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Record W2076921505 · doi:10.1039/c4nr02041c

Three-dimensional printing of freeform helical microstructures: a review

2014· review· en· W2076921505 on OpenAlexaff
Rouhollah D. Farahani, Kambiz Chizari, Daniel Therriault

Bibliographic record

VenueNanoscale · 2014
Typereview
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsPolytechnique Montréal
Fundersnot available
Keywords3D printingFabricationMaterials scienceMicrofabricationFused deposition modelingNanotechnologyMicrostructureDeposition (geology)Fused filament fabricationMicroelectromechanical systemsMicroelectronicsComposite material

Abstract

fetched live from OpenAlex

Three-dimensional (3D) printing is a fabrication method that enables creation of structures from digital models. Among the different structures fabricated by 3D printing methods, helical microstructures attracted the attention of the researchers due to their potential in different fields such as MEMS, lab-on-a-chip systems, microelectronics and telecommunications. Here we review different types of 3D printing methods capable of fabricating 3D freeform helical microstructures. The techniques including two more common microfabrication methods (i.e., focused ion beam chemical vapour deposition and microstereolithography) and also five methods based on computer-controlled robotic direct deposition of ink filament (i.e., fused deposition modeling, meniscus-confined electrodeposition, conformal printing on a rotating mandrel, UV-assisted and solvent-cast 3D printings) and their advantages and disadvantages regarding their utilization for the fabrication of helical microstructures are discussed. Focused ion beam chemical vapour deposition and microstereolithography techniques enable the fabrication of very precise shapes with a resolution down to ∼100 nm. However, these techniques may have material constraints (e.g., low viscosity) and/or may need special process conditions (e.g., vacuum chamber) and expensive equipment. The five other techniques based on robotic extrusion of materials through a nozzle are relatively cost-effective, however show lower resolution and less precise features. The popular fused deposition modeling method offers a wide variety of printable materials but the helical microstructures manufactured featured a less precise geometry compared to the other printing methods discussed in this review. The UV-assisted and the solvent-cast 3D printing methods both demonstrated high performance for the printing of 3D freeform structures such as the helix shape. However, the compatible materials used in these methods were limited to UV-curable polymers and polylactic acid (PLA), respectively. Meniscus-confined electrodeposition is a flexible, low cost technique that is capable of fabricating 3D structures both in nano- and microscales including freeform helical microstructures (down to few microns) under room conditions using metals. However, the metals suitable for this technique are limited to those that can be electrochemically deposited with the use of an electrolyte solution. The highest precision on the helix geometry was achieved using the conformal printing on a rotating mandrel. This method offers the lowest shape deformation after printing but requires more tools (e.g., mandrel, motor) and the printed structure must be separated from the mandrel. Helical microstructures made of multifunctional materials (e.g., carbon nanotube nanocomposites, metallic coated polymer template) were used in different technological applications such as strain/load sensors, cell separators and micro-antennas. These innovative 3D microsystems exploiting the unique helix shape demonstrated their potential for better performance and more compact microsystems.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.021
GPT teacher head0.271
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations162
Published2014
Admission routes1
Has abstractyes

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