Data-driven exploration of NaXTe2 (X = Al, Ga, and In): from high-throughput screening to tailored optoelectronic functionalities

Abstract

The rational design of semiconductor materials with tunable properties for targeted optoelectronic applications remains a significant challenge, particularly in moving beyond traditional paradigms limited by d-electron localization and instability. To address this, we introduce and execute a closed-loop, data-driven research strategy. This paradigm begins with the construction of a proprietary library of 723 Na/K-based ABC₂ compounds, which is then subjected to high-throughput screening and subsequent machine learning predictions to efficiently identify the ternary telluride NaXTe₂ (X = Al, Ga, and In) family as a promising candidate embodying the “alkali metal genetic engineering” concept. Employing first-principles calculations within this workflow, we systematically decode the structure–property relationships in NaXTe₂. Our results reveal that simple cation substitution (Al → Ga → In) serves as a powerful single variable for synergistic, cross-dimensional performance tuning. This is achieved by modulating the interplay of lattice strain and bonding character, which continuously shifts the electronic bandgap from a direct 1.28 eV (NaAlTe₂) to a direct 0.21 eV (NaGaTe₂), while concurrently evolving the mechanical properties from conventional toughness to the high toughness and pronounced anisotropy characteristic of NaInTe₂. Comprehensive calculations confirm the thermal stability and favorable mechanical properties of all three compounds, underpinning their experimental viability. The distinct properties map to specific applications: NaAlTe₂ for photovoltaics; NaGaTe₂ for infrared detection; and NaInTe₂ for flexible and polarization-sensitive optoelectronics. Beyond introducing NaXTe₂ as a tunable platform, this work validates a computational paradigm that integrates data-driven discovery with a mechanistic understanding, offering a blueprint for accelerated design of next-generation functional semiconductors.