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Record W2370243202 · doi:10.1002/cctc.201600107

Influence of Carbon on Molybdenum Carbide Catalysts for the Hydrogen Evolution Reaction

2016· article· en· W2370243202 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemCatChem · 2016
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsMinistry of Education and Child Care
FundersCentral South UniversityNational Natural Science Foundation of China
KeywordsTafel equationCatalysisExchange current densityCarbon fibersCarbideCarbonizationMolybdenumHydrogenMaterials scienceInorganic chemistryElectrical resistivity and conductivityChemical engineeringChemistryOrganic chemistryMetallurgyComposite materialPhysical chemistryElectrochemistryAdsorption

Abstract

fetched live from OpenAlex

Abstract The influence of carbon on molybdenum carbide catalysts for the hydrogen evolution reaction (HER) is discussed. The carbon content is adjusted by varying the molar ratio of molybdenum and glucose sources and the holding time in the carbonization process. The carbon plays a crucial role in the determination of phase formation, surface area, and electrical resistance, which are associated with the final HER activity. There is a contradiction between the reduced active sites and improved electrical resistance that results from the reduced content of carbon, and a balance can be achieved with a holding time of 9 h to provide the best HER activity with a low Tafel slope of 55 mV dec −1 and a high exchange current density of 0.047 mA cm −2 . Importantly, the transformation of the order of the free carbon improves the electrical conductivity remarkably to result in a great improvement in the final HER activity.

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.

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 score0.003
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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