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Record W7140960606

Wetting of Surface Grafted Hydrophilic‐b‐Hydrophobic Block Copolymer Brushes

2025· article· en· W7140960606 on OpenAlexfundno aff
B. Leibauer, A. de los Santos Pereira, D. Dorado Daza, Y. N. Wang, A. Hazrah, O. Pop‐Georgievski, H. Butt, R. Berger

Bibliographic record

VenueMPG.PuRe (Max Planck Society) · 2025
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsnot available
FundersHORIZON EUROPE Marie Sklodowska-Curie ActionsNatural Sciences and Engineering Research Council of CanadaDeutsche ForschungsgemeinschaftGrantová Agentura České RepublikyAlexander von Humboldt-Stiftung
KeywordsCopolymerWettingContact anglePolystyreneBrushMonolayer
DOInot available

Abstract

fetched live from OpenAlex

The wetting of diblock copolymer brushes by water is studied.Th goal of this work is to understand how the thickness of the bottom and top copolymer block affect the wetting behavior, respectively.For the synthesis of diblock copolymer brushes the bottom block, a hydrophilic poly(2-hydroxyethyl methacrylate) (PHEMA) brush is grafted from a undecyl-trichloro-selfassembled monolayer on silicon wafer.Then the top block, a hydrophobic polystyrene (PS) or poly(2-ethylhexyl methacrylate) (PEtHexMA) is grafted from the PHEMA block.Hereby, a hydrophilic-b-hydrophobic diblock copolymer is obtained.The top copolymer block determines the advancing contact angle of the copolymer brushes in their pristine state.The receding contact angle depends on the thickness of the top and bottom copolymer block.For a top copolymer thickness <30 nm the receding contact angle decreased.An increase in the thickness of the bottom block to 35 nm decreases the receding contact angle as well.By exposing the diblock copolymer brush with a thickness of the top block >30 nm to warm water the wetting properties switch from a hydrophobic to a hydrophilic.The surface switches back to the hydrophobic state by exposing it to toluene and subsequent temperature annealing.

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 categoriesMeta-epidemiology (narrow)
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 score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.252
Teacher spread0.244 · 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.

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
Published2025
Admission routes1
Has abstractyes

Explore more

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