Related papers: The LDA+DMFT route to identify good thermoelectric…
A finite electronic band gap is a standard filter in high-throughput screening of materials using density functional theory (DFT). However, because of the systematic underestimation of band gaps in standard DFT approximations, a number of…
First principles methods can provide insight into materials that is otherwise impossible to acquire. Density Functional Theory (DFT) has been the first principles method of choice for numerous applications, but it falls short of predicting…
Understanding the properties of warm dense hydrogen is of key importance for the modeling of compact astrophysical objects and to understand and further optimize inertial confinement fusion (ICF) applications. The work horse of warm dense…
We investigate the thermoelectric response of correlated electron systems near the density driven Mott transition using the dynamical mean field theory.
Thermoelectrics involves both the generation of electrical power from heat flow, and the efficient refrigeration using electricity, which has been intensively focused on for two decades. The performance of thermoelectric power generation…
We discuss the recently proposed LDA'+DMFT approach providing consistent parameter free treatment of the so called double counting problem arising within the LDA+DMFT hybrid computational method for realistic strongly correlated materials.…
The conventional thermoelectric figure of merit and the power factor are not sufficient as a measure of thin film quality of thermoelectric materials, where the power conversion efficiency depends on the film dimensions. By considering the…
The experimental search for new thermoelectric materials remains largely confined to a limited set of successful chemical and structural families, such as chalcogenides, skutterudites, and Zintl phases. In principle, computational tools…
A new approach for calculating spectral density functions of strongly correlated electron systems is proposed within the exact diagonalization method of dynamical mean-field theory (DMFT). This approach is based on the analytic continuation…
Dynamical Mean-Field Theory (DMFT) has established itself as a reliable and well-controlled approximation to study correlation effects in bulk solids and also two-dimensional systems. In combination with standard density-functional theory…
We develop a method combining machine learning (ML) and density functional theory (DFT) to predict low-energy polymorphs by introducing physics-guided descriptors based on structural distortion modes. We systematically generate crystal…
We study the thermopower of a junction between a metal and a strongly correlated semiconductor. Both in the electronic ferroelectric regime and in the Kondo insulator regime the thermoelectric figures of merit, ZT, of these junctions are…
Combining the density functional theory (DFT) and the Gutzwiller variational approach, a LDA+Gutzwiller method is developed to treat the correlated electron systems from {\it ab-initio}. All variational parameters are self-consistently…
Predicting the compositional phase stability of strongly correlated electron materials is an outstanding challenge in condensed matter physics, requiring precise computations of total energies. In this work, we employ the density functional…
The paper deals with thermoelectric figure of merit of the superlattice materials. It is shown,that two-dimensional character of band spectrum of thermoelectric material may increase the power factor,but not the thermoelectric figure of…
Motivated by a collection of experimental results indicating the strongly correlated nature of the ferromagnetic metallic state of $CrO_{2}$, we present results based on a combination of the actual bandstructure [3] with dynamical…
Several new aspects of the subtle interplay between electronic correlations and disorder are reviewed. First, the dynamical mean-field theory (DMFT)together with the geometrically averaged ("typical") local density of states is employed to…
The properties of electrons in matter are of fundamental importance. They give rise to virtually all molecular and material properties and determine the physics at play in objects ranging from semiconductor devices to the interior of giant…
For more than three decades, nearly free electron elemental metals have been a topic of debate because the computed bandwidths are significantly wider in the local density approximation to density-functional theory (DFT) than indicated by…
Machine learning (ML) can facilitate efficient thermoelectric (TE) material discovery essential to address the environmental crisis. However, ML models often suffer from poor experimental generalizability despite high metrics. This study…