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Record W4401006392 · doi:10.1093/mam/ozae044.062

Challenges in Silver Conservation: Characterizing the Composition and Sources of Unusual Tarnish on Seleucid Silver Coins Using SEM-EDS

2024· article· en· W4401006392 on OpenAlexaff
Maria Stanko, Dian Yu, Laura Lipcsei, Jane Y. Howe, Doug D. Perovic

Bibliographic record

VenueMicroscopy and Microanalysis · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsRoyal Ontario MuseumUniversity of Toronto
Fundersnot available
KeywordsTarnishComposition (language)Materials scienceMetallurgyMineralogyNanotechnologyChemistryArtCopper

Abstract

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Due to its status as a noble metal, one might expect that silver, a material abundant in antiquity and cultural heritage, would require little or no conservation, particularly in controlled museum environments. While silver demonstrates greater resistance to oxidation compared with other ancient metals like copper, iron, lead, and tin [1], it possesses a vulnerability that complicates its long-term preservation. Silver exhibits an electrochemical affinity with sulfur, a contaminant that is naturally found in unregulated indoor environments, primarily in the form of hydrogen sulfide (H2S) and carbonyl sulfide (COS) [2]. This process, commonly known as ‘silver tarnishing’, is well-documented and characterized by the growth of silver sulfide (acanthite, Ag2S) on the metal’s surface [3]. Remarkably, airborne sulfur concentrations as minute as 0.2 ppb have been reported as sufficient to trigger silver sulfidation, with increased levels of moisture and sulfur accelerating the tarnishing rate [4]. Prolonged exposure to ambient indoor conditions can result in tarnish layers beyond 100 nm thick [5], giving the originally sleek and shiny metal a black/grey discoloration and dull appearance [6,7,8,9] which, by many curators and patrons, may be considered aesthetically displeasing. Consequently, conservators may be tasked with removing the tarnish chemically or mechanically using particles to abrade the surface, as necessary to reduce the crystalline silver sulfide [10]. At the same time, unless the underlying environmental factors contributing to tarnishing are addressed, the silver artifacts will continue to react with the sulfur, requiring continuous treatment to maintain their appearance. This tarnishing/treatment cycle will cause the progressive removal of surface atoms, resulting in the loss of surface details that characterize the cultural heritage of the object. As such, the long-term preservation of silver artifacts necessitates the maximally achievable elimination of tarnish-inducing agents from their storage and/or exhibition environments. The exact sources responsible for the accelerated development of silver tarnish, however, are not always evident. Featured in this work, is a case study of two extensively tarnished silver coins originating from the Seleucid dynasty of the Hellenistic period (∼117-118 BCE). Having been on display for nearly four decades, these coins had developed significant surface tarnish, as inferred from visual inspection. Contrary to the typical description of advanced silver tarnish in literature, their physical appearance, as shown in Figure 1, is neither entirely ‘black/grey’ nor ‘dull’. Notably, localized areas exhibiting vivid and distinct colouration alongside a ‘glossy’ almost ‘oily’ surface quality prompted an inquiry into the contaminants responsible for the clearly non-silver appearance of the coins. To identify the causes behind the coins’ pronounced tarnishing and ‘glossiness’, as well as to formulate targeted remediations for eliminating the tarnish-inducing contaminants in and around the display case, elemental characterization of the coin surfaces was conducted using non-destructive analytical techniques. Micrographs and elemental spectra were captured using a Hitachi SU-7000 Schottky Field Emission Scanning Electron Microscope (SEM) combined with an Oxford Ultim Max SDD for Energy Dispersive X-ray Spectroscopy (EDS), operating with an acceleration voltage of 20kV. Prior to SEM imaging, the coins were gently swabbed with ethanol to eliminate loose surface particulates and excess carbon contamination. As illustrated in Figures 2 and 3, EDS analysis of both tarnished coins revealed the presence of sulfur, chlorine, and carbon within the uniformly distributed surface tarnish. While the detection of sulfur was anticipated, the significant presence of chlorine was surprising. Although conservation literature acknowledges silver as prone to corrosion attacks by chlorine [3] and identifies chlorine as a common constituent of silver tarnish [7], its study in the context of silver tarnish is limited, with experimental simulations predominantly focused on mechanisms of the sulfidation process. The accumulation of sulfur on the coins was mainly attributed to airborne emissions from gastrointestinal and metabolic processes (humans) within the gallery, whereas chlorine was linked to potential off-gassing from polymer-based materials, like polyvinyl chloride (PVC) components within the display case and/or the microclimate unit feeding its air. Given the observed ‘glossy’ surface texture of the coins, it was hypothesized that an organic film composed of hydrocarbons might be overlaying the silver tarnish. However, solely relying on EDS spectra, which reported significant carbon signals, made it challenging to definitively classify it as an organic coating rather than copious amounts of carbon contamination, as expected due to limitations with sample cleaning. To provide supplementary evidence for the presence of a hydrocarbon film, an SEM technique for visualizing the response of organics to a focused electron beam was employed, with results depicted in Figure 4. This methodology, utilizing a low-energy beam at an accelerating voltage of 3kV and a magnification of up to 45,000x, enabled the observation of the surface actively excited into motion by the beam. This surface activity is attributed to radiolysis, which involves the breaking of weak covalent bonds [11]. Given that silver sulphide is an inorganic crystalline corrosion product, the observation of radiolysis on the surface of the coins, combined with the significant amounts of carbon detected by EDS, suggests the presence of an organic coating. This ‘glossy’ film is attributed to hydrocarbons (oil and grease) sourced from a kitchen environment [3] which likely shares ventilation and piping systems with the Greek gallery that supplies the air into the display case. X-ray Photoelectron Spectroscopy (XPS) analysis is underway to isolate the nature of the organic top-layer as possible triglycerides (fatty acids composing culinary oils [12]), and to generate a depth profile that can confirm the suspected multi-layer contamination on the coins’ surfaces. This profile is anticipated to consist of the outermost organic film, followed by a silver-sulfide/chloride tarnish layer, a possible copper oxide/sulfide layer (as observed in experimentally simulated silver tarnish [6]), and finally the silver-copper alloy of the original coin. Data points will be collected at various locations on the coin surfaces to assess the accuracy of the thin film interference phenomenon as an explanation for the observed differences in colouration resulting from varying tarnish layer thicknesses [5,6,7]. Additionally, this analysis may elucidate whether variations in silver tarnish chemistry and corrosion products play a role in to the observed colouration [6]. This study, implementing a non-destructive SEM-EDS characterization approach, facilitated the correlation of visual and elemental characteristics of silver tarnish to environmental contaminants in the context of a museum exhibit. It explores constituents seldom encountered in literature studies of both real and archaeological silver tarnish and experimentally simulated silver sulfidation. Notably, this work discusses the likely sources of heavy chlorine content in silver tarnish and introduces a procedure for the analytical identification of hydrocarbon accumulation on artifacts along with its attribution to unanticipated environmental contaminants [13]. Digital photographs of the two tarnished coins 5.5 (a) and 6.3 (b), with the areas of analysis boxed out in white (Optical Microscopy) and yellow (SEM-EDS). Indexing of the data is done using the provided descriptive labels referencing the features of the coin on or near the areas of analysis. On the bottom, digital photographs of tarnished coin 5.5 (c), 6.3 (d) and a reference corroded coin (e) under a raking light, highlighting the relative reflectivity or ‘glossiness’ of the surfaces. The visibly lower light diffusion indicates a possible organic film or coating on the two tarnished coins. Typical EDS elemental maps for areas imaged on the tarnished coins. These elemental maps correspond with the Back Scattered Electron (BSE) SEM micrograph, captured at 20kv, of the halo on the obverse side of coin 6.3. Ag and Cu are characterized as ‘bulk’ elements, while C, S and Cl are characterized as ‘tarnish’ elements, and O, Si and Al are characterized as ‘grime’ elements. (a) Plot of the elemental distributions on both tarnished coins, indicating relative amounts detected for each element (in Wt%) based on the location of the SEM-EDS area. Plots (b) and (c) provide elemental distributions for coins 5.5 and 6.3 respectively, with the darkest colored bars corresponding with the SEM-EDS area reporting the highest amounts of sulfur. Screenshots of recordings captured during SEM imaging showing the motion of the contaminants on the coins’ surfaces; Middle Detector (MD) Secondary Electron (SE) images captured at high magnification and low voltage. As highlighted by the blue boxes, the tarnished coins 5.5 (a) and 6.3 (b) display motion on the surface over imaging time, suggesting the presence of an organic film. The reference silver corroded coin (c), which visually exhibited no signs of tarnish, nor an organic coating, shows no such effect under the same imaging parameters. Images captured using a 3kV accelerating voltage, 7.2-9.9 mm working distances, and 40-45k magnifications.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.055
GPT teacher head0.270
Teacher spread0.215 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Published2024
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