Characterization the Laser Cleaning Effects on Sandstone From the Canadian Parliament Building
Bibliographic record
Abstract
Laser cleaning has been used in the rehabilitation and conservation program of the Canadian Parliament Buildings in order to remove the black crust on sandstone surfaces. This study was carried out to characterize the effect of laser cleaning on sandstone from the Canadian Parliament Buildings. First, characteristics of the sandstone and the black crust itself were studied using microscopy, x-ray fluorescence (XRF) spectroscopy, and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS). Two kinds of sandstone samples, Berea/Ohio sandstone and Nepean sandstone, were taken from the West Block of the Parliament Buildings for testing. The results showed that the black crust was a very thin layer covering the surface of the quartz grains and also filling the gaps between the quartz grains on the surface of the sandstone. The characteristic elements of the black crust were sulfur (S), calcium (Ca), iron (Fe), and lead (Pb). Copper (Cu) and chlorine Cl were detected in some samples. Gypsum in the black crust was confirmed by the back-scattered electron (BSE) images. The Fourier transform infrared (FTIR) spectroscopy results indicated that the organic materials of the black crust contained hydrocarbon oil. Second, surface morphology and elemental composition before and after laser cleaning were studied by microscopy, XRF, and SEM-EDS. The cleaning effect of three laser cleaning systems was discussed in terms of cleaning effectiveness and damage to the sandstone. The results showed that the black crust on the Berea/Ohio sandstone and the Nepean sandstone can be removed by using the LaserArt-100 Cleaning System, the main focus of the study, but that residues of the black crust were still found on the cleaned surface and caused the color of cleaned surface was darker than the fresh sandstone surface. Gypsum crystals were also identified on the cleaned surfaces. XRF and SEM-EDS results indicated that the characteristic elements of the black crust still existed in the residues. No direct damage was found on the cleaned surface. The results of the RILEM tests showed the water absorption rate of the cleaned Berea/Ohio sandstone was increased significantly after laser cleaning. The water absorption rate of the cleaned Nepean sandstone was a little higher than that of the black crust surface, which was near zero. The sandstone would be vulnerable to weathering caused by water when water absorption rate increased. Therefore, keeping some residues during the laser cleaning would benefit the long-term preservation of the sandstone surface because the residues can prevent water infiltration
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".