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With a global production of almost 380 million tonnes per year, polymeric materials play a central role in modern society. They are used in the manufacture of countless everyday products, or as more sophisticated compounds in medicine, diagnostics and fine chemistry.

However, new economic and societal constraints require more rational design and alternative methods of polymer synthesis, formulation and processing to meet the needs of greater sustainability and more virtuous end-of-life management, while maintaining optimal performance in application.

The polymer materials of the future will be one of the pillars of the circular economy. The recent development of high throughput methods (HTP) and artificial intelligence (AI) opens up huge opportunities to address these challenges. While such methods are emerging in chemistry, they have not yet been implemented in France in the field of Polymer Science.

Thus, the AMETHIST demonstrator project proposes, as a proof of concept, to marry all these fields by using the combined HTP and AI methodsto address three distinct case studies in the polymer field. The issues addressed have been chosen for their relevance in addressing urgent scientific and societal challenges: better performing, sustainable materials from non-critical and non-toxic raw materials.
- Case Study 1 - Design of polymeric materials with programmable degradability ;
- Case Study 2a and 2b - Organic-inorganic polymer-based materials, nanocomposites, and hybrid composites;
- Case Study 3 - Bio-based polymeric materials.

In each case study, for each type of material, the HTP synthesis and characterisation method will be implemented at the molecular, macromolecular and material scale. The data from the HTP analysis will be used to feed machine learning approaches to determine the best combination with the multiple targeted properties. Optimised materials designed by AI will be manufactured and evaluated.

The BIA Unit, with its expertise in biopolymers and in particular polysaccharides, will cover the research on biobased polymeric materials (case study 3).

• Acronym: AMETHIST
• Project name: AI and high throughput methods guiding the design of polymeric materials (conception de matériaux polymères accélérée par des outils d’intelligence artificielle et des méthodes de préparation et caractérisation haut-débit)
• Begin-End:  2022-2026
• Funding:  PIA 4- PEPR DIADEM
• Total budget/ BIA budget: 1.2 Meuros/400 keuros
• Partners: : IMP INSA Lyon, LCPO Univ Bordeaux, BIA INRAE Nantes
• Coordination : Jean-François Gérard, IMP INSA Lyon
• BIA's teams involved : NANO, BIBS, PVPP