Guided data-driven manufacturing approach for safe and sustainable by design of multi-functional natural-based conductive polymers

Scope

The activity focuses on the optimisation of the manufacturing (3D printing) of composite and multifunctional biopolymers. To achieve this, the integration of machine learning/deep learning approaches with materials science and 3D printing will enable the prototype of multifunctional naturally derived devices with engineered properties (i.e., elastic moduli, conductivity, hydration).

Expected Outcomes

Standardised sustainable by design (SSbD) Manufacturing Methods for flexible electronics.
Prototypes of eco-friendly conductive inks, e.g., biodegradable conductive polymers, eco-friendly solvents.
Prototypes of soft components, e.g., polymer-based artificial muscles, flexible robotic links.

Publications and Patents

PhD Thesis: "Guided data-driven manufacturing approach for safe and sustainable by design of multi-functional natural-based conductive polymers". PhD candidate: Praveen Muralidharan. Scientific responsibles: Annalisa Tirella, Gastone Rosati Papini, Devid Maniglio

Personnel

Reference person: Annalisa Tirella

DII members: Gastone Rosati Papini, Devid Maniglio, Praveen Muralidharan (PhD)

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