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Record W2323712615 · doi:10.1149/1.3157945

Hydrogen and Nanostructured Carbon by Plasma Decomposition of Natural Gas

2009· article· en· W2323712615 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

VenueECS Transactions · 2009
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of New BrunswickAtlantic Hydrogen (Canada)
Fundersnot available
KeywordsNatural gasHydrogenMaterials scienceRaw materialHydrogen productionCarbon fibersChemical engineeringAmorphous carbonFuel gasPlasmaHydrogen fuelAmorphous solidWaste managementChemistryComposite materialOrganic chemistryCombustionComposite number

Abstract

fetched live from OpenAlex

This report describes a commercial plasma reactor system for the GHG-free production of hydrogen enriched natural gas (HENG) using natural gas as a feedstock. The process demonstrated stable operation for the production of 20 vol% HENG fuel. The specific energy requirements of the process were found to be competitive with other GHG-free hydrogen production processes. The HENG fuel produced in the process was used as a fuel for a commercial hot water heater and demonstrated reductions of ca. 22% in the NOx emissions of the system boiler. The solid carbon by-product of the process was found to consist of a mixture of amorphous and nanostructured carbons. The nanostructured material was composed of stacked graphene layers of up ca. 7-10 layers thickness and 100 nm diameter.

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 score0.002
Threshold uncertainty score0.415

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 head0.004
GPT teacher head0.228
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