CAREER: Local Correlation Approaches for High-Level Density Functional Theory Simulations of Large Systems

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Chen Huang of Florida State University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop new theoretical and computational methods for investigating the electronic properties of large, complex molecules and materials. The ability to model large systems at the electronic level is essential for the industrial and technological design of molecules and materials for clean energy, efficient batteries, and novel data storage devices. However, it is challenging to investigate large systems with the most accurate electronic structure methods, since computational cost grows exponentially with system size. Dr. Huang and his group are developing new quantum mechanical embedding methods for determining the electronic properties of large systems in a divide-and-conquer manner. The methods are focused on accurately describing the microscopic interactions among electrons---their quantum correlations---at scale. Finding new ways to address this "electron correlation problem" is regarded as one of the grand challenges of 21st century science. Dr. Huang's new algorithms and methods will be implemented in state-of-the-art, open source quantum chemistry codes and made available to the broader research community. Integrated with his research, Dr. Huang is training a diverse group of undergraduate and graduate students from engineering, chemistry, physics, and materials science to effectively utilize electronic structure methods, through a new problems-based density functional theory (DFT) course. The course lectures and YouTube tutorials are aimed at lowering the barrier for students to integrate DFT simulations within their research. Working with outreach programs at FSU, Dr. Huang is involving middle school and high school students in his research to increase their interest in pursuing STEM careers.The goal of this project is to develop new quantum mechanical embedding methods to obtain accurate reaction energies and electronic structures that scale to large chemical systems. The basic idea of embedding methods is to utilize a high-level electronic structure method within a region of interest, and to treat the rest of the system ("the environment") with a low-level, computationally-efficient method. Dr. Huang and his group are extending embedding methods in three new directions: (i) generalizing density-matrix embedding to metallic systems using a pseudopotential-like approach; (ii) extending the XCPP (exchange-correlation potential patching) methodology to construct RPA (random phase approximation) correlation energies and potentials in large systems in an atom-by-atom manner; and (iii) accelerating the convergence of RPA energy differences calculated with a stochastic sampling scheme by imposing appropriate moment constraints. The new techniques are being applied to challenging problems of significant fundamental and technological interest, including investigating the role of metallic copper in methanol synthesis; charge transfer and magnetic coupling at YBa2Cu3O7/La2/3Ca1/3MnO3 (superconducting/ferromagnetic) interface; and transport, storage, and release of oxygen in ceria for heterogeneous catalysis. The methodologies are being implemented as open source code in the ABINIT, Psi4, and CP2K quantum chemistry packages. The educational plan is focused on developing a problems-based DFT course including YouTube tutorials, to enable students to develop expertise in this widely-used tool of contemporary molecular and materials modeling.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.