Project description
Accurately modelling photoexcitation and the excited-state dynamics of materials' interfaces
Irradiation with light can induce a range of changes in materials. For instance, light absorption can initiate photochemical reactions on surfaces. Advanced computer simulations provide detailed insights into these processes, which can guide the development of new photonic devices with versatile functions. The ERC-funded PhotoMat project aims to develop highly accurate methods for the prediction of excited-state nuclear forces and the properties and dynamics at materials’ interfaces, enabling calculations of system sizes up to 1 000 atoms. The methods will be based on ab initio Green's function theory.
Objective
The PhotoMat project will develop highly accurate methods for the prediction of excited-state properties and dynamics of materials interfaces based on ab initio Green's function theory in the GW approximation. Insight into the intricate processes unfolding after photoexcitation is crucial to realizing the vision of ‘materials by design’. A detailed understanding of experiment requires aid from theory. However, currently there is no computational method available, which can provide reliable excited-state nuclear forces for materials. I propose here to advance the GW-Bethe-Salpeter equation formalism (BSE@GW), which is computationally very expensive. While GW is considered the gold standard for the computation of band structures, the BSE@GW scheme is the method of choice for describing the formation of excitons (bound electron-hole pairs) in materials. I recently contributed to pushing GW to system sizes of up to 1000 atoms, often required to model materials interfaces. I will leverage these advancements to overcome the restriction of BSE@GW to small systems, enabling calculations of similar size. This will be achieved by reducing the scaling of the BSE step with respect to system size combined with an efficient implementation of periodic boundary conditions and optimization of the algorithm for execution on the emerging generation of exascale supercomputers. Excited-state geometry optimization will be enabled by implementing accurate analytic nuclear BSE forces. Non-adiabatic molecular dynamics will be unlocked by combining the low-scaling BSE energies and forces with surface hopping schemes and machine learning potentials. I will employ the newly developed methods to investigate promising candidates for tailored photonic devices. This will include the study of photoisomerization reactions at 2D materials and the formation of charge-transfer excitons in moiré structures. PhotoMat is here the crucial link that bridges the divide between theory and experiment.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologynanotechnologynano-materialstwo-dimensional nanostructures
- natural sciencescomputer and information sciencescomputational science
- natural sciencesmathematicspure mathematicsgeometry
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwaresupercomputers
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
01069 Dresden
Germany