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DFT study of the reaction mechanism of N2O decomposition on Au3+/0/- clusters

2019· dataset· en· W3119953926 on OpenAlexaff
Lin Yu Wu, Cheng Chen, Lan Luo, Yongcheng Wang, Bing Yin

Bibliographic record

VenueAuthorea · 2019
Typedataset
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsScience North
Fundersnot available
KeywordsChemistryDissociation (chemistry)Bond-dissociation energyMolecular orbitalCluster (spacecraft)Density functional theoryCatalysisHOMO/LUMOAtomic orbitalActivation energyReaction mechanismPhysical chemistryElectron transferComputational chemistryMoleculeElectronOrganic chemistry

Abstract

fetched live from OpenAlex

In this paper, the reaction mechanism of Au3+/0/- clusters with N2O was studied by density functional theory (DFT) calculations. The analysis of the potential energy surfaces showed that the Au3 neutral cluster exhibited highest catalyze activity on the decomposition of N2O, energy barrier is only 11.60 kcal/mol. The corresponding energy barriers for Au3- and Au3+ are 28.51 and 58.79 kcal/mol, respectively. The effects of Au3+/0/- clusters assistance analyzed using the activation strain model indicated that the dissociation of the N-O bond depends on the interaction energy of Au3 clusters and N2O. The electron transfer from the Au3+/0/- cluster to the N2O facilitates the dissociation of N-O bond. The analysis of frontier molecular orbitals (FMO) indicated that only the interaction of HOMO-LUMO interactions is strongly enough and there is sufficient orbital overlap between the Au3+/0/- clusters and N2O, electron transfer can occur and activation of N2O can be achieved. The study of thermodynamic processes showed that there is evident correlation between the binding energy of the Au3O+/0/- cluster oxides and the barrier energy of the reaction. Therefore, the orbital interactions between Au3+/0/- and N2O and thermodynamic driving force have a great influence on the reaction. These results enrich our understanding of the catalytic dissociation of N2O by Au-cluster-based catalysts.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.496
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.024
GPT teacher head0.312
Teacher spread0.288 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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