Publikasjoner og ansvarsområder
Functional Properties of CrFeCoNiCu and GeFeCoNiCu oxides
Atomistic simulations and machine learning methods for development of thermoelectric materials
Screening thermoelectric materials with ab initio atomistic modelling and machine learning techniques
Effectiveness of Neural Networks for Research on Novel Thermoelectric Materials. A Proof of Concept.
This paper describes the application of neural network approaches to the discovery of new materials exhibiting thermoelectric properties. Thermoelectricity is the ability of a material to convert energy from heat to electricity. At present, only few materials are known to have this property to a...
Electron-phonon coupling in semiconductors within the GW approximation
Effects of electron-phonon coupling on absorption spectrum: K edge of hexagonal boron nitride
Thermoelectric effect in superlattices; applicability of coherent and incoherent transport models
Band gap mapping of alloyed ZnO using probe-corrected and monochromated STEM-EELS
The band gap of semiconducting ZnO can be readily tuned through alloying it with other relevant oxides, such as CdO, consequently extending the performance of the corresponding materials and devices. In this context, one of the challenges is to establish the methodology for two-dimensional band gap...