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Guidelines for accurate and efficient calculations of mobilities in two-dimen...
Emerging two-dimensional (2D) materials bring unprecedented opportunities for electronic applications. The design of high-performance devices requires an accurate prediction of... -
Crystal structure validation of verinurad via proton-detected ultra-fast MAS ...
The recent development of ultra-fast MAS (>100 kHz) provides new opportunities for structural characterization in solids. Here we use NMR crystallography to validate the... -
High-throughput screening of nano-hybrid metal–organic-frameworks for photoca...
Photocatalytic conversion of CO₂ into fuel feed stocks is a promising method for sustainable fuel production. A highly attractive class of materials,... -
Quasiparticle self-consistent GW with effective vertex corrections in the pol...
Through quasiparticle self-consistent GW, we investigate the electronic structure of the antiferromagnetic ground state of four transition-metal monoxides: MnO, FeO, CoO, and... -
Guidelines for accurate and efficient calculations of mobilities in two-dimen...
Emerging two-dimensional (2D) materials bring unprecedented opportunities for electronic applications. The design of high-performance devices requires an accurate prediction of... -
High-throughput magnetic co-doping and design of exchange interactions in a t...
Using high-throughput automation of ab-initio impurity-embedding simulations we created a database of 3d and 4d transition metal defects embedded into the prototypical... -
Capturing dichotomic solvent behavior in solute–solvent reactions with neural...
Simulations of chemical reactivity in condensed phase systems represent an ongoing challenge in computational chemistry, where traditional quantum chemical approaches typically... -
Low-energy modeling of three-dimensional topological insulator nanostructures
We develop an accurate nanoelectronic modeling approach for realistic three-dimensional topological insulator nanostructures and investigate their low-energy surface-state... -
Proximity-induced Cooper pairing at low and finite energies in the gold Rashb...
Multi-band effects in superconducting heterostructures provide a rich playground for unconventional physics. We combine two complementary approaches based on density-functional... -
Water and Cu⁺ synergy in selective CO₂ hydrogenation to methanol over Cu/MgO ...
The CO₂ hydrogenation reaction to produce methanol holds great significance as it contributes to achieving a CO₂-neutral economy. Previous research identified isolated Cu⁺... -
Enhanced spin Hall ratio in two-dimensional semiconductors
The conversion efficiency from charge current to spin current via spin Hall effect is evaluated by the spin Hall ratio (SHR). Through state-of-the-art ab initio calculations... -
Understanding the role of oxygen-vacancy defects in Cu₂O(111) from first-prin...
The presence of defects, such as copper and oxygen vacancies, in cuprous oxide films determines their characteristic carrier conductivity and consequently their application as... -
Understanding the role of oxygen-vacancy defects in Cu₂O(111) from first-prin...
The presence of defects, such as copper and oxygen vacancies, in cuprous oxide films determines their characteristic carrier conductivity and consequently their application as... -
Spin-dependent interactions in orbital-density-dependent functionals: non-col...
The presence of spin-orbit coupling or non-collinear magnetic spin states can have dramatic effects on the ground-state and spectral properties of materials, in particular on... -
Enhanced spin Hall ratio in two-dimensional III-V semiconductors
Spin Hall effect (SHE) plays a critical role in spintronics since it can convert charge current to spin current. Using state-of-the-art ab initio calculations including... -
Ab-initio simulation of liquid water without artificial high temperature
Comprehending the structure and dynamics of water is crucial in various fields such as water desalination, ion separation, electrocatalysis, and biochemical processes. While... -
Prediction rigidities for data-driven chemistry
The widespread application of machine learning (ML) to the chemical sciences is making it very important to understand how the ML models learn to correlate chemical structures... -
High-throughput dataset of impurity adsorption on common catalysts in biomass...
An extensive dataset consisting of adsorption energies of pernicious impurities present in biomass upgrading processes on common catalysts and support materials has been... -
Automated computational workflows for muon spin spectroscopy
Muon spin rotation and relaxation spectroscopy is a powerful tool for studying magnetic materials, offering a local probe that complements scattering techniques and provides... -
FINALES - Electrolyte optimization for maximum conductivity and for maximum c...
This study investigates an electrolyte system composed of lithium hexafluorophosphate (LiPF6), ethylene carbonate (EC) and ethyl methyl carbonate (EMC). For the assembly of full...