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Sweet2Gel

Financiado

Learning to Design Sweet Renewable Hydrogels - Development of Experimental Proto...

Learning to Design Sweet Renewable Hydrogels - Development of Experimental Protocols and Deep Learning Models to Decode Complex Structure-Function Relatioships Gels are 3D entangled polymer or particle networks that present, simultaneously, solid and liquid-like properties. Gels are widely present in daily life products such as contact lenses, food thickeners, platforms for drug delivery... ver más

15/06/2024

CSIC

181K€

Presupuesto del proyecto: 181K€

Líder del proyecto

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGA... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 2-3 | 552M€

Ver 2 Participantes

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-06-15

HORIZON-MSCA-2021-PF-01-01: MSCA Postdoctoral Fellowships 2021 ExpectedOutcome:

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2 Participantes

CSIC

181.15K€ | Lider

UNIVERSITY OF MANCHESTER

N.D. | Participante

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Duración del proyecto: 24 meses Fecha Inicio: 2022-05-17
Fecha Fin: 2024-06-15

Líder del proyecto

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGA... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 2-3 | 552M€

Presupuesto del proyecto 181K€

Descripción del proyecto Gels are 3D entangled polymer or particle networks that present, simultaneously, solid and liquid-like properties. Gels are widely present in daily life products such as contact lenses, food thickeners, platforms for drug delivery, or wound healing ointments, among others. Carbohydrate-based hydrogels have gathered increasing attention for a wide range of biomedical and industrial applications (e.g. tissue engineering or water decontamination) due to their biocompatible, biodegradable and non-immunogenic features. However, the development of most gel-like materials is currently limited due their high production costs and greatly pollutant manufacturing techniques. In addition, the great structural complexity of gels, where different lengths scales and isotropic and anisotropic phases coexist, limit their characterisation at the molecular and macroscopic scales, thus hindering the design and development of functional gels with tailored properties. High Resolution Magic Angle Spinning (HR-MAS) and solid-state NMR (SSNMR) spectroscopy constitute the most powerful technologies to characterise the structure and dynamics of hydrogels at the molecular level, not accessible by other techniques. The specific objectives of the Sweet2Gel project are (i) to develop novel HR-MAS and SSNMR protocols for the characterisation of carbohydrate-based gels, (ii) to develop predictive deep-learning-based models that allow to decipher hidden relationships between the molecular and macroscopic properties of the gels and (iii) to improve the molecular models of carbohydrate gel particles by a combination of molecular dynamics and deep learning approaches. Hence, the Sweet2Gel Project aims to accelerate the development of a new generation of renewable materials with rationally designed properties for a wide range of applications.

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