Closing the loop in stereoselective catalysis with data driven approaches
Data-driven methods promise to enable a highly structured approach for the development of asymmetric catalytic reactions, founded both on experimental and computational data. In this new but underdeveloped method, a small number o...
Data-driven methods promise to enable a highly structured approach for the development of asymmetric catalytic reactions, founded both on experimental and computational data. In this new but underdeveloped method, a small number of experiments is performed and that data is used to make a mathematical model to predict how new ligands will behave. Such a model is based on calculated or measured physical descriptors of the ligand, and correlations obtained between enantioselectivity and such descriptors also provide mechanistic insight. In an iterative (looped) approach, the model’s predictions are tested experimentally, and fed back to make an improved model, which is again tested experimentally, until satisfactory stereoselectivity and yield is obtained. Importantly, the integration and feedback of computational and experimental data during the research process is a significantly more efficient approach to developing asymmetric catalytic reactions and also provides mechanistic insight as the reaction is developed.
The main research aim of this doctoral network is to develop powerful and readily applicable workflows for data-driven development of stereoselective catalysis.
Using this data-driven approach requires a fundamentally different experimental workflow to developing catalytic reactions than is currently employed in most research laboratories. Since this requires a fundamental change in the way most experimental groups work, the data-driven approach is not widespread and remains underdeveloped. The next generation of chemists requires training in combined and integrated computational and experimental approaches, both in academia and industry.
The main training aim of this doctoral network is to train researchers in comprehensive data-driven experimental approach for realizing challenging asymmetric catalytic methods.ver más
28/02/2029
Líder desconocido
3M€
Duración del proyecto: 55 meses
Fecha Inicio: 2024-07-05
Fecha Fin: 2029-02-28
Línea de financiación:
concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto
el día 2024-07-05
Presupuesto
El presupuesto total del proyecto asciende a
3M€
Seleccionando "Aceptar todas las cookies" acepta el uso de cookies para ayudarnos a brindarle una mejor experiencia de usuario y para analizar el uso del sitio web. Al hacer clic en "Ajustar tus preferencias" puede elegir qué cookies permitir. Solo las cookies esenciales son necesarias para el correcto funcionamiento de nuestro sitio web y no se pueden rechazar.
Cookie settings
Nuestro sitio web almacena cuatro tipos de cookies. En cualquier momento puede elegir qué cookies acepta y cuáles rechaza. Puede obtener más información sobre qué son las cookies y qué tipos de cookies almacenamos en nuestra Política de cookies.
Son necesarias por razones técnicas. Sin ellas, este sitio web podría no funcionar correctamente.
Son necesarias para una funcionalidad específica en el sitio web. Sin ellos, algunas características pueden estar deshabilitadas.
Nos permite analizar el uso del sitio web y mejorar la experiencia del visitante.
Nos permite personalizar su experiencia y enviarle contenido y ofertas relevantes, en este sitio web y en otros sitios web.