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Record W2611565226 · doi:10.1149/2.0091708jes

Electrochemical Synthesis of Ammonia in Molten Salt Electrolyte Using Hydrogen and Nitrogen at Ambient Pressure

2017· article· en· W2611565226 on OpenAlexafffund
Yusuf Biçer, İbrahim Dinçer

Bibliographic record

VenueJournal of The Electrochemical Society · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsMolten saltAmmonia productionElectrolyteElectrochemistryAmmoniaInorganic chemistryAnodeCathodeChemistryHydrogenSalt (chemistry)Materials scienceChemical engineeringElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

In this study, the synthesis of ammonia (NH3) at ambient pressure using H2 and N2 is electrochemically achieved. The conducting and reaction media with molten salt consist of molten hydroxide as NaOH and KOH whereas the reaction temperature is varied in the range of 200°C to 255°C to investigate the impact of temperature on the ammonia production rate and hence performance. The porous nickel mesh electrodes having an area of 100 cm2 are used as cathode and anode where the supplied electricity is controlled using potentiostat/galvanostat. The maximum faradaic efficiency for ammonia synthesis is found to be 9.3% at 210°C corresponding to 6.53 × 10−10 mol/s cm2 ammonia evolution rate at 2 mA/cm2 current density with nano-Fe3O4 as the catalyst. Furthermore, the applied voltages and applied currents are varied to find the optimum experimental conditions for molten salt electrolyte based electrochemical ammonia synthesis.

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)0.001
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 score0.011
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.228
Teacher spread0.219 · 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

Citations41
Published2017
Admission routes2
Has abstractyes

Explore more

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