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Record W4382280766 · doi:10.1039/d3sm00670k

Thermal- and pH-responsive triple-shape memory hydrogel based on a single reversible switch

2023· article· en· W4382280766 on OpenAlexaff
Yufang Song, Hui Lv, Xiaorong Wang, Yi-Ming Chen, Weifeng Zhong, Weifu Dong, Dongjian Shi, Yang Wang, Piming Ma, Hongji Zhang

Bibliographic record

VenueSoft Matter · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsUniversité de Sherbrooke
FundersDepartment of Education of Liaoning ProvinceChina Postdoctoral Science Foundation
KeywordsShape-memory alloyThermalMaterials scienceChemistryChemical engineeringComposite materialThermodynamicsPhysicsEngineering

Abstract

fetched live from OpenAlex

Here we provide a novel method for fabricating a pH- and thermal-responsive triple-shape memory hydrogel based on a single reversible switch phase. A high-density quadruple hydrogen-bonding ureido-pyrimidinone (UPy) system was introduced into the hydrogel network, which can occur to varied degrees of dissociation under different pH and temperature conditions. Different degrees of dissociation and reassociation can be viewed as different subsets of memory elements to freeze and unfreeze the temporary shapes. Although this class of hydrogels contains only a single transition phase, they feature a large dissociative differential in response to varied external stimuli to provide multiple windows for programming different temporary shapes.

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 categoriesInsufficient payload (model declined to judge)
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 score0.189
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.001

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 head0.012
GPT teacher head0.212
Teacher spread0.199 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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