Atomic Scale Modeling of Alloys and Functional Materials
||Atomic Scale Modeling of Alloys and Functional Materials|
||SNIC Medium Compute|
||Paul Erhart <firstname.lastname@example.org>|
||Chalmers tekniska högskola|
||2019-11-01 – 2020-11-01|
Understanding and manipulating the electrical and thermal conductivity of materials is of interest to a large number of applications, including electronic and optoelectronic devices, thermal management, and thermoelectric energy generation. In collaboration with several experimental groups, we study the electrical and thermal conductivity of various materials and their dependence on microstructure, focusing on inorganic clathrates and chalcogenides.
To this end, we use both first-principles calculations and semi-empirical models in combination with solvers for the Boltzmann transport equation as well as molecular dynamics simulations. The computational expense of individual calculations, the large number of degrees of freedom to be treated, and the chemical complexity of the systems of interest imply that we require very substantial computational resources in order to complete our research plan.
The codes to be used are all well suited for massively parallel computing environments. Density functional theory (DFT) calculations are conducted using the VASP and GPAW codes. Boltzmann transport calculations are carried out using phono3py, shengBTE, and boltzTrap using input generated with the hiphive package that we released recently (https://hiphive.materialsmodeling.org; doi: 10.1002/adts.201800184). Molecular dynamics simulations are conducted using LAMMPS. We will also employ our in-house model construction codes atomicrex (https://www.atomicrex.org) and icet, the latter of which has been recently released as FOSS for public use (https://icet.materialsmodeling.org; doi: 10.1002/adts.201900015).
This research is supported by a Fellowship grant from the Wallenberg foundation.
Recent publications (https://materialsmodeling.org/publications/):
* Lindroth et al., Phys. Rev. B 100, 19078 (2019)
* Ångqvist et al., Adv. Sim. Theo. 2, 1900015 (2019)
* Eriksson et al., Adv. Sim. Theo. 2, 1800184 (2019)
Metallic nanoparticles are key components in many areas including e.g., catalysis, medicine, energy generation and storage. The properties of these particles are highly sensitive to variations in size, shape, composition and surface termination. Recently, owing to fascinating advances in shape-selected nanocrystal synthesis, particles with well-controlled size, shape and chemical composition have become available. This has brought about new exciting opportunities for engineering particle properties.
Here, our research is concerned with the development of models and tools for simulating alloys on the atomic scale. This approach enables an improved understanding of the microscopic processes that govern materials response on the macroscopic scale. The specific objectives are
* to quantitatively resolve the phase diagrams of nanoparticles composed of late transition-metals as a function of size, shape, and surface chemistry, and
* to predict plasmonic properties as a function of size, shape, composition, and chemical state under experimentally relevant conditions.
In this subproject we employ DFT calculations via the GPAW and VASP codes along with empirical potentials in molecular dynamics and Monte Carlo simulations. Post-processing and model building as described above are carried out as well.
* Rossi et al., Nature Comm. 10, 3336 (2019)
* Kumar et al., ACS Nano 13, 3188 (2019)
* Rahm and Erhart, J. Phys. Chem. C 122, 28439 (2018)
This project is supported by the Swedish Research Council.