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Published December 20, 2023 | Published
Book Section - Chapter

Accurate Approximations of Density Functional Theory for Large Systems with Applications to Defects in Crystalline Solids

Abstract

This chapter presents controlled approximations of Kohn–Sham density functional theory (DFT) that enable very large scale simulations. The work is motivated by the study of defects in crystalline solids, though the ideas can be used in other applications. The key idea is to formulate DFT as a minimization problem over the density operator, and to cast spatial and spectral discretization as systematically convergent approximations. This enables efficient and adaptive algorithms that solve the equations of DFT with no additional modeling, and up to desired accuracy, for very large systems, with linear and sublinear scaling. Various approaches based on such approximations are presented, and their numerical performance is demonstrated through selected examples. These examples also provide important insights into the mechanics and physics of defects in crystalline solids.

Copyright and License

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG.

Acknowledgement

We are grateful to Phani Motamarri for sharing the unpublished results shown in Table 12.1. We acknowledge the help of Arpit Bhardwaj, Sambit Das and Xin Jing in running some of the DFT-FE and SQ simulations, and generating the corresponding figures. KB, MO and MP acknowledge the support of the Army Research Laboratory under Cooperative Agreement Number W911NF-12-2-0022. VG acknowledges the support of the U.S. Department of Energy, Office of Science through grants DE-SC0008637 and DE-SC0017380. VG also gratefully acknowledges the support of the Army Research Office through the DURIP grant W911NF1810242. PS acknowledges support of the U.S. Department of Energy, Office of Science through grant DE-SC0019410. The computations presented here were conducted on the Resnick High Performance Cluster at Caltech, the Great Lakes High Performance Cluster at the University of Michigan, the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory under contract DE-AC05-00OR22725, and the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory, Department of Energy, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.

Additional details

Created:
December 20, 2023
Modified:
December 20, 2023