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Record W4400770996 · doi:10.26434/chemrxiv-2024-n35nl

Scaling Relations for Ammonia Oxidation

2024· preprint· en· W4400770996 on OpenAlexafffund
Rachelle M. Choueiri, Stephen W. Tatarchuk, O. F. Parker, William F. Cooper, Leanne D. Chen

Bibliographic record

VenueChemRxiv · 2024
Typepreprint
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCatalysisScalingAmmoniaAmmonia productionTransition metalDensity functional theoryScale (ratio)Materials scienceChemistryInorganic chemistryComputational chemistryMathematicsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

The ammonia oxidation reaction is a reaction of great interest for its potential to upcycle ammonia waste, creating fertilizer salts beneficial for the agricultural industry. Currently, AOR catalysts typically suffer either from high onset potentials or catalyst poisoning, and better catalyst materials must be found in order for AOR to be viable for large-scale fertilizer production. Experimentally, it is difficult to study the interactions of adsorbates on catalyst surfaces on an atomic level, whereas computational studies provide us with a means to study catalysts on this scale. In this study, we use density functional theory calculations to develop linear scaling relations for ammonia oxidation using a set of ten reference metals. The scaling relations were used in a microkinetic model to predict the most active transition metal electrocatalysts for the AOR.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.999

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 integrity0.0000.001
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 head0.023
GPT teacher head0.260
Teacher spread0.237 · 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
Published2024
Admission routes2
Has abstractyes

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