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Record W4225126729 · doi:10.1002/pc.26679

Evaluating the mechanical, thermal, and antibacterial properties of poly (lactic acid)/silicone rubber blends reinforced with (3‐aminopropyl) triethoxysilane‐functionalized titanium dioxide nanoparticles

2022· article· en· W4225126729 on OpenAlexaff
Raha Mokhtari Aghdami, Seyed Rasoul Mousavi, Sara Estaji, Reza Khalili Dermeni, Hossein Ali Khonakdar, Alireza Shakeri

Bibliographic record

VenuePolymer Composites · 2022
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsVancouver Island UniversityUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceCrystallinityTriethoxysilaneThermal stabilityComposite materialSilicone rubberNanoparticleTitanium dioxideSurface modificationNatural rubberSiliconeChemical engineeringNanotechnology

Abstract

fetched live from OpenAlex

Abstract Poly (lactic acid)/silicone rubber (PLA/SR) blends were reinforced with (3‐aminopropyl) triethoxysilane‐functionalized titanium dioxide nanoparticles, and the effect of the virgin (TDO) and functionalized (FTDO) nanoparticles was investigated in the presence and absence of compatibilizer. The results demonstrated that the functionalization of TDO had no negative effect on the morphology of the blends, and no aggregation was seen in the blends containing TDO and FTDO. Furthermore, nanoparticles were localized at the interface of PLA and SR. Adding TDO in the PLA/SR blends increased the mechanical properties. The same trend was observed after incorporating the compatibilizer and FTDO. Additionally, a good agreement was seen between the theoretical and experimental mechanical properties values. Moreover, introducing SR diminished the crystallinity of PLA, and further reduction was observed by adding TDO, FTDO, and compatibilizer. Also, the modification of TDO did not affect the crystallinity of the blends. Incorporating 1 and 2 phr TDO to the blends increased the thermal stability while diminishing with 3 phr TDO. In addition, FTDO improved thermal stability. The antibacterial test indicated that the higher nanoparticles content, the better the antibacterial properties.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.066
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.042
GPT teacher head0.250
Teacher spread0.209 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations33
Published2022
Admission routes1
Has abstractyes

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