Interdisciplinary Research to Advance Digital Imagery and Natural Compounds for Eco-Cleaning and for Preserving Textile Cultural Heritage

Sensors (Basel). 2022 Jun 12;22(12):4442. doi: 10.3390/s22124442.

Abstract

The old fibers that make up heritage textiles displayed in museums are degraded by the aging process, environmental conditions (microclimates, particulate matter, pollutants, sunlight) and the action of microorganisms. In order to counteract these processes and keep the textile exhibits in good condition for as long as possible, both reactive and preventive interventions on them are necessary. Based on these ideas, the present study aims to test a natural and non-invasive method of cleaning historic textiles, which includes the use of a natural substance with a known antifungal effect (being traditionally used in various rural communities)-lye. The design of the study was aimed at examining a traditional women's shirt that is aged between 80-100 years, using artificial intelligence techniques for Scanning Electron Microscopy (SEM) imagery analysis and X-ray powder diffraction technique in order to achieve a complex and accurate investigation and monitoring of the object's realities. The determinations were performed both before and after washing the material with lye. SEM microscopy investigations of the ecologically washed textile specimens showed that the number of microorganism colonies, as well as the amount of dust, decreased. It was also observed that the surface cellulose fibers lost their integrity, eventually being loosened on cellulose fibers of cotton threads. This could better visualize the presence of microfibrils that connect the cellulose fibers in cotton textiles. The results obtained could be of real value both for the restorers, the textile collections of the different museums, and for the researchers in the field of cultural heritage. By applying such a methodology, cotton tests can be effectively cleaned without compromising the integrity of the material.

Keywords: SEM; X-ray powder diffraction technique; artificial intelligence techniques; digital imagery; heritage textiles.

MeSH terms

  • Aged, 80 and over
  • Artificial Intelligence
  • Cellulose
  • Female
  • Humans
  • Interdisciplinary Research*
  • Lye*
  • Textiles

Substances

  • Lye
  • Cellulose

Grants and funding

The research was funded by the University of Oradea, within the Grants Competition “Scientific Research of Excellence Related to Priority Areas with Capitalization through Technology Transfer: INO–TRANSFER–UO”, Projects No. 329/2021; No. 317/2021. The research undertaken was made possible by the equal scientific involvement of all the authors concerned.