MALTOSE
Financiado
Machine Learning for Tailoring Organic Semiconductors
Machine Learning for Tailoring Organic Semiconductors (MALTOSE) connects fundamental materials research with machine-learning (ML) techniques, focusing on the electronic properties of organic semiconductors. The aim of this innova...
Machine Learning for Tailoring Organic Semiconductors (MALTOSE) connects fundamental materials research with machine-learning (ML) techniques, focusing on the electronic properties of organic semiconductors. The aim of this innovative project is to discover and design novel materials with exciting properties, the prime example being the design of compounds for better organic photovoltaic cells, i.e., that reach higher power-conversion efficiencies and are more stable and more environmentally friendly.
The methodology relies on a deep tensor neural network, the so-called PredictNet, that is designed and trained to predict electronic properties of molecules and polymers, at a fraction of the numerical cost compared to density-functional theory (DFT) computations, not to mention experimental measurements. PredictNet will be particularly fruitful in combination with a genetic algorithm that will be developed to propose candidate compounds from crossover and mutation from previously successful compounds. MALTOSE will enable the identification and design of promising compounds, out of the immense pool of imaginable molecules and materials, for future technological applications in fields like organic photovoltaic solar cells, large-area electronic displays, flexible organic electronics, or sensors.
The project will bring together the fellow, a recognized quantum physicist and data scientist with academic and industry research experience, and a top research host institution under the supervision of a leading expert in materials science, genetic algorithms, modelling, simulation and knowledge transfer. The fellow will receive an advanced training programme in research skills and complementary non-research-oriented skills in order to enhance his future career prospects and to provide a strong basis for an independent career.
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Duración del proyecto: 51 meses
Fecha Inicio: 2020-04-29
Fecha Fin: 2024-07-30
Fecha Fin: 2024-07-30
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2024-07-30
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
MSCA-IF-2019:
Individual Fellowships
Cerrada
hace 5 años
Presupuesto
El presupuesto total del proyecto asciende a
173K€
Líder del proyecto
CENTRO INTERNACIONAL DE MATERIALES AVANZADOS...
Actividades de investigación asociacion
Perfil tecnológico
TRL
4-5
50K
Perfil tecnológico
TRL
4-5
50K