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Record W2888818829 · doi:10.1002/slct.201801544

pH‐Switchable Water‐Soluble Boron Nitride Nanotubes

2018· article· en· W2888818829 on OpenAlexaff
Jingwen Guan, Keun Su Kim, Michael B. Jakubinek, Benoît Simard

Bibliographic record

VenueChemistrySelect · 2018
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsBoron nitrideSolubilityAqueous solutionBoronBromineHydrogen bondYield (engineering)ChemistryInorganic chemistryMaterials scienceChemical engineeringOrganic chemistryMolecule

Abstract

fetched live from OpenAlex

Abstract The first example of aqueous solutions of boron nitride nanotubes (BNNTs) with switchable stability and without use of surfactants is demonstrated. The as‐produced boron nitride nanotubes are both purified and solubilized through an environmentally friendly and scalable approach using water extraction and liquid bromine treatment. This treatment effectively removes elemental boron particles and excess bromine reacts with BNNTs, inducing B−N bond cleavage on the BNNT surface to yield hydroxyl (OH) and amino (NH 2 ) functionalized BNNTs. The resulting functionalized BNNTs form stable aqueous solutions around neutral pH (4 < pH < 8), but readily precipitate in other pH ranges. This switchable solubility is explained in terms of the capability of the functional groups (OH and NH 2 ) to form hydrogen‐bonding networks in water. Further, the solubility differences in selected polar organic solvents have been utilized to prepare functionalized BNNTs with higher purity.

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 head0.013
GPT teacher head0.265
Teacher spread0.252 · 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

Citations31
Published2018
Admission routes1
Has abstractyes

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