Rapid screening strategy for aluminum-ion battery cathode materials using data-driven filtering and Ab initio calculations

Abstract

The development of high-performance and cost-effective cathode materials is critical for advancing aluminum-ion battery (AIB) technology as a sustainable alternative to lithium-ion batteries. In this study, we employed a rapid screening strategy that integrates data-driven filtering with ab initio density functional theory (DFT) calculations to accelerate the discovery of promising AIB cathodes. Utilizing an extensive dataset of over 154,500 inorganic compounds from the Materials Project (MP) database, candidate materials were systematically evaluated based on criteria including thermodynamic stability, theoretical specific capacity, electrical conductivity, environmental compatibility, and economic feasibility. This approach led to the identification of six promising cathode materials: AlCuS₂, AlCuSe₂, AlFe₂O₄, AlFeO₃, AlVO₃, and AlMnO₃. Among these, AlFeO₃ and AlMnO₃ emerged as the most promising candidates, exhibiting outstanding electrochemical performance with high specific capacities (614.59 mAh/g and 618.88 mAh/g, respectively), significant operating voltages (3.61 V and 3.41 V), and superior energy densities (2218.67 Wh/kg and 2110.38 Wh/kg). These materials also demonstrated minimal volume changes during charge-discharge cycles, ensuring structural stability for long-term battery operation. Additionally, AlCuS₂ and AlCuSe₂ were identified as viable cathodes for aqueous electrolyte systems due to their lower operating voltages. The results highlight the efficacy of combining computational screening with ab initio calculations in expediting cathode material discovery. This study provides a pathway for future experimental validation and further optimization, paving the way for the development of next-generation AIBs with improved performance, sustainability, and economic viability.