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Record W6950427763 · doi:10.5683/sp3/id9dqx

Additive manufacturing of a super toughened biodegradable polymer blend: Structure-property-processing correlation and 3D printed prosthetic part development

2024· dataset· en· W6950427763 on OpenAlexaff

Bibliographic record

VenueBorealis · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsDiscovery Centre
Fundersnot available
KeywordsInfill3d printedUltimate tensile strengthIzod impact strength test3D printingFlexural strengthNozzleRaster graphics

Abstract

fetched live from OpenAlex

Super toughened polymer materials have garnered significant attention from the scientific and industrial communities due to their vast application potential. However, a notable gap exists in the exploration of additive manufacturing (AM) of biodegradable polymer blends with enhanced impact resistance. This research addresses this gap by investigating the AM of a resilient green blend comprising PLA, BioPBS, and PBAT to achieve an enhanced impact resistance. To characterize the blend, rheological analysis, differential scanning calorimetry, thermomechanical analysis, and mechanical testing were performed. The printing parameters varied were the nozzle temperature, infill density, top and bottom solid layer raster angles, and infill pattern. This study is the first attempt to investigate the impact of the raster angle of top and bottom solid layers, which is important for determining the structural integrity of printed objects. The study revealed that a nozzle temperature of 180 °C, a rectilinear infill pattern, 100% infill density, and solid layers raster angle of 0° resulted in high mechanical properties with a notched Izod impact strength of 489.75 ± 16.6 J/m. Additionally, the study compared the mechanical properties of 3D printed and injection-molded samples. The 3D printed samples demonstrated comparable tensile strength to injection-molded samples, with only a 2% difference, and exhibited higher tensile and flexural moduli, showcasing 8 and 10% increases, respectively. However, there was a 10% decrease in impact strength compared to that of the injection-molded counterparts. These findings indicate that the 3D printed blend offers mechanical properties comparable to injection molding, making it a promising alternative for biomedical applications. A 3D printed leg prosthesis prototype has been developed using the formulated blend at optimized printing conditions.

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)0.000
metaresearch head score (Gemma)0.000
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: Dataset · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.236
Teacher spread0.222 · 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
GenreDataset

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

Citations0
Published2024
Admission routes1
Has abstractyes

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