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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".