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Record W4406770344 · doi:10.1021/acsnano.4c14802

Highly Accessible Electrocatalyst with <i>I</i><i>n Situ</i> Formed Copper-Cluster Active Sites for Enhanced Nitrate-to-Ammonia Conversion

2025· article· en· W4406770344 on OpenAlexaff
Zhen Shen, Fengfei Xu, Xueyi Cheng, Jietao Jiang, Changkai Zhou, Yu Zeng, Xizhang Wang, Lijun Yang, Qiang Wu, Zheng Hu

Bibliographic record

VenueACS Nano · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsMinistry of Education and Child Care
FundersNational Key Research and Development Program of ChinaSuzhou Municipal Science and Technology BureauNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsElectrocatalystCopperIn situNitrateAmmoniaCluster (spacecraft)Ammonia productionInorganic chemistryMaterials scienceChemistryEnvironmental chemistryNanotechnologyElectrochemistryElectrodeMetallurgyOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Ammonia synthesis via nitrate electroreduction is more attractive and sustainable than the energy-extensive Haber–Bosch process and intrinsically sluggish nitrogen electroreduction. Herein, we have designed a single-site Cu catalyst on hierarchical nitrogen-doped carbon nanocage support (Cu 1 /hNCNC) for nitrate electroreduction, which achieves an ultrahigh ammonia yield rate (YR NH3 ) of 99.4 mol h –1 g Cu –1 (2.30 mol h –1 g cat. –1 ) with ammonia Faradaic efficiency (FE NH3 ) of 99.3%, far beyond the most reported single-site catalysts on carbon-based supports. The combined operando characterization and theoretical studies indicate that the in situ formed Cu-cluster active sites are responsible for the high YR NH3 and FE NH3 due to the enhanced NO 3 – adsorption and subsequent protonation on the unique Cu 3 –N 4 moieties, and meanwhile, the hierarchical hNCNC support facilitates the mass/charge transfer kinetics, thus promoting the high expression of intrinsic activity. The demonstration of plasma N 2 oxidization and nitrate electroreduction cascade reaction manifests the great potential of the Cu 1 /hNCNC electrocatalyst in sustainable NH 3 synthesis. These findings offer valuable insights into the design of effective catalysts for electrosynthetic reactions.

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 score0.021
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.235
Teacher spread0.227 · 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

Citations19
Published2025
Admission routes1
Has abstractyes

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