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Record W3132233440 · doi:10.3390/cryst11030222

Facile Synthesis of High-Quality Nano-Size 10B-Enriched Fibers of Hexagonal Boron Nitride

2021· article· en· W3132233440 on OpenAlexfundno aff
Pervaiz Ahmad, Mayeen Uddin Khandaker, Fida Rehman, Nawshad Muhammad, Mohammad Rashed Iqbal Faruque, Zahoor Ullah, M.A. Khan, Ghulamullah Khan, Muhammad Imtiaz Khan, Hazrat Ali, Sirajul Haq, Yousaf Iqbal, K. Alzimami, Layal Jambi, D.A. Bradley

Bibliographic record

VenueCrystals · 2021
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsnot available
FundersInstitute of Population and Public HealthUniversiti Kebangsaan MalaysiaKing Saud University
KeywordsNanoscopic scaleMaterials scienceRaman spectroscopyHexagonal boron nitrideBoron nitrideAnnealing (glass)BoronChemical engineeringHexagonal crystal systemNanotechnologyNano-Phase (matter)CrystallographyComposite materialChemistryGrapheneOpticsOrganic chemistry

Abstract

fetched live from OpenAlex

The interesting properties of hexagonal boron nitride (h-BN) and its potential uses in thermo-structural advanced applications have been limited or restricted by its inherent brittleness, which can easily be eliminated by its fibers (h-BN) in nanoscale dimensions. The current study is based on the synthesis of nanoscale 10B-enriched fibers of h-BN (10BNNFs) from 10B in the precursors instead of B in two-hour annealing at 900 °C and one-hour growth at 1000 °C. All of the 10BNNFs are randomly curved and highly condensed or filled from 10h-BN species with no internal space or crack. XRD peaks reported the 10h-BN phase and highly crystalline nature of the synthesized 10BNNFs. 10h-BN phase and crystalline nature of 10BNNFs are confirmed from high-intensity peaks at 1392 (cm−1) in Raman and FTIR spectroscopes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.022
GPT teacher head0.288
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2021
Admission routes1
Has abstractyes

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