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Performance of Clay, SiO<sub>2</sub>, Ca(OH)<sub>2 </sub>and CaCO<sub>3</sub> - Polymeric Nanocomposites for Conservation and Preservation of Limestone Artworks

2018· preprint· en· W2790127485 on OpenAlexfundno aff
Mohammad Aldoasri, S. Darwish, Mahmoud A. Adam, Nagib A. Elmarzugi, Sayed M. Ahmed

Bibliographic record

VenuePreprints.org · 2018
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsnot available
FundersKing Abdulaziz City for Science and TechnologyMcMaster University
KeywordsMaterials scienceNanocompositeNanoparticlePolymerChemical engineeringWeatheringNanomaterialsCrystallizationComposite materialCopolymerNanotechnology

Abstract

fetched live from OpenAlex

Environmental deterioration factors are constantly increasing, causing unwanted aesthetic changes to stone artworks due to exposure to various physical and chemical deterioration factors. Inorganic nanoparticle-filled polymer composites have extended their multiple functionalities to various applications, including cultural heritage conservation. Therefore, this study has examined the effects of clay, SiO2, Ca(OH)2 and CaCO3 nanomaterials in the enhancement of the physicomechanical properties of limestone monuments, the aim of the present work being to evaluate comparatively the effectiveness of nanoparticles as consolidation and protection material for limestone artworks. The nanoparticles were added to an acrylic-based copolymer (polyethylmethacrylate (EMA)/methylacrylate (MA) (70/30), in order to improve its physiochemical and mechanical properties, and produced a significant improvement in the ability of the polymers to consolidate and protect the stone. The synthesis process of nanoparticles/polymer nanocomposite has been prepared by an in situ emulsion polymerization system. The nanocomposites contained poly (EMA/MA) with a solid content of 3% [poly (EMA/MA)] in the absence and presence of 5% nanoparticles (0.15 g nanoparticles). Samples were subjected to artificial aging by relative humidity/temperature and acid/salt crystallization weathering to show the optimum conditions of durability and the effectiveness of the nano-mixture in improving the physical and mechanical properties of the stone material. To ensure that the treatment had no negative effects on the physical characteristics of the limestone, the properties of the treated limestone samples were evaluated comparatively before and after artificial aging by the conduct of microstructural (phase morphology studied by means of scanning electron microscopy) and aesthetic (colour and lightness measured by spectrophotometry) analyses. Also used were measurement of static contact angle of water droplets on the surface of the samples, total immersion water absorption, compressive strength, and abrasion resistance test. Results demonstrated that the addition of nanoparticles to an acrylic-based polymer enhanced its capability to consolidate and protect the limestone samples.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0020.001
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 head0.044
GPT teacher head0.257
Teacher spread0.214 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2018
Admission routes1
Has abstractyes

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