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Density Functional Theory Methods for Computing and Predicting Mechanical Properties

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Multiscale Materials Modeling for Nanomechanics

Part of the book series: Springer Series in Materials Science ((SSMATERIALS,volume 245))

Abstract

Density functional theory (DFT) is one of the most powerful and efficient approaches for predicting the properties of materials. Although formally exact, all modern DFT methods invoke various levels of approximation, due to the unknown form of the exact exchange-correlation functional. This book chapter focuses on four such representative functionals within the local density approximation, generalized gradient approximation, DFT-D, and nonlocal vdW DFT families to highlight their relevance in various mechanical and structural properties. In particular, to illustrate the use of these first-principles methods, we focus on two specific mechanical systems: palladium-hydride materials and spiropyran-based mechanochromic polymers, both of which pose unique challenges to electronic structure methods. We explore how these various DFT methods can be utilized to predict important mechanical properties such as cohesive energies, maximum strength, stress–strain properties, and mechanochromic effects. Finally, we conclude this chapter with a detailed analysis of the different functional families and highlight the relevance of each method for predicting the diverse mechanical properties of these material systems.

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Ilawe, N.V., Cercy Groulx, M.N., Wong, B.M. (2016). Density Functional Theory Methods for Computing and Predicting Mechanical Properties. In: Weinberger, C., Tucker, G. (eds) Multiscale Materials Modeling for Nanomechanics. Springer Series in Materials Science, vol 245. Springer, Cham. https://doi.org/10.1007/978-3-319-33480-6_4

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