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Record W7083314993 · doi:10.1016/j.physb.2025.417808

Exploring oxygen dissociation on hexagonal boron nitride: Insight from high-temperature molecular dynamics simulation

2025· article· en· W7083314993 on OpenAlexaff

Bibliographic record

VenuePhysica B Condensed Matter · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsSafran Electronics (Canada)
FundersEuropean Commission
KeywordsReaxFFDissociation (chemistry)Molecular dynamicsChemisorptionOxygenHexagonal boron nitrideAdsorptionActivation energy

Abstract

fetched live from OpenAlex

Hexagonal boron nitride (h-BN), known for its exceptional thermal and chemical stability, is widely used in high-temperature applications and as an encapsulation layer for other two-dimensional materials. This study examines the dissociation mechanisms of O 2 molecules on the h-BN surface, focusing on activation energies and minimum energy pathways at different adsorption sites using climbing-image nudged elastic band (CI-NEB) calculations. The results reveal several dissociation pathways with significant variations in activation barriers depending on site and configuration, including one low-barrier route favorable for surface reactions. Reactive molecular dynamics (RMD) simulations with the ReaxFF force field are employed to investigate oxidation behavior in multilayer h-BN at 900 K, 1200 K, and 1500 K. At 900 K, O 2 adsorbs without penetrating beneath the surface, while higher temperatures enhance dissociation and promote deeper oxygen incorporation. Charge analysis at elevated temperatures shows stronger chemisorption and electron transfer, forming a more uniform, chemically bonded oxygen layer.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.148
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.018
GPT teacher head0.229
Teacher spread0.211 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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