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Record W2746444728

Fabrication and characterization of biomimetic dry adhesives supported by foam backing material

2017· dissertation· en· W2746444728 on OpenAlexfundno aff
Kelvin Chia Wei Liew

Bibliographic record

VenueUWSpace (University of Waterloo) · 2017
Typedissertation
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsCharacterization (materials science)AdhesiveFabricationMaterials scienceMetal foamNanotechnologyComposite materialPolymer scienceMedicine
DOInot available

Abstract

fetched live from OpenAlex

Using sacrificial templates to create 3D structures is commonly employed in various fields such as tissue engineering and water remediation to create complex and high surface area scaffolds. Herein, several sacrificial templating techniques are tried, tested, and evaluated and several methods for creating 3D porous material are discussed, including: solvent casting particulate leaching (SCPL) and simple sugar and salt leaching. The porous material is then integrated with polymer soft lithography patterning to create a single functionally graded adhesive (FGA) material to use in dry adhesive applications. The use of a soft foam backing layer helps to improve the compliance and flexibility of the adhesive pad, thus enhancing peel tolerance, buckling, and deflection and vibration resistance.
\nA dry FGA based on film-terminated silicone foam is developed utilizing the polymer foam's capacity to absorb large amounts of energy and so deliver high adhesion and peel resistance. The fabrication technique is based on simple sugar cube templating of common elastomers, followed by film termination of the polymer cubes using the same material. Dependencies of the pull-off adhesive force and energy release rate on preload and foam thickness are systematically investigated through a series of axisymmetric indentation/de-bonding tests. The contribution of the foam backing layer to the overall compliance and adhesion is analysed and discussed. The developed elastic film-terminated structure strongly enhances the pull-off force and work of adhesion, and can be employed in the transport of delicate objects, as demonstrated in the pick and place of a silicon wafer. Furthermore, the proposed foam-based FGAs can be readily detached from the adherent surface by applying shear deformation between the pad and the surface. This research clarifies the role of mechanical graded properties in adhesion and can have technical implications in the development of a simple but effective dry adhesive material for mounting and transporting objects using automated robotic devices.
\nThe film terminated dry adhesive pads were further developed to investigate the feasibility of using a foam backing material as a universal platform to improve the adhesive properties of other terminal surface morphologies. Integrating other fast prototyping technologies as an alternative to lithographic templating techniques, scaled acrylonitrile butadiene styrene (ABS) 3D printed mushroom capped terminal structures are determined to be comparable to polyacrylate microstructure templated moulds. The effect of the foam is systematically evaluated using a similar axisymmetric indentation/de-bonding test with a probe of a large radius of curvature. Contact splitting through the control of terminal structures in both micro and millimetre scales shows improved contact properties with the addition of foam backing material. The mushroom capped adhesive pads are employed to demonstrate shear peel tolerance and cold temperature surface tolerance demonstrations.
\nLastly, various sugar and salt templating techniques are explored and optimized for consistency and repeatability to select the material most suitable for current research. Statistical analysis is used in the selection process. A linearly approximated model to determine the pull-off force from foam porosity and stiffness parameters are reported as sample candidates. Model estimates find that the density of sugar granules and the applied preload force are the mostly significant contributors to increasing pull-off force.

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 score0.062
Threshold uncertainty score0.865

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 head0.008
GPT teacher head0.187
Teacher spread0.179 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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