Elsevier

Journal of Cultural Heritage

Volume 45, September–October 2020, Pages 10-24
Journal of Cultural Heritage

Original article
Response surfaces model for restoring and cleaning oil painted artworks

https://doi.org/10.1016/j.culher.2020.03.011Get rights and content

Highlights

  • Cleaning oil-based paintings is a complex, delicate matter.

  • A statistical model is proposed to study response surfaces using MODDE GO®.

  • Cleaning formulas are tested that contain water, limonene, Findet® 1214/N23, phenethyl alcohol and Glucopon® 600.

  • Different factors are analyzed: chemical composition, expert opinion, lightness and gloss.

  • Diverse cleaning conditions can be simulated and the main factors that influence the process calculated.

Abstract

In order to clean varnishes used as final protective layers in paintings and polychromed sculptures,organic solvents often associated with high toxicity, have traditionally been used that pose a risk to the original materials. Therefore, it is necessary to develop cleaning methods that use substances that are as innocuous as possible for the artwork and the restorers themselves. Water-based cleaning systems have been put forward in recent years, usually accompanied by surfactants, which under certain circumstances can provide significant benefits. We are presenting this work along these lines, proposing a model for studying response surfaces that analyses the performance in cleaning and removing varnish from artworks using various cleaning formulas comprised mainly of water and a low-toxicity monoterpene: limonene. Their level of effectiveness has been evaluated using the software for statistical design and optimization of experiments, MODDE GO®. The study shows the model's statistical validity and its ability to simulate a multitude of cleaning scenarios in silico and to determine the main factors that affect the cleaning, evaluated via the responses according to: chemical composition, expert opinion using visible light, expert opinion using ultraviolet light, variation in color and percentage variation of lightness and gloss.

Introduction

In the field of restoration, cleaning can be defined as any activity aimed at removing external surface layers (surface dirt or aged varnishes) that are not part of the artwork's original composition and which make it difficult to see the original surface, or which affect its integrity.

Although procedures for cleaning works of art have been used since antiquity, it was only in the second half of the 20th century when scientific study began to use organic solvents provided by industry with different properties and variable levels of toxicity, most notably in the classic studies by Hildebrand & Scott, Teas, Feller and Hansen [1], [2], [3], [4], [5].

The work by Masschelein-Kleiner [6] stands out in the sphere of restoration. It related the effectiveness of the treatment to the type of dirt, the characteristics of the picture's surface and the type and condition of the varnishes protecting it. Since the end of the 1980s, different water-based cleaning systems with low toxicity have been developed in order to improve on the results from traditional organic solvents and to reduce the risks for the restorers. Different researchers have put forward formulations that combine solvents, surfactants, chelating agents, enzymes, buffer solutions and gellants, seeking to be selective in the removal of undesired matter with as little damage as possible to the original artwork [7], [8], [9], [10], [11], [12], [13], [14], [15], [16].

It is in this context that we are proposing formulations to clean polychrome artworks using mixtures of water and limonene, stabilized with non-ionic surfactants. Limonene (1-Methyl-4-(1-methylethenyl)-cyclohexene) is a colorless liquid hydrocarbon classified as a cyclic monoterpene. It is chiefly produced from a natural source: citrus oil, as a by-product of orange juice manufacture. Limonene is a chiral molecule, and biological sources produce one enantiomer: d-limonene, which is the R-enantiomer (CAS number 5989-27-5). The enantiomer d-Limonene is a chemical with low toxicity based upon lethal dose (LD50 Oral=5.600 mg/kg in male mice and 4.400 mg/kg in male rats) [17]. There is no evidence for carcinogenicity or genotoxicity in humans and it is not deemed necessary to use breathing protection when handling it, although limonene and its oxidation products are respiratory and skin irritants if exposed to the pure compound for a long time or if it is ingested [17], [18]. Applied in common polychrome restoration techniques, it may be considered a low-toxic, much safer product to use than most other classic solvents normally employed in this field. However, in the field of restoration of cultural assets, it is not a product that is often used. Indeed, this study is the first to evaluate the use of limonene compositions to clean and remove natural varnish in professional restoration techniques forpolychrome painted artworks.

Section snippets

Research aim

The purpose of this study is to test the aforementioned cleaning formulations using a statistical design for experiments via the MODDE GO® program in order to obtain a response surfaces model. The pigments, types of varnish and extent of aging are varied in order to optimize the complex process of cleaning oil paintings. We seek to evaluate the statistical validity of the model and determine the main factors that influence the process for cleaning works of art painted with oil. This model is

Response surfaces model

The response surface methodology is traditionally used to model complex systems with numerous factors and responses in engineering and development of cleaning product formulations, and even in social sciences to evaluate scientific activity, considered as a complex system [19], [20], [21]. The proposed model considers the cleaning of polychrome painted artworks to be a procedure affected by a set of values or variables that is evaluated via a set of responses. The factors can be quantitative or

Validity of the model

In order to confirm the validity of the model, the predicted values for the model were compared with the values observed experimentally for each response. The absolute and relative errors were also calculated, correlating the latter with the experiments’ order of implementation (run) so as to discard any bias related to the way and order in which they were implemented. Equally, they were correlated with the value of each response, either in their observed values or in their predicted values, so

Conclusions

A response surfaces model has been proposed for cleaning oil paintings with aqueous-based and limonene cleaning formulas using the MODDE GO®program, and its statistical validity has been demonstrated.

The main factors that influence cleaning with the proposed formulations were the concentrations of water and limonene as the main solvents and which regulate the cleaners’ level of hydrophilia and lipophilicity, followed by the type of varnish, aging and types of pigments. The other components in

Acknowledgements

This study was supported by the National Spanish Project “I+D” reference: HAR2016-79886-P.

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      The cleaning process of historical artworks for conservation and restoration purposes includes the removal of dirt, grime, stains, and soil as well as the removal of degraded layers such as aged, yellowed varnishes, and coatings [1,2]. Even though it has been performed since antiquity, modern, systematic and scientific approaches began to appear towards the end of the 20th century [2,3]. The traditional method is to clean the surface of paintings by using pure solvents or solvent mixtures and applying them directly on the coating layers or paintings with the aid of cotton swabs or brushes [4].

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