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Record W2002346281 · doi:10.1021/cg060747m

Synthesis of High-Purity Boron Nitride Nanocrystal at Low Temperatures

2007· article· en· W2002346281 on OpenAlex
Li Hou, Faming Gao, Guifang Sun, Huiyang Gou, Min Tian

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

VenueCrystal Growth & Design · 2007
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAmorphous solidNanocrystalNanocrystalline materialBoron nitrideMaterials scienceAnhydrousSolventBoronChemical engineeringAnalytical Chemistry (journal)Lattice constantAbsorption spectroscopyNanotechnologyCrystallographyChemistryOrganic chemistryOptics

Abstract

fetched live from OpenAlex

High-purity nanocrystalline boron nitride has been successfully synthesized by a simple synthesis method using amorphous B powder and NaN 3 as the reactants and anhydrous CH 3 CN as the solvent at 380 °C. Results from XRD, FT-IR, EELS, and BET absorption measurements suggest that the synthesized product can be indexed as pure hexagonal BN with lattice constants of a = 2.497 Å and c = 6.678 Å, and the specific surface area of product is 52.19 m 2 /g. The TEM images show the multiplex belt spherelike, fiberlike, sheetlike, and tubelike morphologies of the products. Here, the multiplex belt spherelike and sheetlike structures are reported for the first time. When the temperature of reaction and the solvent are controlled, BN products with particular morphologies can be selectively produced. The optical properties of the product are observed in the PL spectra, which shows that the as-prepared BN emits strong visible luminescence at 580 nm (λ ex = 325 nm).

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.243
Teacher spread0.229 · 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