Developing Thermal Hybrid Exchange-Correlation Functionals for Accurate Prediction of Transport and Optical Properties of Warm Dense Plasmas

The Nobel Prize-winning method of density-functional theory (DFT) has been widely used for important applications to better understand the physics and chemistry of nature, as well as to improve our daily life. Examples of DFT applications range from inventing materials of specific functions, to understanding chemical reactions for better products, to designing drugs to cure cancers. The success of DFT relies on the accuracy of the approximation of how particles in a material interact with each other, the so-called exchange-correlation (XC) free-energy density functional. So far, most of the available XC-functionals have been limited to zero-temperature cases. In this research project, finite-temperature XC-functionals will be developed to significantly improve the predictive capability of DFT for plasma-physics and materials studies. The outcome of this research project is expected to make a significant difference in a variety of scientific fields and applications such as planetary science, astrophysics, fusion-energy and national defense applications, as well as to make a positive impact on the society through delivering tools for discovering better materials and designing efficient drugs.Matter at warm dense conditions exists vastly in the universe -- from shocks and inertial confinement fusion implosions created in laboratories to planetary cores and astrophysical objects such as brown and white dwarfs. Thorough understanding of the properties of warm-dense matter, non-ideal and "exotic" plasmas hold the key to unravel many mysteries in planetary and astrophysical sciences; for example, the possible H-He demixing on Saturn. Reliably predicting the transport and optical properties of matter at such extreme conditions heavily depends on the accuracy of XC functionals required by the DFT method. In this project, a three-step research program will be established to develop accurate finite-temperature hybrid XC-functionals by: (i) Assessing the available thermal free-energy functional performance to identify the state conditions wherein those current functionals fail; (ii) Developing thermal-hybrid and thermal-screened hybrid XC functionals that correspond to those proven to be accurate for the energy gap in the zero-temperature case; and (iii) Applying the developed thermal hybrid XC-functionals to warm-dense-plasma simulations to benchmark with experiments and deliver a useful software to the broad computational science community. In particular, the PIs will release the resulting software package as open source and incorporate it into the standard distribution for the existing Quantum-Espresso and ABINIT computational packages. This will allow a wider growth of the project. This aspect is of special interest to the software cluster in the Office of Advanced Cyberinfrastructure, which has provided co-funding for this award.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

The Nobel Prize-winning method of density-functional theory (DFT) has been widely used for important applications to better understand the physics and chemistry of nature, as well as to improve our daily life. Examples of DFT applications range from inventing materials of specific functions, to understanding chemical reactions for better products, to designing drugs to cure cancers. The success of DFT relies on the accuracy of the approximation of how particles in a material interact with each other, the so-called exchange-correlation (XC) free-energy density functional. So far, most of the available XC-functionals have been limited to zero-temperature cases. In this research project, finite-temperature XC-functionals will be developed to significantly improve the predictive capability of DFT for plasma-physics and materials studies. The outcome of this research project is expected to make a significant difference in a variety of scientific fields and applications such as planetary science, astrophysics, fusion-energy and national defense applications, as well as to make a positive impact on the society through delivering tools for discovering better materials and designing efficient drugs.Matter at warm dense conditions exists vastly in the universe -- from shocks and inertial confinement fusion implosions created in laboratories to planetary cores and astrophysical objects such as brown and white dwarfs. Thorough understanding of the properties of warm-dense matter, non-ideal and "exotic" plasmas hold the key to unravel many mysteries in planetary and astrophysical sciences; for example, the possible H-He demixing on Saturn. Reliably predicting the transport and optical properties of matter at such extreme conditions heavily depends on the accuracy of XC functionals required by the DFT method. In this project, a three-step research program will be established to develop accurate finite-temperature hybrid XC-functionals by: (i) Assessing the available thermal free-energy functional performance to identify the state conditions wherein those current functionals fail; (ii) Developing thermal-hybrid and thermal-screened hybrid XC functionals that correspond to those proven to be accurate for the energy gap in the zero-temperature case; and (iii) Applying the developed thermal hybrid XC-functionals to warm-dense-plasma simulations to benchmark with experiments and deliver a useful software to the broad computational science community. In particular, the PIs will release the resulting software package as open source and incorporate it into the standard distribution for the existing Quantum-Espresso and ABINIT computational packages. This will allow a wider growth of the project. This aspect is of special interest to the software cluster in the Office of Advanced Cyberinfrastructure, which has provided co-funding for this award.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.