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Record W3120768630 · doi:10.1038/s41467-020-20256-3

Direct printing of functional 3D objects using polymerization-induced phase separation

2021· article· en· W3120768630 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.

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsOntario Tech UniversityCarleton UniversityNational Research Council Canada
Fundersnot available
Keywords3D printingMaterials scienceFabricationNanotechnologyPolymerizationComputer scienceFunctional polymersPolymerComposite material

Abstract

fetched live from OpenAlex

3D printing has enabled materials, geometries and functional properties to be combined in unique ways otherwise unattainable via traditional manufacturing techniques, yet its adoption as a mainstream manufacturing platform for functional objects is hindered by the physical challenges in printing multiple materials. Vat polymerization offers a polymer chemistry-based approach to generating smart objects, in which phase separation is used to control the spatial positioning of materials and thus at once, achieve desirable morphological and functional properties of final 3D printed objects. This study demonstrates how the spatial distribution of different material phases can be modulated by controlling the kinetics of gelation, cross-linking density and material diffusivity through the judicious selection of photoresin components. A continuum of morphologies, ranging from functional coatings, gradients and composites are generated, enabling the fabrication of 3D piezoresistive sensors, 5G antennas and antimicrobial objects and thus illustrating a promising way forward in the integration of dissimilar materials in 3D printing of smart or functional parts.

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 score0.035
Threshold uncertainty score0.470

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 head0.039
GPT teacher head0.316
Teacher spread0.277 · 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