Title

Optimized Micro-Sampling and Computational Analysis for SERS Identification of Red Organic Dyes on Prints

Published In

Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy

Document Type

Citation

Publication Date

1-5-2022

Abstract

The goals of this study were to develop a robust methodology and data analysis procedure to identify red dyes in artwork where dye collection is inaccessible by traditional methods. With Surface-Enhanced Raman Spectroscopy (SERS) it is possible to obtain identifying molecular information from dilute and degraded dyes. A minimally invasive, soft-mechanical sampling method to gently contact printed paper is described; using a customized polymeric hydrogel surface with an exposure area of about 1 mm, micrometer-diameter colorant particles were collected. To validate that the sample collection methodology is minimally invasive, test papers were photographed before and after sampling under UV and white light; and DART-MS analysis of the sampled area was conducted. A reference library of SERS spectra from binder (hide glue), dyes (safflower, sappan, and madder), and binder-dye mixtures was built and used by a spectral-matching genetic algorithm (GA). Fifty individual GA runs returned results that precisely matched at least one dye component in 48-50 of the 50 runs, and matched both dyes in a mixture between 29 and 50 of the 50 runs. Finally, in an artwork application, the methodologies were demonstrated on micro-samples from three areas of an 18th century Japanese woodblock print by Suzuki Harunobu in the collection of the Portland Art Museum, on which, madder dyes were positively identified. Conclusions and extensions from this work are expected to contribute to the body of knowledge about 18th c. Japanese woodblock prints.

Rights

Copyright © 2022 Elsevier B.V. All rights reserved.

Description

The National Science Foundation is acknowledged for support of the BioAnalytical Mass Spectrometry Facility at PSU (MRI 1828573), where DART data was collected.

DOI

10.1016/j.saa.2022.120857

Persistent Identifier

https://archives.pdx.edu/ds/psu/37019

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