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Record W2323110010 · doi:10.1166/jnn.2008.an44

Potential for Mass Production of Nickel-Based Nanomaterials by Carbonyl Process

2008· article· en· W2323110010 on OpenAlexaff
Vladimir Paserin, Steve Baksa, Alexandre Zaitsev, Jun Shu, Faranak Shojai, William Nowosiadly

Bibliographic record

VenueJournal of Nanoscience and Nanotechnology · 2008
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsVale (Canada)
Fundersnot available
KeywordsNickelMaterials scienceNanomaterialsDecompositionPolymerHomogeneousChemical engineeringMass transferNanotechnologyMetallurgyOrganic chemistryComposite materialChromatographyChemistry

Abstract

fetched live from OpenAlex

High purity micron and sub-micron scale nickel materials have been mass-produced by the nickel carbonyl process for many decades. The same technology is being explored for mass production of nano-scale nickel products. The paper presents an overview of nickel carbonyl technology suitable for mass production of nano-scale nickel powders with surface areas exceeding 100 m2/g, and various three-dimensional nickel based micro structures. The industrial processes are based on the homogeneous decomposition of carbonyl in the free space of a CVD reactor and on the heterogeneous decomposition of carbonyl on a variety of substrates, including polymer foams and carbon fibres.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.008
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.009
GPT teacher head0.251
Teacher spread0.241 · 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

Citations18
Published2008
Admission routes1
Has abstractyes

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