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Record W2695500266 · doi:10.1295/koron.2015-0040

Adhesion Using the Covalent Bond Formation Reaction at the Soft Material Interface

2015· article· en· W2695500266 on OpenAlexaff
Tomoko Sekine, Yoshinori Takashima, Akihito Hashidzume, Hiroyasu Yamaguchi, Akira Harada

Bibliographic record

VenueKOBUNSHI RONBUNSHU · 2015
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsImpact
Fundersnot available
KeywordsCovalent bondAdhesionInterface (matter)Materials sciencePolymer chemistryChemical engineeringComposite materialChemistryOrganic chemistryWettingEngineering

Abstract

fetched live from OpenAlex

ボロン酸,およびヨードアリールをそれぞれの側鎖に有した高分子ゲルは,金属触媒を添加することにより接着した.これは高分子ゲル界面における鈴木・宮浦クロスカップリング反応によるものであり,ソフトマテリアルの界面で共有結合が形成され,二つの材料を接着することができた.このような材料間の接着は他の化学反応にも適用できる.銅触媒を用いたアジド–アルキン環化付加反応(CuAAC反応)や薗頭クロスカップリング反応を用いても,接触界面における共有結合の形成によって接着できた.この接触界面での共有結合形成は水中および有機溶媒中でも達成できる.さらに難易度の高い異種材料間の接着を試みた.高分子ゲルと無機材料である硬質ガラス基板のそれぞれにボロン酸またはヨードアリールを修飾し,鈴木・宮浦クロスカップリング反応による異種材料間接着を試みた.その結果,適切な組合せの場合のみ,高分子ゲルとガラス基板において,接着を確認した.このような接着は従来の接着剤を用いた接着とは異なり,有機溶媒に浸漬させても接着剤が溶解しないため,安定した接着を実現できた.界面での共有結合形成を利用した接着は有機材料–有機材料間だけでなく,有機–無機の異種材料間の接着においても新たな展開を示した.

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.239
Teacher spread0.214 · 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
Published2015
Admission routes1
Has abstractyes

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