Chalcogenides,
which refer to chalcogen anions, have attracted
considerable attention in multiple fields of applications, such as
optoelectronics, thermoelectrics, transparent contacts, and thin-film
transistors. In comparison to oxide counterparts, chalcogenides have
demonstrated higher mobility and p-type dopability,
owing to larger orbital overlaps between metal–X covalent chemical
bondings and higher-energy valence bands derived by p-orbitals. Despite
the potential of chalcogenides, the number of successfully synthesized
compounds remains relatively low compared to that of oxides, suggesting
the presence of numerous unexplored chalcogenides with fascinating
physical characteristics. In this study, we implemented a systematic
high-throughput screening process combined with first-principles calculations
on ternary chalcogenides using 34 crystal structure prototypes. We
generated a computational material database containing over 400,000
compounds by exploiting the ion-substitution approach at different
atomic sites with elements in the periodic table. The thermodynamic
stabilities of the candidates were validated using the chalcogenides
included in the Open Quantum Materials Database. Moreover, we trained
a model based on crystal graph convolutional neural networks to predict
the thermodynamic stability of novel materials. Furthermore, we theoretically
evaluated the electronic structures of the stable candidates using
accurate hybrid functionals. A series of in-depth characteristics,
including the carrier effective masses, electronic configuration,
and photovoltaic conversion efficiency, was also investigated. Our
work provides useful guidance for further experimental research in
the synthesis and characterization of such chalcogenides as promising
candidates, as well as charting the stability and optoelectronic performance
of ternary chalcogenides.