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Record W4392163811 · doi:10.18280/acsm.480108

Comparative Study on Dry and Wet Wear Characteristics of Ultra-High Molecular Weight Polyethylene Composites Reinforced with Direct Precipitated Nano Zinc Oxide

2024· article· en· W4392163811 on OpenAlex
Venkata Ramana Murty Yerubandi, Venkata Subbaiah Kambagowni, Jagannadha Kameswara Prasad Ayyagari, Yeshvantha Hirisave Sathyanarayana, Chethan Devarahatti

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2024
Typearticle
Languageen
FieldEngineering
TopicTribology and Wear Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceZincComposite materialNano-Ultra-high-molecular-weight polyethylenePolyethyleneOxideDry frictionMetallurgy

Abstract

fetched live from OpenAlex

The tribological behavior of Ultra-High Molecular Weight Polyethylene (UHMWPE) composites, reinforced with nano-sized Zinc Oxide (ZnO) particles, was systematically investigated under both dry and wet conditions.Composites were fabricated via hot compression molding, ensuring homogeneous nanoparticle distribution and effective bonding.Wear rates in dry conditions were assessed using a pin-on-disc apparatus, with a composite pin against a 63 HR EN31 steel disc, while wet tribology tests employed distilled water as a lubricant.Post-experimental Scanning Electron Microscopy (SEM) analyses revealed distinct wear mechanisms between the two environments.Under dry conditions, an increase in wear rates and frictional forces was observed for the composites, whereas the introduction of water as a lubricant significantly reduced wear rates in wet conditions.The presence of nano ZnO was found to enhance the mechanical properties and wear resistance of UHMWPE, particularly in the presence of lubrication.When subjected to a 100rpm and 10N load, the UHMWPE composite with a 10wt% ZnO filler exhibited a marked reduction in weight loss (1.1mg) in comparison to the unfilled UHMWPE (5.1mg).This improvement was sustained at elevated speeds and loads, indicating that higher filler concentrations correlate with improved wear resistance.Wet wear testing further demonstrated the advantageous role of nano ZnO, with UHMWPE composites incurring less weight loss than their unfilled counterparts.The hydrophobic nature of nano ZnO was instrumental in reducing wear under lubricated conditions.These findings underscore the potential for nano ZnO reinforced UHMWPE composites in applications demanding high wear resistance, such as in biomedical implants and automotive components.Moreover, the hydrophobic properties of nano ZnO suggest additional benefits in wet environments.Future work should focus on optimizing nano ZnO loadings for maximum wear resistance and exploring the integration of other reinforcing agents to create composites with multifaceted functional attributes.

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)0.000
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 score0.155
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.247
Teacher spread0.234 · 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