CAREER: Coupling Quantum Monte Carlo with implicit solvent models for materials in energy and information technologies

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Technical SummaryThis CAREER award is funded through the Division Materials Research and the Office of Cyberinfrasructure. It supports computational and theoretical research and education to develop a computational approach for interfaces, particularly between solid and liquid. The PI will develop a technique that combines quantum Monte Carlo methods with an implicit solvent description based on the electrostatic interaction between the liquid and the solid. The accuracy of the method will be tested by comparison with experimental data and previous computational studies. To establish its range of applicability, the method will address three material problems that present difficulties for existing methods, are important for energy and information technologies and can answer fundamental questions of how solvents affect materials properties. The problems are: (1) How does the electrolyte change the rate of oxidation of organic molecules on fuel cell catalysts, (2) how do organic solvents modify the dispersion interaction of carbon nanostructures, and (3) how are optical excitations of trap states in organic electronic materials affected by the surrounding molecules.Understanding the fundamental principles of how to incorporate solvent effects into quantum Monte Carlo methods will enable the quantitative study of solvent effects on reaction rates, dispersion interactions and electronic excitations. This will ultimately enable better control of catalysis, improve the design of materials for self-assembly and enhance the performance of organic electronic materials. The PI aims to provide advanced computational concepts and an alternative approach to quantum chemistry and density functional techniques. The methods developed and the knowledge gained in this work can directly be transferred to other technologically important materials that are controlled by their interfaces, such as biomolecular systems and hydrogen storage materials. The project will build a solid knowledge base that will enable future fundamental work on these and other materials systems. The methods will be made available to the broad community by implementation into widely used codes. This research program, through integration of computation and experimental collaborations across the scientific disciplines of materials science, electrochemistry, organic chemistry and condensed-matter physics, will provide a unique educational experience for students of all levels and prepare them for careers in the growing area of computational materials science. The primary educational objectives of this program are to introduce K-12, undergraduate, and graduate students to the interdisciplinary field of computational materials science and to broaden the participation of underrepresented minorities. The PI will train undergraduate and graduate students for future jobs in materials science, both through mentoring students from freshman to graduate level in research and by integrating the research into undergraduate and graduate level courses. To attract young students, particularly underrepresented minorities, to STEM disciplines the PI will build an extended outreach program Science with random numbers for middle and high-school students and distribute it to racially diverse inner-city schools in Syracuse and New York City and add it into a workshop for Cornell University's Expanding Your Horizon program for middle school girls. For the development, evaluation and distribution of the teaching module, the PI will work with the platforms provided by the Cornell Center for Materials Research and the College of Engineering Diversity Programs Office.Non-Technical SummaryThis CAREER award is funded through the Division Materials Research and the Office of Cyberinfrasructure. It supports computational and theoretical research and education to develop techniques for computers to solve materials problems involving interfaces, specifically interfaces of solid materials with liquids. Interfaces, particularly between solids and liquids, challenge many computational approaches due to their heterogeneity, the statistical nature of the liquid, the importance of both strong and weak forces among molecules and the high atomic density on both sides. The PI aims to develop a novel computational method for solid/liquid interfaces, establish its accuracy and apply it to selective materials problems. This computational materials science program addresses essential fundamental questions on the effects of solvents on fundamental physical and chemical processes. The PI will develop a computational approach that combines random sampling methods for solving the equations of quantum mechanics with a model for the solvent based on the electrostatic interaction between the liquid and the solid. The accuracy of the method will be tested by comparison with experimental data and previous computational studies. To establish its range of applicability, the method will be used to address three material problems that present difficulties for existing methods, are important for energy and information technologies and can answer fundamental questions of how solvents affect materials properties. This research advances the use of computers and computation to predict the properties of materials to advance fundamental understanding and develop new technologies.This research program, through integration of computation and experimental collaborations across the scientific disciplines of materials science, electrochemistry, organic chemistry and condensed-matter physics, will provide a unique educational experience for students of all levels and prepare them for careers in the growing area of computational materials science. The primary educational objectives of this program are to introduce K-12, undergraduate, and graduate students to the interdisciplinary field of computational materials science and to broaden the participation of underrepresented minorities. The PI will train undergraduate and graduate students for future jobs in materials science, both through mentoring students from freshman to graduate level in research and by integrating the research into undergraduate and graduate level courses. To attract young students, particularly underrepresented minorities, to STEM disciplines the PI will build an extended outreach program Science with random numbers for middle and high-school students and distribute it to racially diverse inner-city schools in Syracuse and New York City and add it into a workshop for Cornell University's Expanding Your Horizon program for middle school girls. For the development, evaluation and distribution of the teaching module, the PI will work with the platforms provided by the Cornell Center for Materials Research and the College of Engineering Diversity Programs Office.