MétaCan
Menu
Back to cohort
Record W3095967317 · doi:10.1002/anie.202010159

Modulating Single‐Atom Palladium Sites with Copper for Enhanced Ambient Ammonia Electrosynthesis

2020· article· en· W3095967317 on OpenAlexaff
Lili Han, Zhouhong Ren, Pengfei Ou, Hao Cheng, Ning Rui, Lili Lin, Xijun Liu, Longchao Zhuo, Jun Song, Jiaqiang Sun, Jun Luo, Huolin L. Xin

Bibliographic record

VenueAngewandte Chemie International Edition · 2020
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsMcGill University
FundersNational Natural Science Foundation of China
KeywordsElectrosynthesisCatalysisAmmonia productionChemistryFaraday efficiencyPalladiumElectrochemistryChemisorptionProtonationCopperInorganic chemistryHydrogenAdsorptionPhysical chemistryElectrodeOrganic chemistryIon

Abstract

fetched live from OpenAlex

Abstract The electrochemical reduction of N 2 to NH 3 is emerging as a promising alternative for sustainable and distributed production of NH 3 . However, the development has been impeded by difficulties in N 2 adsorption, protonation of *NN, and inhibition of competing hydrogen evolution. To address the issues, we design a catalyst with diatomic Pd‐Cu sites on N‐doped carbon by modulation of single‐atom Pd sites with Cu. The introduction of Cu not only shifts the partial density of states of Pd toward the Fermi level but also promotes the d‐2π* coupling between Pd and adsorbed N 2 , leading to enhanced chemisorption and activated protonation of N 2 , and suppressed hydrogen evolution. As a result, the catalyst achieves a high Faradaic efficiency of 24.8±0.8 % and a desirable NH 3 yield rate of 69.2±2.5 μg h −1 mg cat. −1 , far outperforming the individual single‐atom Pd catalyst. This work paves a pathway of engineering single‐atom‐based electrocatalysts for enhanced ammonia electrosynthesis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.233
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), 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

Citations226
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAngewandte Chemie International EditionSame topicAmmonia Synthesis and Nitrogen ReductionFrench-language works237,207