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Record W3035028779 · doi:10.1021/acscatal.0c01073

Generalized Mechanistic Framework for Ethane Dehydrogenation and Oxidative Dehydrogenation on Molybdenum Oxide Catalysts

2020· article· en· W3035028779 on OpenAlexafffund
Rui Yao, José E. Herrera, Lihang Chen, Ya-Huei Cathy Chin

Bibliographic record

VenueACS Catalysis · 2020
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsWestern UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilCanada Foundation for Innovation
KeywordsDehydrogenationCatalysisChemistryOxygenPhotochemistryEthyleneInorganic chemistryDissociation (chemistry)Organic chemistry

Abstract

fetched live from OpenAlex

Ethane turnovers to ethylene in either oxidehydrogenation with diverse oxidants (O 2, CO 2, H 2 O) or dehydrogenation (without an oxidant) over two-dimensional MoO x dispersed on Al 2 O 3 catalyst occur via a generalized mechanistic framework encompassing ternary catalytic cycles of C 2 H 6 activation, oxidant activation, and carbon removal. This is confirmed from rate assessments, detailed kinetic analysis accounting for active site loss, isotopic tracer studies, and detailed spectroscopic characterization. Irrespective of the oxidant’s chemical identity, the C 2 H 6 activation cycle occurs via the kinetically relevant C–H bond activation of C 2 H 6 on lattice oxygen of MoO x, forming C 2 H 4 . The concomitant oxidant activation cycle either replenishes the oxygen vacancies or generates reactive oxygen species, which scavenge unwanted carbonaceous debris deposited on catalyst surfaces at contents dictated by the chemical identity of the oxidant and oxygen chemical potential that it exerts. Among the oxidants, O 2 is the most effective, as it removes coke effectively, leading to essentially no rate decay. CO 2 and H 2 O are alternate soft oxidants, and their use prevents the overoxidation of ethylene, thus resulting in higher ethylene selectivity (80–85%) than using O 2 . CO 2 activation is, however, severely restricted kinetically, as evidenced from the reverse water–gas shift reaction that is far away from chemical equilibrium; thus, the generation of reactive oxygen species and their ability to concomitantly oxidize coke are much less effective than those with O 2 oxidant. H 2 O dissociation is rapid and quasi-equilibrated, but its activation converts a portion of the active lattice oxygen to hydroxy species, reducing the active oxygen centers and lowering C 2 H 6 turnovers. The rates of the C 2 H 6 activation cycle dictate the intrinsic rates, whereas those of the concomitant oxidant activation and carbon removal cycles dictate the surface lattice oxygen density available for catalysis and in turn the extent of rate decay. Consolidating these findings within a generalized mechanistic framework leads to a universal rate expression containing two terms, one accounting for an intrinsic C 2 H 6 activation rate and a second one for the time-dependent rate decay. This universal rate expression captures the kinetic properties of early transition-metal oxides in C 2 H 6 catalysis, irrespective of the chemical identity of the oxidant.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.024
GPT teacher head0.267
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations105
Published2020
Admission routes2
Has abstractyes

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