Davidson diagonalization in Fortran
This package contains a Modern Fortran implementation of the Davidson diagonalization algorithms to compute several eigenvalue-eigenvector pairs of a symmetric matrix
Quantum Monte Carlo meets solar energy conversion
The in silico optimization of solar energy conversion devices in which light is used to separate charge and generate power requires advanced quantum mechanical approaches to describe the photon-harvesting component and the initial charge-propagation process in the excited state.
Computing excited states, however, is highly demanding for electronic structure methods, which often struggle to ensure accuracy or treat the large, relevant system sizes. To overcome these limitations, we work in the sophisticated framework of many-body quantum Monte Carlo (QMC) methods, we have been actively developing in recent years for the accurate treatment of excited states in complex systems.
Here, we propose to professionally structure and further accelerate our methodology for energy-related applications into a set of open and re-usable software tools addressing three key elements of QMC simulations: fast computation of observables, effective non-linear optimization schemes, and efficient graphics-processing-units kernels.
With these enhanced tools, we will in parallel proceed to establish a computational protocol to optimize the primary elements of a dye-sensitized solar cell and provide robust reference data for the characterization of one of the major limitations in efficiency, namely, the charge-recombination process at the interface between dye and semiconductor.
Safer batteries with higher energy densities
Accurate and Efficient Computation of the Optical Properties of Nanostructures for Improved Photovoltaics
More efficient lighting and solar energy conversion devices
Multiscale simulations of excitation dynamics in molecular materials for sustainable energy applications
Studying uncertainties in large eddy simulations of wind farms
New tools for researchers in plasma, combustion and chemical reactor science
Solving a scalability problem through dynamic multi-level parallelization
This package contains a Modern Fortran implementation of the Davidson diagonalization algorithms to compute several eigenvalue-eigenvector pairs of a symmetric matrix
QMCBlip allows to couple Quantum Monte Carlo Simulations with Machine Learning Force Fields to accelerate Molecular Dynamics simulations
Use and design neural network ansatz wave function for real-space quantum Monte Carlo simulations of molecular systems.