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Record W3125039275 · doi:10.1186/s40824-021-00204-y

3D printing PCL/nHA bone scaffolds: exploring the influence of material synthesis techniques

2021· article· en· W3125039275 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

VenueBiomaterials Research · 2021
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials sciencePorositySolventComposite materialScaffoldPolycaprolactoneThermogravimetric analysisChemical engineeringModulusPolymerBiomedical engineeringChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

BACKGROUND: It is known that a number of parameters can influence the post-printing properties of bone tissue scaffolds. Previous research has primarily focused on the effect of parameters associated with scaffold design (e.g., scaffold porosity) and specific scaffold printing processes (e.g., printing pressure). To our knowledge, no studies have investigated variations in post-printing properties attributed to the techniques used to synthesize the materials for printing (e.g., melt-blending, powder blending, liquid solvent, and solid solvent). METHODS: Four material preparation techniques were investigated to determine their influence on scaffold properties. Polycaprolactone/nano-hydroxyapatite 30% (wt.) materials were synthesized through melt-blending, powder blending, liquid solvent, and solid solvent techniques. The material printability and the properties of printed scaffolds, in terms of swelling/degradation, mechanical strength, morphology, and thermal properties, were examined and compared to one another using Kruskal-Wallis nonparametric statistical analysis. RESULTS: Material prepared through the liquid solvent technique was found to have limited printability, while melt-blended material demonstrated the highest degree of uniformity and lowest extent of swelling and degradation. Scaffolds prepared with powder-blended material demonstrated the highest Young's modulus, yield strength, and modulus of resilience; however, they also demonstrated the highest degree of variability. The higher degree of inhomogeneity in the material was further supported by thermal gravimetric analysis. While scaffolds printed from melt-blended, powder-blended, and solid solvent materials demonstrated a high degree of micro-porosity, the liquid solvent material preparation technique resulted in minimal micro-porosity. CONCLUSIONS: Study results indicate that specific techniques used to prepare materials influence the printing process and post-printing scaffold properties. Among the four techniques examined, melt-blended materials were found to be the most favorable, specifically when considering the combination of printability, consistent mechanical properties, and efficient preparation. Techniques determined to be favourable based on the properties investigated should undergo further studies related to biological properties and time-dependent properties beyond 21-days.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.063
GPT teacher head0.303
Teacher spread0.241 · 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