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Record W4407901712 · doi:10.1016/j.jmps.2025.106090

Control of competing delamination in peeling-based microtransfer printing

2025· article· en· W4407901712 on OpenAlexafffund
Aoyi Luo, Yiping Zhou, Yunfeng Yan, Changhong Cao

Bibliographic record

VenueJournal of the Mechanics and Physics of Solids · 2025
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsDelamination (geology)Materials scienceControl (management)Composite materialMechanical engineeringComputer scienceArtificial intelligenceEngineeringGeologyPaleontology

Abstract

fetched live from OpenAlex

This paper investigates the mechanics of peeling-based microtransfer printing, focusing on the competing delamination at the stamp/ink and the ink/substrate interfaces under both high-degree and zero-degree peeling configurations. We found that the thickness and modulus contrast between the stamp and the ink significantly affect the ratio of the energy release rates at these two interfaces. Our findings also reveal that high-degree peeling has limited capability in promoting the printing of thin inks, whereas zero-degree peeling shows significant potential in facilitating this process. Experimental validations were performed to verify the proposed mechanics. Based on these insights, we discussed several strategies to tune the ratio of the energy release rates at the two interfaces to achieve controlled microtransfer printing, and conducted case studies and performed simple demonstrations to illustrate the practical applications of these strategies.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.215
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 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

Citations3
Published2025
Admission routes2
Has abstractyes

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