Diffusion Monte Carlo spin density difference between bulks of potassium-doped nickel oxide and pure nickel oxide, showing the effects of substituting a potassium atom (center atom) for a nickel atom on the spin density of the bulk.
Image credit: Anouar Benali, Olle Heinonen, Joseph A. Insley, and Hyeondeok Shin, Argonne National Laboratory
This project aims to predict and better understand the quantum-mechanical properties of materials that display novel properties, including novel quantum phases.
This project aims to predict and better understand the quantum-mechanical properties of materials that display novel properties, including novel quantum phases. These materials are of outstanding fundamental scientific interest and present the potential for the development of new sensors and devices.
In all of the materials studied, small changes in composition, pressure, strain, doping, and applied field yield greatly altered properties, which is a challenge to simulation and modeling. This project therefore applies approaches based on Quantum Monte Carlo (QMC), as implemented in the open-source QMCPACK code. By directly solving the Schrödinger equation and by treating the electrons at a consistent highly-accurate many-body level, these methods can be applied to general elements and materials, while employing very few approximations.
Supported by the DOE BES Computational Materials Sciences Center for the Predictive Simulation of Functional Materials and core BES programs, this project operates alongside experimental collaborators to enable joint theory-experimental work.
