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Record W4410946596 · doi:10.1021/acsomega.4c11420

Deposition of Ag/TMC Nanoparticles via MAPLE to Enhance the Mechanical and Antimicrobial Properties of Silicone Hydrogel

2025· article· en· W4410946596 on OpenAlexafffund
Hossein Pouri, Chao Lu, Andrés Rodrı́guez, José E. Herrera, Jin Zhang

Bibliographic record

VenueACS Omega · 2025
Typearticle
Languageen
FieldEngineering
TopicGraphene and Nanomaterials Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMapleSiliconeDeposition (geology)AntimicrobialMaterials scienceNanoparticleNanotechnologyChemical engineeringPolymer chemistryChemistryComposite materialOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Surface treatment of silicone hydrogels is essential for achieving suitable mechanical properties and high antimicrobial effectiveness. Incorporating biocompatible nanostructures into a silicone hydrogel can improve its mechanical strength and hydrophilicity. However, few studies have focused on directly depositing hybrid nanostructures onto a silicone hydrogel to enhance both its antimicrobial effectiveness and mechanical properties. Additionally, the impact of environmental conditions, such as hydration and physiological temperature, on the mechanical behavior of the nanostructure-deposited silicone hydrogel remains unclear. Herein, matrix-assisted pulsed laser evaporation (MAPLE) with a pulsed Nd:YAG laser at 532 nm has been applied to directly deposit silver/ N, N, N -trimethyl chitosan nanoparticles (Ag/TMC NPs) on the surface of silicone hydrogels. The effect of MAPLE irradiation time ( t ) on the deposition of organic–inorganic hybrid nanostructures on the silicone hydrogel has been studied. The Young’s modulus of silicone hydrogel deposited with Ag/TMC NPs increased from 76 to 139.38 kPa when t increases from 0 to 120 min. Meanwhile, the mechanical behavior of the silicone hydrogel deposited with Ag/TMC NPs was evaluated at different swelling states and environmental conditions, showing that the mechanical strength of the hydrogel strongly depends on hydration and temperature. On the other hand, the antimicrobial efficiency of silicone hydrogel deposited with Ag/TMC NPs against Escherichia coli ( E. coli ) and Staphylococcus aureus ( S. aureus ) increased by approximately 83.8 and 114.7%, respectively, when t increases from 0 to 120 min. In addition, NIH3T3 cells treated with a silicone hydrogel with/without the deposition of hybrid nanostructures were analyzed, indicating that the deposited nanostructures do not exhibit toxic effects on cells. Overall, this study demonstrates the versatility of MAPLE as a technique for depositing hybrid nanostructures onto silicone hydrogels to achieve improved mechanical and antimicrobial 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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.176

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2025
Admission routes2
Has abstractyes

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