorption sites for aromatic rings. Finally, in-situ DRIFT studies on methoxy decomposition and CO-WGS unraveled that the electronic composition of Ru was more stable in Ru/NiAl 2 O 4 -200 which contributes to its excellence.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.034
GPT teacher head0.293
Teacher spread0.259 · 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 designObservational
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

Citations16
Published2024
Admission routes2
Has abstractyes

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