87 citations · 219 across the 6 of their papers we have counts for
6 papers
Quantifying the performance of machine learning models in materials discovery
Christopher K. H. Borg, Eric S. Muckley, Clara Nyby +4
The predictive capabilities of machine learning (ML) models used in materials discovery are typically measured using simple statistics such as the root-mean-square error (RMSE) or…
Mapping Thermoelectric Transport in a Multicomponent Alloy Space
Ramya Gurunathan, Suchismita Sarker, Christopher K. H. Borg +4
Interest in high entropy alloy thermoelectric materials is predicated on achieving ultralow lattice thermal conductivity through large compositional disorder. However, h…
Quantifying uncertainty in high-throughput density functional theory: a comparison of AFLOW, Materials Project, and OQMD
Vinay I. Hegde, Christopher K. H. Borg, Zachary del Rosario +7
A central challenge in high throughput density functional theory (HT-DFT) calculations is selecting a combination of input parameters and post-processing techniques that can be use…
Strong anisotropy in nearly ideal-tetrahedral superconducting FeS single crystals
Christopher K. H. Borg, Xiuquan Zhou, Christopher Eckberg +4
We report the novel preparation of single crystals of tetragonal iron sulfide, FeS, which exhibits a nearly ideal tetrahedral geometry with S--Fe--S bond angles of 110.2(2) $^\circ…
The preparation and phase diagrams of (LiFeOD)FeSe and (LiFeOH)FeSe superconductors
Xiuquan Zhou, Christopher K. H. Borg, Jeffrey W. Lynn +3
We report the phase diagram for the superconducting system (LiFeOD)FeSe and contrast it with that of (LiFeOH)FeSe both in single crystal…
Neutron investigation of the magnetic scattering in an iron-based ferromagnetic superconductor
Jeffrey W. Lynn, Xiuquan Zhou, Christopher K. H. Borg +3
Neutron diffraction and small angle scattering experiments have been carried out on the double-isotopic polycrystalline sample (7Li0.82Fe0.18OD)FeSe. Profile refinements of the dif…