Obtaining of at least one model that allows the prediction of a more sustainable material/process than the selected benchmark while having comparable performances.

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Establishment of a comprehensive and general modelling framework to describe photopolymerisation processes, enabling their control and increasing their efficiency and sustainability, by reducing chemical and energy consumption, and minimising trial-and-error failure and material waste.

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Coupling of ‘minimal’ models focusing on physical observables for spatio-temporal conversion with mechanical property gradients that generate stress differentials to actuate 2D and 3D patterns into spontaneously forming structures, thereby reducing printing steps (material/energy) and augmenting function.

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Parameterisation, testing and validation of the models with a series of experiments on custom-formulated radical polymerisation systems (academic secondment), predicting a plethora of well-organised patterns with prescribed profile and curvature, for applications in optics and photonics, structural colour, and autonomous (self-sustaining) curing systems.

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Obtaining a modelling and manufacturing framework that permits the design and fabrication of more sustainable materials/processes than the existing selected benchmark while having comparable performance.

Comprehensive analytical and numerical modelling toolkit to predictively describe photopolymerisation process for both conventional and advanced material patterning.

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Collection of experimental data on a representative chemical library for validation of the models.

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Setting of appropriate sustainability metrics, and sustainability assessment of the materials/processes predicted by the new models, including chemicals, energy and time expended, as well as solvents used and waste generated.

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Rained researcher expert in modelling, including numerical simulation, with experimental skills in photopolymerisation, acquired also during secondments.