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Record W3022580245 · doi:10.1002/advs.201902307

Multi‐Material 3D and 4D Printing: A Survey

2020· review· en· W3022580245 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

VenueAdvanced Science · 2020
Typereview
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
Keywords3D printingComputer scienceProcess (computing)Dimension (graph theory)Three dimensional printingManufacturing engineering3d printedComputer-aided technologiesEmerging technologiesNanotechnologySystems engineeringEngineeringMechanical engineeringMaterials scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Recent advances in multi-material 3D and 4D printing (time as the fourth dimension) show that the technology has the potential to extend the design space beyond complex geometries. The potential of these additive manufacturing (AM) technologies allows for functional inclusion in a low-cost single-step manufacturing process. Different composite materials and various AM technologies can be used and combined to create customized multi-functional objects to suit many needs. In this work, several types of 3D and 4D printing technologies are compared and the advantages and disadvantages of each technology are discussed. The various features and applications of 3D and 4D printing technologies used in the fabrication of multi-material objects are reviewed. Finally, new avenues for the development of multi-material 3D and 4D printed objects are proposed, which reflect the current deficiencies and future opportunities for inclusion by AM.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.051
GPT teacher head0.309
Teacher spread0.258 · 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