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Record W4386606505 · doi:10.1002/adem.202301048

Biopolymer Composites Material Extrusion and their Applications: A Review

2023· review· en· W4386606505 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

VenueAdvanced Engineering Materials · 2023
Typereview
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of TorontoUniversity of Alberta
FundersBeijing Municipal Education Commission
KeywordsMaterials science3D printingNanotechnologyElectronicsMicroscale chemistryInkwellExtrusionNanomaterialsStretchable electronicsFlexible electronicsPrinted electronicsComposite materialEngineering

Abstract

fetched live from OpenAlex

Advances in additive manufacturing are leading to the emergence of new printable applications, including sensors for healthcare monitoring and bioengineering scaffolds. Research is driven by designing new printable inks including composites that can be extruded and respond to changes in their surroundings and patterning these materials on the microscale. In modern printing techniques, an emerging modified three‐dimensional (3D) printing method: materials extrusion has been utilized for customizable electronics because of its high compatibility with various inks, low cost, and versatility to different levels of complexity. Material extrusion enables not only the printing of 2D and 3D architecture of the electrode structure but also the bioprinting of structures such as conductive scaffolds. In this review, fundamental insights into rational printable ink formulation including colloidal suspensions, gels, polymer melts, composites, printing criteria, processes, and applications toward printable electronics using composites composed of nanomaterials and biopolymers are fully discussed. New manufacturing insights on how to further improve the resolution and simplify the printing process of responsive materials are discussed, which have not been seen in currently published representative reviews. It is envisioned that this review provides high scientific merits to readers working in wearable devices, biological smart materials, and flexible nanoelectronics.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
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 head0.022
GPT teacher head0.268
Teacher spread0.246 · 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