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Record W4414376636 · doi:10.1002/adma.202505620

Arbitrarily Shapeable Couplant with Fluidity Onset for Conformal Ultrasound

2025· article· en· W4414376636 on OpenAlexaff
Jian Chen, Youlong Hua, Binjie Jin, Zhu Zhan, Mengru Zhang, Yuhua Zhang, Renan Jin, Xiaowen Liang, Ruijue Cao, Xinben Hu, Xingkun Man, Xijun Li, Baochun Guo, Bing‐Feng Ju, Qian Zhao

Bibliographic record

VenueAdvanced Materials · 2025
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsMcMaster University
FundersNatural Science Foundation of Zhejiang ProvinceNational Natural Science Foundation of China
KeywordsConformal mapUltrasoundIdeal (ethics)Stress (linguistics)Adaptability

Abstract

fetched live from OpenAlex

Couplant is indispensable for ultrasound examinations. However, shape adaptability and operational feasibility, which are both crucial, cannot be provided conjointly by existing couplants due to their either liquid or solid form. Here an ideal couplant composed of fibers and dynamically cross-linked polysilicone is reported, which exhibits a unique solid-to-fluid transition upon application of stress exceeding a threshold. Together with the acoustically transparent feature, the particularity of the stress-triggered fluidity allows conformal adapting to arbitrary geometries under stress exertion and stable preserving for long-term and reliable ultrasound examination after stress release. Steeply curved geometries and pressure-sensitive tissues, which are extremely challenging for the state-of-the-art ultrasound modalities, are successfully graphed or treated. This couplant integrates the merits of liquids and solids, providing new opportunities for various ultrasound in industrial and medical fields.

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)0.001
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 score0.043
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.254
Teacher spread0.248 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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