posted on 2018-10-30, 00:00authored byRachel Woods-Robinson, Danny Broberg, Alireza Faghaninia, Anubhav Jain, Shyam S. Dwaraknath, Kristin A. Persson
The
growth of materials databases has yielded significant quantities
of data to mine for new energy materials using high-throughput screening
methodologies. One application of interest to energy and optoelectronics
is the prediction of new high performing p-type transparent conductors
(TCs). However, screening methods for such materials have never been
validated over the breadth of computed materials properties. In this
study, we compile an experimental data set of 74 bulk crystal structures
corresponding to known state-of-the-art n-type and p-type TCs and
compute a series of corresponding computational descriptor properties.
Our goals are to (1) compare computational descriptors to experimentally
demonstrated properties of real materials in the data set, (2) determine
the ability of ground state, density functional theory (DFT)-based
computational screening methodologies to identify these experimentally
realized TCs, and (3) use this understanding to estimate reasonable
screening cutoffs for four commonly used descriptors. First, stability
calculations demonstrate that most materials in the data set have
an energy above the convex hull (Ehull) of <100 meV/atom, and we also propose a Pourbaix analysis technique
to estimate moisture stability. Second, we find a lenient cutoff for
the DFT PBE band gap of 0.5 eV is sufficient to include a majority
of the wide gap candidates and exclude narrow gap compounds. Next,
the effective mass, m*, is found to correlate weakly
to conductivity in the p-type materials as compared with n-type materials,
which may motivate an increase in the m* cutoff as
well. Lastly, we perform an uncertainty analysis and literature comparison
for the branch point energy (BPE), a qualitative descriptor for dopability.
We find the BPEs of most n-type materials to lie near the conduction
band and those of most p-type materials to lie at midgap; this is
a significant distinction, suggesting BPE to be a more definitive
descriptor for n-type TC materials. By assessing the validity of this
simple screening methodology via comparing experimental data to computational
descriptors, we aim to motivate and strengthen future materials discovery
efforts in the field of transparent conductors and beyond.