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Improved methods for modeling functional transition metal compounds in complex environments: Ground states, excited states, and spectroscopies

Hrant P. Hratchian (Principal Investigator), Christine M. Isborn, Aurora Pribram-Jones, Liang Shi, and David A. Strubbe (Co-Principal Investigators)

University of California, Merced

Rapid advances in energy applications require new theory and computational models to provide guidance for interpretation of experimental results and mechanistic understanding. New theory development is necessary to treat systems of increasing complexity, size, and relevance to real applications. Functional transition metal compounds, including molecules, clusters, nanoparticles, surfaces, and solids, provide particular promise for magnetic, optical, and catalytic applications. However, such systems can be exceptionally challenging to model. To make progress in understanding and designing transition metal compounds for energy applications, theory must be able to simulate such systems in complex environments, as well as simulate the spectra of such complex systems to provide direct connections with experiment.

This project establishes the Center for Chemical Computation and Theory (ccCAT) at UC Merced. Leveraging the independent expertise of ccCAT members, the work will make significant inroads to the theoretical and computational challenges associated with studying transition metal compounds, their reaction chemistry, photophysics and photochemistry, and response to spectroscopic interrogation. The ccCAT team members will address three objectives: (1) to develop new electronic ground and excited state methods that will more accurately treat open-shell transition metal compounds; (2) to build models for treating complex environments within ground and excited state calculations; and (3) to implement new theory and methods for simulating modern ultrafast spectroscopies, including 2D-electronic spectroscopy.

The project is focused on developments in chemical computation and theory. Building on the team’s long track record developing widely used computer programs, new code built as part of this project will be freely available to the research community. Care will be taken to develop intelligent and scalable software capable of handling systems and environments with a broad array of methods and levels of theory. Improved computational efficiency and parallelization will enable calculations at greater length and time scales. Indeed, ccCAT will produce new knowledge and computer programs that will benefit many other groups contributing to the DOE Basic Energy Sciences portfolio.