Join the lecture: Modelling the lifetime of PVC in collections by Tjaša Rijavec

On Thurday 23 June 2022 at 4:30pm CET, we invite you to a lecture by Tjaša Rijavec a PhD student of Chemical Sciences at the University of Ljubljana, Faculty of Chemistry and Chemical Technology.  The lecture titled ”Modelling the lifetime of PVC in collections” is part of the MCI – Topics in Museum Conservation and is organsied by the Smithsonian Museum Conservation Institute. The lecture will be delivered via ZOOM.

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Fig. 1. Tjaša Rijavec

Objects made of poly(vinyl chloride) (PVC) represent a significant part of many heritage and art collections. Unfortunately, this polymer is chemically unstable and prone to degradation by elimination of hydrogen chloride. This leads to the formation of polyene sequences and results in visible yellowing. Many PVC objects in heritage collections contain plasticizers, commonly used to improve the flexibility and processing properties of the material. Plasticizers can make up as much as 50% of the total mass of the PVC. They are prone to migration by diffusion to the surface, which is sometimes evident as ‘bleeding’, resulting in a visible surface layer that traps soiling or by evaporation from the surface causing deformation or cracks. Both PVC degradation and plasticizer migration create conservation challenges.

The research presented here is focused on modelling the lifetime of PVC from two perspectives. (i) The effect of temperature, relative humidity and plasticizer content on accelerated PVC degradation. Fitting these parameters with multiple linear regression allowed us to create a tool for predicting how storage conditions affect the time to visible yellowing. (ii) The effect of environmental parameters (temperature, humidity, air velocity) as well as intrinsic parameters (plasticizer composition, content, and polymer molecular weight) on the loss of plasticizers. The results allow us to determine how storage parameters could be optimised to reduce plasticizer loss and identify the most susceptible object types.

Application of these findings to heritage collections requires that the analytical techniques are nondestructive. Using the results of non-destructive IR spectroscopy, we have applied machine learning to create classification and regression models for the identification and quantification of plasticizers in PVC objects. In the future, we thus plan to provide guidelines for preventive conservation of PVC in heritage and art collections.

The event is organsied by the Smithsonian Museum Conservation Institute and is part of the MCI – Topics in Museum Conservation. This research was partly funded by project APACHE (This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 814496) in the frame of damage function development for PVC.

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