most citedSpatial segregation of substitutional B atoms in graphene patterned by the moiré superlattice on Ir(111)

18 citations · 26 across the 5 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2023

Unconventional band structure via combined molecular orbital and lattice symmetries in a surface-confined metallated graphdiyne sheet

Ignacio Piquero-Zulaica, Wenqi Hu, Ari Paavo Seitsonen +13

Graphyne (GY) and graphdiyne (GDY)-based materials represent an intriguing class of two-dimensional (2D) carbon-rich networks with tunable structures and properties surpassing thos…

cond-mat.mtrl-sci2023

On-Surface Carbon Nitride Growth from Polymerization of 2,5,8-Triazido-s-heptazine

Matthias Krinninger, Nicolas Bock, Sebastian Kaiser +8

Carbon nitrides have recently come into focus for photo- and thermal catalysis, both as support materials for metal nanoparticles as well as photocatalysts themselves. While many a…

cond-mat.mtrl-sci202218 cited

Spatial segregation of substitutional B atoms in graphene patterned by the moiré superlattice on Ir(111)

Marc G. Cuxart, Daniele Perilli, Sena Tömekce +6

Fabrication of ordered structures at the nanoscale limit poses a cornerstone challenge for modern technologies. In this work we show how naturally occurring moiré patterns in Ir(11…

cs.HC20222 cited

Explainable AI for tailored electricity consumption feedback -- an experimental evaluation of visualizations

Jacqueline Wastensteiner, Tobias M. Weiss, Felix Haag +1

Machine learning (ML) methods can effectively analyse data, recognize patterns in them, and make high-quality predictions. Good predictions usually come along with "black-box" mode…

cs.LG20226 cited

Augmented cross-selling through explainable AI -- a case from energy retailing

Felix Haag, Konstantin Hopf, Pedro Menelau Vasconcelos +1

The advance of Machine Learning (ML) has led to a strong interest in this technology to support decision making. While complex ML models provide predictions that are often more acc…