Descripción del proyecto
Atravesar la barrera de la velocidad para estudiar fotoprocesos de subnanosegundos en el ADN
El objetivo del proyecto SubNano, financiado con fondos europeos, es lograr una velocidad mucho mayor en la simulación de la dinámica de las moléculas fotoexcitadas para contribuir a los estudios de eventos con una duración de subnanosegundos (sub-ns). Se empleará la metodología de sub-ns para investigar en un periodo de tiempo largo la dinámica no adiabática de procesos fotoinducidos en ácidos nucleicos, incluida la fotoestabilización del ADN mediante procesos excitónicos, marcadores fluorescentes y la formación transitoria de aniones en la reparación del ADN. Los investigadores ampliarán las simulaciones de dinámica no adiabática a nuevas escalas temporales mediante algoritmos de aprendizaje automático diabáticos y adaptativos, así como un método combinado cuántico clásico con corrección vibrónica y de punto cero. La ampliación de las investigaciones teóricas de los procesos fotodinámicos en el régimen sub-ns será por fin una realidad.
Objetivo
My goal in the SubNano project is to massively speed up the dynamics simulation of photoexcited molecules to allow addressing sub-nanosecond phenomena (that is, one thousand times above the current limits).
The sub-ns methodology will be employed to investigate the long timescale nonadiabatic dynamics of photoinduced processes in nucleic acids, including DNA photostabilization via excitonic processes, biological fluorescent markers, and transient anion formation in DNA repair.
To fulfill these goals, I will develop and implement a series of methods to extend nonadiabatic dynamics simulations into the new timescale, mainly based on a novel adaptive diabatic machine learning algorithm and a novel zero-point-corrected and vibronically-corrected mixed quantum-classical method.
The sub-ns methodology will be constrained to be general (any kind or size of molecule), black-box (minimum user intervention), modular (adaptable to any electronic structure theory), on-the-fly (no need of precomputed potential energy surfaces), and local (independent-trajectories).
It will be implemented into the Newton-X software platform, which I have been the main designer and developer. It will also be made available for all academic community through new releases of Newton-X.
For the last 25 years, theoretical investigations of photodynamical processes have been restricted to the ultrafast (picosecond) regime, selectively choosing problems in this domain. The extension into the sub-ns regime is finally feasible thanks to a large algorithmic infrastructure I have built over the last 13 years, paving the grounds to develop a new research area, atomistic nonadiabatic dynamics on the long timescale.
The success of the SubNano project will have an enormous impact on the research field, allowing to investigate outstanding interdisciplinary phenomena in chemistry, biology, and technology, which have been neglected due to a lack of methods.
Ámbito científico
- natural sciencescomputer and information sciencessoftware
- natural sciencesbiological sciencesbiochemistrybiomoleculesnucleic acids
- natural sciencesbiological sciencesgeneticsDNA
- natural scienceschemical sciencesphysical chemistryphotochemistry
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programa(s)
Régimen de financiación
ERC-ADG - Advanced GrantInstitución de acogida
13284 Marseille
Francia