THE PROJECT

PlasCOis a 3-year research project (2018-2021) financed by the Portuguese Foundation for Science and Technology (FCT - Fundação para Ciência e a Tecnologia).

The project explores the use of Carbon Dioxide (CO2) - in liquid or supercritical phase - for the preservation of modern and contemporary works of art. The final aim is to design environmentally friendly cleaning and conservation protocols based on CO2 technology for plastic materials, namely Polyurethanes (PUR), foam/rubber-based materials, poly(methyl methacrylate) (PMMA) and others.
Selected plastic-based works of art that have posed several conservation challenges in the past are used as case study candidates and inform the production of mock-up samples (i.e. replicas) to be used for testing the CO2 technology. 

Extensive trials are performed on the mock-ups using a variety of parameters (CO2 phase and density) and conditions (pressure, temperature, use of co-solvent, exposure time). 
The impact and suitability of each trial on the selected materials will be assessed using different analytical techniques, to guarantee a full characterisation of the samples from the macro to the nanoscale and to outline efficient and safe cleaning/conservation protocol(s).

A Machine Learning model will be used in conjunction with the experimental work to correlate the physical and chemical properties of the selected materials, the conditions of the CO2 treatments, and the observed outcomes. Using this approach will enable to highlight the most promising and suitable CO2 conditions, which can be then further fine-tuned to meet conservation standards.
Based on the Machine Learning model, a user-friendly prototype of a computational toll will also be designed, to assist conservators with the selection of the optimal CO2 treatment conditions for each specific case study.

THE PROJECT

PlasCOis a 3-year research project (2018-2021) financed by the Portuguese Foundation for Science and Technology (FCT - Fundação para Ciência e a Tecnologia).

The project explores the use of Carbon Dioxide (CO2) - in liquid or supercritical phase - for the preservation of modern and contemporary works of art. The final aim is to design environmentally friendly cleaning and conservation protocols based on CO2 technology for plastic materials, namely Polyurethanes (PUR), foam/rubber-based materials, poly(methyl methacrylate) (PMMA) and others.
Selected plastic-based works of art that have posed several conservation challenges in the past are used as case study candidates and inform the production of mock-up samples (i.e. replicas) to be used for testing the CO2 technology. 

Extensive trials are performed on the mock-ups using a variety of parameters (CO2 phase and density) and conditions (pressure, temperature, use of co-solvent, exposure time). 
The impact and suitability of each trial on the selected materials will be assessed using different analytical techniques, to guarantee a full characterisation of the samples from the macro to the nanoscale and to outline efficient and safe cleaning/conservation protocol(s).

A Machine Learning model will be used in conjunction with the experimental work to correlate the physical and chemical properties of the selected materials, the conditions of the CO2 treatments, and the observed outcomes. Using this approach will enable to highlight the most promising and suitable CO2 conditions, which can be then further fine-tuned to meet conservation standards.
Based on the Machine Learning model, a user-friendly prototype of a computational toll will also be designed, to assist conservators with the selection of the optimal CO2 treatment conditions for each specific case study.