High-performance
p-type transparent conducting materials (TCMs)
are needed in a wide range of applications ranging from solar cells
to transparent electronics. p-type TCMs require a large band gap (for
transparency), low hole effective mass (for high mobility), and hole
dopability. It has been demonstrated that oxides have inherent limitations
in terms of hole effective masses making them difficult to use as
a high-performance p-type TCM. In this work, we use a high-throughput
computational approach to identify novel, non-oxide, p-type TCMs.
By data mining a large computational data set (more than 30,000 compounds),
we demonstrate that non-oxide materials can lead to much lower hole
effective masses but to the detriment of smaller gaps and lower transparencies.
We propose a strategy to overcome this fundamental correlation between
low effective mass and small band gap by exploiting the weak absorption
for indirect optical transitions. We apply this strategy to phosphides
and identify zinc blende boron phosphide (BP) as a very promising
candidate. Follow-up computational studies on defects formation indicate
that BP can also be doped p-type and potentially n-type as well. Our
work demonstrates how high-throughput computational design can lead
to identification of materials with exceptional properties, and we
propose a strategy to open the design of TCMs to non-oxide materials
