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Magnetism in strongly correlated honeycomb systems with $d^5$ electronic configuration has garnered significant attention due to its potential to realize the Kitaev spin liquid state, characterized by exotic properties. However, real…
A density functional theory of two-dimensional freezing is presented for a soft interaction potential that scales as inverse cube of particle distance. This repulsive potential between parallel, induced dipoles is realized for paramagnetic…
Silicon (Si) is one of the most extensively studied materials owing to its significance to semiconductor science and technology. While efforts to find a new three-dimensional (3D) Si crystal with unusual properties have made some progress,…
We present in full detail a newly developed formalism enabling density functional perturbation theory (DFPT) calculations from a DFT+$U$ ground state. The implementation includes ultrasoft pseudopotentials and is valid for both insulating…
High-throughput density functional theory (DFT) calculations allow for a systematic search for conventional superconductors. With the recent interest in two-dimensional (2D) superconductors, we used a high-throughput workflow to screen over…
Two-dimensional transition metal dichalcogenides (TMDs) exhibit remarkable thermal anisotropy due to their strong intralayer covalent bonding and weak interlayer van der Waals (vdW) interactions. However, accurately modeling their thermal…
Using density functional theory (DFT) we report results for the electronic structure and vibrational dynamics of hydrogenated {\beta} reconstructed Silicon Carbide (001) (3x2) surfaces with various levels of hydrogenation. These results…
Two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) are good candidates for high-performance flexible electronics. However, most demonstrations of such flexible field-effect transistors (FETs) to date have been on…
Transition metal dichalcogenides (TMD) are currently among the most interesting two-dimensional (2D) materials due to their outstanding properties. MoTe2 involves attractive polymorphic TMD crystals which can exist in three different 2D…
Machine learning interatomic potentials (MLIPs) achieve excellent accuracy when trained on large Density Functional Theory (DFT) data. To be useful in practice, they must often be adapted to target chemistries using small and expensive…
Density-functional-theory (DFT) calculations have been performed on the Li-Si and Li-Ge systems. Lithiated Si and Ge, including their metastable phases, play an important technological r\^ole as Li-ion battery (LIB) anodes. The calculations…
Materials engineering using atomistic modeling is an essential tool for the development of qubits and quantum sensors. Traditional density-functional theory (DFT) does however not adequately capture the complete physics involved, including…
We present a physically motivated strategy for the construction of training sets for transferable machine learning interatomic potentials. It is based on a systematic exploration of all possible space groups in random crystal structures,…
Most functional materials possess one single outstanding property and are limited to be used for a particular purpose. Instead of integrating materials with different functions into one module, designing materials with controllable…
We have parameterized a reactive force field (ReaxFF) for lithium aluminum silicates using density functional theory (DFT) calculations of structural properties of a number of bulk phase oxides, silicates, and aluminates, as well as of…
In spite of remarkable developments in the field of advanced materials, silicon remains one of the foremost semiconductors of the day. Of enduring relevance to science and technology is silicon's nanomechanical behaviour including phase…
The experimental data on elastic and inelastic scattering of 270 MeV 3He particles to several low lying states in 90Zr, 116Sn and 208Pb are analyzed within the double folding model (DFM). Fermi density distribution (FDD) of target nuclei is…
Density functional theory (DFT) underpins modern atomistic simulations of transition-metal surfaces. It can predict key properties linked to catalytic performance, such as adsorption energies and barrier heights, enabling new paradigms in…
Higher superconducting critical temperature and large-area epsilon-near-zero interfaces are two long-standing goals of Condensed Matter Physics and Optics. Motivated by the recent advancements of experimental interests on metallic…
Silicon carbide (SiC) is an essential material for next generation semiconductors and components for nuclear plants. It's applications are strongly dependent on its thermal conductivity, which is highly sensitive to microstructures.…