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Hydrogels with multiple characteristic pore dimensions: From transport properties to multifunctional materials

2025· article· en· W4417214353 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProgress in Polymer Science · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSelf-healing hydrogelsPolymerPorositySwelling

Abstract

fetched live from OpenAlex

Hydrogels with multiple characteristic pore dimensions (HMPs) have emerged as a powerful class of soft materials inspired by biological systems. By incorporating distinct average pore sizes into a single network, simultaneous control over competing hydrogel transport properties can be achieved, including throughput and selectivity, both of which are important in drug delivery, tissue engineering, catalysis, sensing, and water remediation hydrogel applications. This review highlights recent advances in the design, synthesis, characterization, and applications of HMPs. It highlights the fundamental principles of transport in these hydrogels, including the role of spatial arrangement of regions with different pore dimensions in probe mobility and fluid flow. Experimental and theoretical characterization of distinct pore dimensions in HMPs is followed by the discussion of the contribution of multiple pore dimensions to HMP functionality. The review provides the summary of the strategies for fabricating HMPs and their applications. An outlook highlights key challenges and future opportunities in this field to advance HMPs as the new generation of hydrogel-based materials for diverse applications.

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.

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 score0.029
Threshold uncertainty score0.617

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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