ERI: Modeling Development of Calcium Superionic Conductors

Metal-ion batteries are widely used in electric vehicles, portable electronics, and energy storage for the power grid. Lithium-ion batteries have enabled many of these advances, but they are reaching limits in energy density and cost. Calcium-ion solid-state batteries are a promising alternative because calcium is abundant, low-cost, and capable of storing large amounts of energy. However, progress has been limited by the lack of solid electrolytes that can efficiently transport calcium ions at room temperature and remain stable when in contact with battery electrodes. This project aims to speed up the discovery of high-performance calcium solid electrolytes and to improve understanding of how calcium ions move through these materials. It will use data-driven approaches and advanced computer simulations. Large materials databases will be screened to find promising candidates. First-principles simulations will be used to study ion transport at the atomic scale. The project will also support education and outreach by involving students in research and promoting STEM learning in local schools. These efforts will help prepare a skilled workforce. Overall, this project will help develop safer, lower-cost, and high-performance energy storage systems, thereby strengthening energy security in the United States. This project will focus on identifying, characterizing, and optimizing inorganic calcium-ion conductors that can approach superionic conductivity at room temperature. A key challenge is that most known materials either exhibit low Ca-ion mobility or undergo interfacial reactions that form interphases that block ion transport. Addressing this challenge will require both the discovery of new materials and a deeper understanding of the mechanisms governing ion diffusion and interfacial stability. To achieve these goals, the project will integrate data-driven materials discovery with high-throughput computational approaches. First, large-scale materials databases will be screened using data mining and bond-valence models to identify candidate calcium-ion conductors with favorable structural and chemical features. Second, calculations based on density functional theory will be employed to evaluate migration pathways, activation energies, defect formation, and electrochemical stability windows. Molecular dynamics simulations will further capture ion transport behavior at finite temperatures and provide insight into diffusion mechanisms and possible ion-correlation effects. Building on these insights, the project will explore strategies to enhance ionic conductivity through in silico doping and defect engineering. This includes introducing aliovalent dopants, tuning vacancy and interstitial defect populations, and optimizing lattice frameworks to reduce migration barriers. In parallel, the electrochemical and interfacial stability of candidate materials will be systematically assessed against calcium metal anode and relevant cathode materials to ensure compatibility. The outcomes of this project will include identifying new calcium superionic conductors, developing a fundamental understanding of Ca-ion transport mechanisms, and establishing design principles that provide actionable guidance for experimental synthesis and validation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2551941 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Hong Fang | Institution: Rutgers University Camden, CAMDEN, NJ | Award Amount: $199,876 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2551941 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2551941.html