activity
19972023
most citedConsistent set of band parameters for the group-III nitrides AlN, GaN, and InN

404 citations · 3.9k across the 44 of their papers we have counts for

collaborators
Showing 2018 · cond-mat.mtrl-sciShow all

9 papers · 2 filters

cond-mat.mtrl-sci2018

NOMAD 2018 Kaggle Competition: Solving Materials Science Challenges Through Crowd Sourcing

Christopher Sutton, Luca M. Ghiringhelli, Takenori Yamamoto +7

Machine learning (ML) is increasingly used in the field of materials science, where statistical estimates of computed properties are employed to rapidly examine the chemical space…

cond-mat.mtrl-sci2018

Two-to-three dimensional transition in neutral gold clusters: the crucial role of van der Waals interactions and temperature

Bryan R. Goldsmith, Jacob Florian, Jin-Xun Liu +6

We predict the structures of neutral gas-phase gold clusters (, = 513) at finite temperatures based on free-energy calculations obtained by replica-exchange ab initio…

cond-mat.mtrl-sci2018

Modulation of the Work Function by the Atomic Structure of Strong Organic Electron Acceptors on H-Si(111)

Haiyuan Wang, Sergey V. Levchenko, Thorsten Schultz +3

Advances in hybrid organic/inorganic architectures for optoelectronics can be achieved by understanding how the atomic and electronic degrees of freedom cooperate or compete to yie…

cond-mat.mtrl-sci2018

Test set for materials science and engineering with user-friendly graphic tools for error analysis: Systematic benchmark of the numerical and intrinsic errors in state-of-the-art electronic-structure approximations

Igor Ying Zhang, Andrew J. Logsdail, Xinguo Ren +3

Understanding the applicability and limitations of electronic-structure methods needs careful and efficient comparison with accurate reference data. Knowledge of the quality and er…

cond-mat.mtrl-sci2018

Artificial Intelligence for High-Throughput Discovery of Topological Insulators: the Example of Alloyed Tetradymites

Guohua Cao, Runhai Ouyang, Luca M. Ghiringhelli +4

Significant advances have been made in predicting new topological materials using high-throughput empirical descriptors or symmetry-based indicators. To date, these approaches have…

cond-mat.mtrl-sci2018

AFLOW-CHULL: Cloud-oriented platform for autonomous phase stability analysis

Corey Oses, Eric Gossett, David Hicks +10

prediction of phase stability of materials is a challenging practice, requiring knowledge of all energetically-competing structures at formation conditions. Lar…