SCOML
Financiado
Machine learning methods for excited-state dynamics simulations in light-induced...
Machine learning methods for excited-state dynamics simulations in light-induced spin-crossover complexes
Spin crossover complexes are bistable transition-metal compounds in which light, or other external simuli, is used to induce a change in the magnetic state of the system, allowing them to be employed as molecular switches in futur...
Spin crossover complexes are bistable transition-metal compounds in which light, or other external simuli, is used to induce a change in the magnetic state of the system, allowing them to be employed as molecular switches in future spintronics and photonics technologies. Despite the rapid development of experimental techniques to characterise these complexes, computational material science is not yet able to provide a quantitative description of the light-induced spin crossover mechanism. These limitations are mainly due to the need for enormous computational resources to perform accurate excited-state dynamics simulations in medium-sized transition-metal complexes. The aim of the SCOML project is to provide the proof of concept for a new machine learning-based strategy that will enable efficient and accurate simulations of the light-induced spin-crossover mechanism, thus paving the way for a systematic design of new materials. Achieving this goal has the potential to revolutionise the production of new technological solutions to guide Europe towards a digital and green transition.
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Duración del proyecto: 28 meses
Fecha Inicio: 2023-05-02
Fecha Fin: 2025-09-30
Fecha Fin: 2025-09-30
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-05-02
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
HORIZON-MSCA-2022-PF-01-01:
MSCA Postdoctoral Fellowships 2022
Cerrada
hace 2 años
Presupuesto
El presupuesto total del proyecto asciende a
200K€
Líder del proyecto
THE PROVOST FELLOWS FOUNDATION SCHOLARS THE...
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Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5
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