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Ti/C and Ti/B Nanocomposites: Comparison of Sorption-Desorption Properties

2009· article· en· W2047445575 on OpenAlex
T. I. Khomenko, А. В. Леонов, C. Borchers, E.Z. Kurmaev, Alexandr Moewes

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

VenueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2009
Typearticle
Languageen
FieldEngineering
TopicIntermetallics and Advanced Alloy Properties
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMaterials scienceDesorptionSorptionNanocompositeBoronHydrogenAmorphous solidChemical engineeringEconomies of agglomerationAnalytical Chemistry (journal)AdsorptionComposite materialCrystallographyPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Hydrogen sorption-desorption properties of Ti/B and Ti/C nanocomposites prepared under ball-milling of the corresponding powders in H2 flow were studied using kinetic, microscopic and spectroscopic techniques. Amorphous boron was found to be more effective in spurring Ti – H2 interaction than carbon because of the following properties: (1) significant fragmentation of Ti powder by preventing agglomeration of the particles; (2) unhindered hydrogen access to the surface of Ti nanoparticles through the boron matrix; (3) appearance of new occupation sites available for H atoms, which are characterized by low H2 desorption temperature. The dynamics of the formation of these sites and the H2 distribution between different occupation sites in dependence on phase composition and morphology were studied for the Ti/B system.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0000.001
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 head0.046
GPT teacher head0.292
Teacher spread0.246 · 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