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Record W2314838919 · doi:10.7209/tanso.2002.7

KOH Activation Method of a Mesophase Pitch-based Carbon Fiber

2002· article· en· W2314838919 on OpenAlexaff
Takashi Maeda, Young Jung Kim, K. Koshiba, K. Ishii, Toshiyuki Kasai, Morinobu Endo, Yoshiyuki Nishimura, Yuji Kawabuchi

Bibliographic record

VenueTANSO · 2002
Typearticle
Languageen
FieldChemistry
TopicAerogels and thermal insulation
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsMesophaseMaterials scienceActivated carbonAdsorptionSpecific surface areaComposite materialFiberChemical engineeringChemistryOrganic chemistryCatalysisLiquid crystal

Abstract

fetched live from OpenAlex

At present, activated carbon fiber (ACF) generally consists of materials such as cellulose, acrylic phenol and so on. Activated carbon fiber is usually made by gas activation by CO2, and steam. Mesophase pitch-based carbon fiber (MPCF) has been developed to achieve higher strength and elasticity. Due to the difficulty of activating the MPCF using conventional methods, it has not been used as a starting material for ACFs. In spite of having such difficulties, the development of new activation method can lead us to a new ACF having pore structure and adsorption property different from conventional materials.In this paper, we present the study on the relation between the newly developed KOH activation method and the specific surface area of the activated MPCFs by changing the activating conditions. Using our method, we could suc-cessfully control the specific surface area of the MPCF-based ACFs. This activation method proved to be promising for the development of the ACFs with novel characteristics.

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 score0.002

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)0.0000.000

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 head0.028
GPT teacher head0.269
Teacher spread0.241 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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