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Record W3087969825 · doi:10.1149/2162-8777/abb8ef

Review—Two-Dimensional Boron Carbon Nitride: A Comprehensive Review

2020· review· en· W3087969825 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueECS Journal of Solid State Science and Technology · 2020
Typereview
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaOntario Centres of Excellence
KeywordsMaterials scienceGrapheneNanotechnologyCarbon fibersBoron nitrideCarbon nitrideTernary operationSupercapacitorFabricationLithium (medication)BoronNitrideSemiconductorHexagonal boron nitrideEngineering physicsCapacitanceComputer scienceOptoelectronicsCatalysisChemistryElectrodePhysical chemistryPhysicsComposite numberPhotocatalysis

Abstract

fetched live from OpenAlex

Two-dimensional Boron Carbon Nitride (BCN) is a complex ternary system that has recently attracted great attention due to its ability to be tuned over a range of chemical, optical and electrical properties. In the last decade, BCN structures have been extensively researched for many energy-related applications, from supercapacitors and lithium ion batteries to electrocatalysts and sensors. However, the stoichiometry dependent properties of BCN as well as the difficult-to-control domain distribution of boron, carbon, and nitrogen atoms throughout the planes result in challenges for the fabrication of devices with reproducible performance. This review starts by discussing the fundamental properties of BCN as compared to its parent compounds (hexagonal boron nitride and graphene). Then the fabrication methods are comprehensively reviewed, analyzing each method’s advantages and shortcomings. This is followed by an explanation of BCN characteristics while particular attention is given to the surface chemistry and engineering of nanosheets. Applications of two dimensional BCN will also be reviewed to illustrate its significance over the last decade. Lastly, future trends and prospects of BCN structures will be reviewed, indicating on-going areas of research and the possible integration of BCN in semiconductor and energy-related applications.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.004
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.042
GPT teacher head0.382
Teacher spread0.339 · 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