Product Oriented Development of Xanthan Konjac Agar Solvent Gels for Art Conservation

Researcher(s)

  • Gavin Brownstein, Chemical Engineering, University of Delaware

Faculty Mentor(s)

  • Norman Wagner, Chemical and Biomolecular Engineering, University of Delaware
  • Benjamin Thompson, Chemical and Biomolecular Engineering, University of Delaware

Abstract

Gel systems offer a novel method for controlled delivery of cleaning solutions to moisture sensitive surfaces such as paintings, ceramics, and metals. Traditional gels used in art conservation–typically agar or gellan–can release excess water and leave residues detectable under UV light. Previous research has demonstrated that strong elastic gels composed of xanthan gum, konjac glucomannan, and agar (XKA) can deliver cleaning agents effectively without leaving apparent residues. This study investigates the relationship between the mechanical properties of XKA gels and their cleaning performance, while also developing scalable, reproducible methods for gel formulation and storage to support product design. The research investigates XKA polymer gels stored under vacuum-packed, frozen, and dried conditions and compares their rheological properties when tested in the as-prepared, thawed, and rehydrated states respectively. It further quantifies how different drying conditions affect the rehydration behavior of the films. Mechanical properties such as yield stress and elastic modulus are assessed via oscillatory rheology. Gels were dried at various temperatures using a moisture analyzer and then rehydrated in deionized water. Over seven weeks of storage, vacuum-sealed, frozen, and dried XKA gels showed no mold growth. However, frozen gels exhibited reduced yield stress upon thawing. Rehydrated XKA films continued to swell until partial dissolution, while gels containing calcium acetate reached a stable equilibrium swelling ratio of approximately twice their original mass. Although gel thickness changes during rehydration complicate the use of simple 1D Fickian diffusion models, empirical models accurately predict water absorption over time.