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Record W2738176969 · doi:10.1021/acssuschemeng.7b01638

Assessment of a Sustainable Electrochemical Ammonia Production System Using Photoelectrochemically Produced Hydrogen under Concentrated Sunlight

2017· article· en· W2738176969 on OpenAlexafffund
Yusuf Biçer, İbrahim Dinçer

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAmmonia productionHydrogen productionAmmoniaElectrochemistryMaterials scienceMolten saltInorganic chemistryWater splittingHydrogenElectrolyteChemical engineeringChemistryElectrodePhotocatalysisCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Intensive fossil fuel usage in ammonia production is considered nonsustainable; hence, alternative ammonia synthesis options are under investigation. In this study, a comprehensive study on environmental impact assessment is performed to investigate the electrochemical synthesis of ammonia at ambient pressure using photoelectrochemically produced hydrogen under concentrated solar light. The photoelectrochemical reactor consists of a membrane electrode assembly with a copper oxide semiconductor on a stainless steel cathode plate. The electrolyte for ammonia synthesis is molten salt containing a eutectic mixture of NaOH and KOH. The electrodes and wires are made of nickel. The life cycle assessment of the concentrated light photoelectrochemical hydrogen production is initially performed and integrated to molten-salt-based electrochemical ammonia synthesis. The material and energy requirements of the life cycle assessment are taken from the experimental data. The results imply that electrochemical ammonia synthesis driven by solar energy can significantly reduce the total environmental impact, corresponding to about 50% of the current steam methane reforming based ammonia production.

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 categoriesMeta-epidemiology (narrow)
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 score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.230
Teacher spread0.224 · 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.

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

Citations46
Published2017
Admission routes2
Has abstractyes

Explore more

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