QML
Financiado
Quantum Machine Learning Chemical Reactions with Unprecedented Speed and Accura...
Large and diverse property data sets of relaxed molecules and crystals, resulting from computationally demanding quantum calculations, have recently been used to train machine learning models of various energetic and electronic pr...
Large and diverse property data sets of relaxed molecules and crystals, resulting from computationally demanding quantum calculations, have recently been used to train machine learning models of various energetic and electronic properties. We propose to advance these techniques to a level where they can also describe reaction profiles, i.e. reactive non-equilibrium processes which traditionally would require quantum chemistry treatment. The resulting quantum machine learning (QML) models will provide reaction profiles for new reactants in real-time and with quantum accuracy. The overall goal is to develop a predictive computational tool which allows chemists to easily optimize reaction conditions, develop new catalysts, or even plan new synthetic pathways.
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Duración del proyecto: 76 meses
Fecha Inicio: 2018-01-24
Fecha Fin: 2024-05-31
Fecha Fin: 2024-05-31
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2024-05-31
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2017-COG:
ERC Consolidator Grant
Cerrada
hace 7 años
Presupuesto
El presupuesto total del proyecto asciende a
2M€
Líder del proyecto
TECHNISCHE UNIVERSITAT BERLIN
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5
1.21M€ |
Participante
950.10K€ |
Participante
364.79K€ |
Participante