Collaborative Research: Elements: Towards Accurate Magnetic Simulations: A Comprehensive Framework for Strongly Correlated Systems

About This Grant

This project develops an open-source computational platform to study the magnetic and electronic properties of strongly correlated materials (SCMs), which are essential for emerging technologies and devices related to quantum computing, spintronics, and magnetic storage. SCMs exhibit complex behaviors that are difficult to capture through conventional static theories or based on pure experimental measurements. By incorporating dynamical fluctuation effects into conventional first-principles methods, this project offers a new way to accurately simulate magnetic phenomena at multiple scales, from atomic spins to macroscopic magnetism. The developed software automates the modeling workflow and enables users to compute critical properties such as magnetic ground states, exchange interactions, spin excitations, and temperature-dependent magnetic transitions. By integrating this tool with community-developed packages and offering training through virtual workshops and Research Experiences for Undergraduates (REU) programs, the project fosters inclusive education and expands access to cutting-edge materials in science research. This work promotes the progress of science by enabling high-precision simulations, supporting national efforts in technology innovation, and training a broad range of students in computational materials research. The project develops a unified, extensible software framework that integrates Density Functional Theory (DFT), DFT+U, and Dynamical Mean Field Theory (DMFT) calculations to compute magnetic properties of SCMs with high fidelity, under the basis of two different electronic structure implementations, VASP and SIESTA. It builds on the existing DMFTwDFT codebase, expanding it to support collinear and noncollinear magnetic configurations and to interface with spin analysis tools including TB2J, PyProcar, Multibinit, and Vampire. Key technical advances include a spin-dependent Green’s function implementation, magnetic susceptibility calculations using the Bethe-Salpeter equation, and perturbative method implementation to extract spin-exchange interactions from the localized spin Hamiltonian. This framework is embedded in AiiDA for high-throughput studies and allows for direct comparison of DFT+U and DMFT-derived magnetic parameters. Additional modules capture ligand corrections, multispin interactions, and spin anisotropy contributions. Results are validated against experimental data such as neutron scattering and ARPES, ensuring robust predictions across diverse material classes. The platform supports automated U and J calculations and aims for integration with public repositories such as Materials Cloud. The project also includes extensive outreach, user documentation, and education efforts to ensure sustainable and impactful adoption by the research community. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Material Research within the Directorate of Mathematical and Physical Science. 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.