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Record W4380534840 · doi:10.1016/j.cartre.2023.100273

The base versus tip growth mode of carbon nanotubes by catalytic hydrocarbon cracking: Review, challenges and opportunities

2023· article· en· W4380534840 on OpenAlexaff
Xinlong Chen, Xin Pang, Clémence Fauteux‐Lefebvre

Bibliographic record

VenueCarbon Trends · 2023
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsNatural Resources CanadaUniversity of Ottawa
Fundersnot available
KeywordsCarbon nanotubeMaterials scienceCatalysisNucleationCarbon fibersNanotechnologyMethaneCokeCrackingHydrocarbonChemical engineeringFluid catalytic crackingComposite materialChemistryOrganic chemistryMetallurgyComposite number

Abstract

fetched live from OpenAlex

Hydrogen gas production using catalytic hydrocarbon cracking on metal nanoparticles has become a vital bridge technology, as this process, unlike the traditional methane-based reforming process, does not co-produce carbon gasses (e.g., CO, CO2). The major benefit of direct catalytic methane cracking using a nanostructured catalyst is the formation of solid carbon in high-value products, such as carbon nanotubes (CNTs) or filaments. This solid carbon can then be removed physically and valorized. However, it is challenging to design a catalyst capable of sustaining its activity after solid carbon has started to deposit and grow, meanwhile preventing the formation of coke. For CNTs, in particular, the base growth mode of CNTs is the desired pathway, as the catalyst can then be regenerated and re-used. If the CNTs are formed under the tip-growth mode, the catalyst particle will be lifted off the support of the regeneration and reusability is lost. Therefore, the study of CNTs growth modes is a vital topic, both experimentally and theoretically, of designing appropriate catalysts. To date, enormous efforts have been made to investigate conditions where the CNTs base growth mode can be maintained during the carbon deposition process. Several possible correlations and mechanisms regarding the base growth mode have been explored and established. Theoretical calculations and numerical simulations across length scales were conducted to investigate the nucleation mechanism and growth of CNTs. Density functional theory (DFT), classical and quantum-based molecular dynamics (MD) and Monte Carlo (MC) simulations were also carried out to study the initial CNT cap formation and its encapsulation during the catalytic hydrocarbon cracking process. A thermodynamics-based nucleation formula of CNTs for both the base and tip growth modes was also established. However, there is still no consensus on what determines the CNT growth modes and what the roles are of the various influencing factors such as the nanoparticle size, the oxidation state of the catalyst, the mechanical properties of CNT, and the catalyst-support interaction. This paper reviews the current status of CNT's growth mechanism development. The benefits and limitations of theory and modeling approaches concerning CNT growth modes are discussed.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.050
GPT teacher head0.283
Teacher spread0.233 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations42
Published2023
Admission routes1
Has abstractyes

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