AN ELECTRICAL RESISTANCE MONITOR STUDY OF THE POST-EXCAVATION CORROSION OF ARCHAEOLOGICAL IRON
Bibliographic record
Abstract
Electrical Resistance Corrosion Monitoring (ERCM) is a non-destructive method commonly applied in industry and which can detect the onset of corrosion and interferences in any type of corrosive environment. Furthermore, it does not necessarily require the presence of a liquid electrolyte to monitor corrosion rate unlike other electrochemical techniques. The method has so far been applied in the field of museum conservation in the form of reference probes for museum showcases and storage rooms. This project has studied the application of ERCM to investigate the post-excavation corrosion of iron and to model the corrosion kinetics involved. Electrical resistance (ER) probes are manufactured with photochemical milling from thin iron foil in a serpentine pattern that produces higher sensitivity and faster response time. The iron oxyhydroxides which are commonly detected on excavated artefacts are formed on the ER probes’ surface in the lab with various chloride contaminations and the change of their ohmic resistance is monitored at 57% and 82% RH at 25oC. The identity of the corrosion products and the topography of the probes’ surface have been examined using XRD and SEM analysis. The sensitivity and the applicability of ERCM have been developed with respect to the thickness and the nature of iron corrosion and its products. It has proven to be responsive to the degree of chloride contamination and the ambient relative humidity (RH %) levels. It is now sensitive enough to record a mean corrosion rate of 50 μm per year and 600 μm per year within the first hour of monitoring the corroded ER probes at 57% RH and at 82% RH respectively. Data analysis provides information on the corrosion kinetics at the various stages of their exposure. Furthermore, ERCM has been applied to make an assessment of the chloride extraction treatments commonly used in the conservation laboratories by monitoring pre-treated probes at 90% RH and, thus, to monitor the effect of any residual chloride ions on the post-treatment atmospheric corrosion rate.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".