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Our research interests are in the field of first-principles computational modeling of high-performance materials. We use and develop theoretical methods for quantum mechanical calculations based on the density functional theory (DFT) and beyond, as well as modern statistical simulation methods, such as Monte Carlo, molecular dynamics, and path integral molecular dynamics. One of the main themes of our research is to incorporate recent developments in applied mathematics and machine learning to create rigorous, efficient and highly automated high-throughput methods and to apply them to design and discover materials with exceptional technological properties.
Topics of interest in our group include, but are not limited to:
- High-performance materials for energy storage and generation (supercapacitors, batteries, thermoelectrics, solar cells, solar thermochemical conversion, etc.)
- Thermodynamic, structural and dynamical properties of solids at high temperatures
- Spin liquid materials for topological quantum computing
- Electron and phonon transport in bulk materials and nanostructures
- Thermoelectric phenomena, Seebeck and Peltier effects
- Compressive sensing and machine learning for building efficient computational models of materials
- Mathematical approaches for solving partial differentia equations of quantum mechanics and materials science that exploit inherent sparsity
Hyung-Seok Kim, John B. Cook, Hao Lin, Jesse S. Ko, Sarah H. Tolbert, Vidvuds Ozolins, and Bruce Dunn, “Oxygen vacancies enhance pseudocapacitive charge storage properties of MoO3−x” Nature Materials (2016). URL: http://dx.doi.org/10.1038/nmat4810
Jiangang He, Maximilian Amsler, Yi Xia, S. Shahab Naghavi, Vinay I. Hegde, Shiqiang Hao, Stefan Goedecker, Vidvuds Ozolins, and Chris Wolverton, “Ultralow Thermal Conductivity in Full Heusler Semiconductors,” Physical Review Letters 117, 046602 (2016). URL: http://dx.doi.org/10.1103/PhysRevLett.117.046602.
X. Lu, D. T. Morelli, Y. Xia, and V. Ozoliņš, “Increasing the Thermoelectric Figure of Merit of Tetrahedrites by Co-Doping with Nickel and Zinc,” Chemistry of Materials 27, 408–413 (2015). URL: http://dx.doi.org/10.1021/cm502570b.
Fei Zhou, Weston Nielson, Yi Xia, and Vidvuds Ozoliņš, “Lattice Anharmonicity and Thermal Conductivity from Compressive Sensing of First-Principles Calculations,” Physical Review Letters 113, 185501 (2014). URL: http://dx.doi.org/10.1103/PhysRevLett.113.185501.
V. Ozolins, R. Lai, R. E. Caflisch, and S. Osher, “Compressed modes for variational problems in mathematics and physics,” Proceedings of the National Academy of Sciences of the United States of America (PNAS) 110 (46), 18368-18373 (2013). URL: http://dx.doi.org/10.1073/pnas.1318679110.
X. Lu, D. T. Morelli, Y. Xia, F. Zhou, V. Ozolins, H. Chi, and C. Uher, “High Performance Thermoelectricity in Earth-Abundant Compounds Based on Natural Mineral Tetrahedrites,” Advanced Energy Materials 3, 342-348 (2013). URL: http://dx.doi.org/10.1002/aenm.201200650.
M. D. Nielsen, V. Ozolins, and J. P. Heremans, “Lone Pair Electrons Minimize Lattice Thermal Conductivity,” Energy & Environmental Science 6, 570-578 (2013). URL: http://dx.doi.org/10.1039/c2ee23391f.
L. J. Nelson, G. L. W. Hart, F. Zhou, and V. Ozolins, “Compressive sensing as a paradigm for building physics models,” Physical Review B 87, 035125 (2013). URL: http://link.aps.org/doi/10.1103/PhysRevB.87.035125.
- D. Morelli, X. Lu, and V. Ozolins. "Thermoelectric materials based on tetrahedrite structure for thermoelectric devices."
- B. Sadigh, T. Lenosky, T. D. de la Rubia, M.-J. Caturia, S. Theiss, A. Quong, M. Foad, M. Giles, V. Ozolins, and M. Asta , “A Method for Enhancing the Solubility of Boron and Indium in Silicon.”