1 citations · 2 across the 3 of their papers we have counts for
3 papers
cond-mat.mtrl-sci2026
Data-Efficient Machine learning for Predicting Dopant Formation Energies in TiO Monolayer
Kati Asikainen, Matti Alatalo, Marko Huttula +1
Machine learning models are increasingly applied in materials science, yet their predictive power is often constrained by data scarcity. Here, we show that accurate predictions can…
cond-mat.mtrl-sci2026★ 1 cited
Investigating the Electronic and Magnetic Properties of NaFeMnO Cathode Materials with X-ray Compton Scattering
Veenavee Nipunika Kothalawala, Kosuke Suzuki, Johannes Nokelainen +21
We discuss electronic and magnetic properties of NaFeMnO, a promising Na-ion battery cathode material. Using x-ray Compton scattering, SQUID magnetometry, a…
cond-mat.mtrl-sci2021★ 1 cited
Quasiparticle electronic structure and optical response (+BSE) of anatase TiO starting from modified HSE06 functionals
Sruthil Lal S. B, D Murali, Matthias Posselt +2
The quasiparticle electronic structure and optical excitation of anatase TiO is determined within the framework of many-body perturbation theory (MBPT) by combining the $G_0W_0…