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Record W4410348892 · doi:10.1007/s10008-025-06327-9

A cautionary tale about hydrogen reference electrodes in nitrogen cycle electrochemistry

2025· article· en· W4410348892 on OpenAlexfundno aff
Yair Shahaf, Thierry K. Slot, David Eisenberg

Bibliographic record

VenueJournal of Solid State Electrochemistry · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsnot available
FundersTechnion-Israel Institute of TechnologyAzrieli FoundationNancy and Stephen Grand Technion Energy ProgramJewish National FundPurdue University
KeywordsElectrochemistryElectrodeNitrogenHydrogenMaterials scienceReversible hydrogen electrodeInorganic chemistryReference electrodeChemistryPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Nitrogen cycle electrochemistry involves important reactions such as ammonia synthesis from dinitrogen or from nitrates and the oxidation of hydrazine or urea fuels. Many of these applications require the reliable detection of ammonia and the precise reporting of applied potentials. We now report that a commercial reversible hydrogen electrode catalyzes an undesired chemical reaction between hydrogen (from the electrode cartridge) and NOx anions (from the electrolyte), generating ammonia in the absence of any applied potential. In addition to skewing the reported ammonia yields, this leads to a mixed potential and wrong reports of electrocatalytic onset potentials, compromising the measurements on several levels. Awareness and mitigation of these ubiquitous effects will allow nitrogen cycle electrocatalysis studies to advance on solid ground.

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)0.033
metaresearch head score (Gemma)0.098
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.098
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0050.012
Scholarly communication0.0070.010
Open science0.0080.003
Research integrity0.0160.040
Insufficient payload (model declined to judge)0.0050.006

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 head0.005
GPT teacher head0.242
Teacher spread0.238 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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