An SWIR-MIR Spectral Database of Organic Coatings Used on Historic Metals

Surface organic coatings (SOCs) composed of drying oils, resins, and bitumen were commonly applied to small Renaissance bronze sculptures to enhance their visual and physical properties, producing dark, lustrous surfaces that were both esthetic and protective. Yet, the identification of these coatings remains challenging due to aging, conservation interventions, and the damage caused by physical sampling. This study presents a reproducible, non-destructive protocol for characterizing SOCs on metal substrates using external reflection Fourier transform infrared spectroscopy (ER-FTIR) and fiber optic reflectance spectroscopy (FORS). Twenty-seven reference coating mock-ups of linseed oil, walnut oil, mastic resin, pine resin, and bitumen were stoved onto bronze coupons and artificially aged. Spectra were analyzed across the visible/near-infrared (VIS-NIR) (~400–1000 nm), short-wave-infrared (SWIR) (~1000–2500 nm), and mid-infrared (MIR) (~2.5–25 µm) ranges, with key diagnostic features identified for each component and blend, including primary absorptions, combination bands, and overtones. ER-FTIR proved highly effective in detecting oil–resin mixtures and later wax coatings through characteristic bands in the MIR, while FORS, enhanced by first-derivative processing, successfully differentiated triterpenoid and diterpenoid resins and identified multi-component SOCs in the SWIR region. The reference spectral database generated in this study is intended to serve as a comparative tool for future non-invasive analysis of organic coatings on metal surfaces and to demonstrate that ER-FTIR and FORS, used in tandem, offer a practical and scalable framework for the non-destructive identification of SOCs.

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Publication Details

Journal
Coatings
Published
2025-10-20
DOI
https://doi.org/10.3390/coatings15101226
Primary Topic
Cultural Heritage Materials Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

An SWIR-MIR Spectral Database of Organic Coatings Used on Historic Metals

Aaron Shugar, Elizabeth Provost
Coatings
Cultural Heritage Materials Analysis
article

An SWIR-MIR Spectral Database of Organic Coatings Used on Historic Metals

Aaron Shugar, Elizabeth Provost
article en

Abstract

Surface organic coatings (SOCs) composed of drying oils, resins, and bitumen were commonly applied to small Renaissance bronze sculptures to enhance their visual and physical properties, producing dark, lustrous surfaces that were both esthetic and protective. Yet, the identification of these coatings remains challenging due to aging, conservation interventions, and the damage caused by physical sampling. This study presents a reproducible, non-destructive protocol for characterizing SOCs on metal substrates using external reflection Fourier transform infrared spectroscopy (ER-FTIR) and fiber optic reflectance spectroscopy (FORS). Twenty-seven reference coating mock-ups of linseed oil, walnut oil, mastic resin, pine resin, and bitumen were stoved onto bronze coupons and artificially aged. Spectra were analyzed across the visible/near-infrared (VIS-NIR) (~400–1000 nm), short-wave-infrared (SWIR) (~1000–2500 nm), and mid-infrared (MIR) (~2.5–25 µm) ranges, with key diagnostic features identified for each component and blend, including primary absorptions, combination bands, and overtones. ER-FTIR proved highly effective in detecting oil–resin mixtures and later wax coatings through characteristic bands in the MIR, while FORS, enhanced by first-derivative processing, successfully differentiated triterpenoid and diterpenoid resins and identified multi-component SOCs in the SWIR region. The reference spectral database generated in this study is intended to serve as a comparative tool for future non-invasive analysis of organic coatings on metal surfaces and to demonstrate that ER-FTIR and FORS, used in tandem, offer a practical and scalable framework for the non-destructive identification of SOCs.

CoatingsVol. 15(10)
Queen's University (CA)
Bader Philanthropies, Government of Ontario, Queen's University
Openalex Percentile: Top 69%
Cultural Heritage Materials Analysis
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