CAREER: Development of Efficient Spin Projection Models for Applications to Transition Metal Catalysis

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Hrant P. Hratchian, of the University of California Merced, is supported by an award from the Chemical Theory, Models, and Computational Methods program in the Division of Chemistry to develop new theoretical models to study transition metal compounds. Transition metals include commonly known metals such as iron, gold, copper, titanium, and platinum. The transition metal compounds used in this project are useful for increasing the speed of chemical reactions (chemical catalysts). Modeling chemical catalysis and the experiments that demonstrate their properties is challenging due to the complexity of their electronic structure. Professor Hratchian's research is focused on designing and applying new predictive models, which can be translated into useful software to address this complexity. These models inform and guide the rational design of next-generation catalysts used in energy research and pharmaceutical production. Strong collaborations with experimental groups enhance the impact and scope of this project. Professor Hratchian develops new educational programs at UC Merced to improve student success. The outreach and education goals address needs at both graduate and undergraduate levels. At the graduate level, Professor Hratchian is expanding a program introducing students to leaders in quantum chemistry using an informal journal club setting. At the undergraduate level, new computational and simulation modules enhancing learning are being developed and implemented in the curriculum. Professor Hratchian also engages in outreach with local school districts and works with K-8 educators to develop new visualization tools for immersive learning with students in the Merced City School District.This project has three main scientific objectives to assess currently available approximate spin projection models, to develop and implement new models that address electronic structures posing challenges for current models and to explore metal oxide and metal sulfide chemistry using these new models. The project builds on recent work from the Professor Hratchian's research group developing a hierarchy of affordable and predictive models for studies involving metal oxides, metal sulfides, and other systems suffering from spin contamination. This work is of critical importance in the field as spin contamination limits the expected accuracy of affordable mean-field models. Professor Hratchian also engages in educational activities aimed at students at all levels. These educational activities include the development of new computational modules to enhance learning in undergraduate courses, the expansion of a graduate level training activity, and collaboration with a local K-8 school district to build visualization models as engaging vehicles for immersive learning.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.