Speaker
Description
Density-functional theory (DFT) with extended Hubbard functionals is a powerful method for studying complex materials containing transition-metal and rare-earth elements, owing to its accuracy in correcting self-interactions and its low computational costs [1]. Recently, we developed an automated and reliable approach for the first-principles determination of the on-site U and inter-site V Hubbard parameters using density-functional perturbation theory (DFPT) [2-4]. In this talk I will show that DFPT allows us to reduce significantly computational costs, improve numerical accuracy, and fully automate the calculation of the Hubbard parameters by recasting the linear response of a localized perturbation in supercells into an array of monochromatic perturbations that can be calculated in the primitive cell. This framework can be used with different Hubbard manifolds, such as nonorthogonalized and orthogonalized atomic orbitals, including the respective calculation of Pulay (Hubbard) forces and stresses [5] that are needed for the self-consistent evaluation of Hubbard parameters [3]. I will show how this formalism can be used for the calculation of such properties as voltages in Li-ion batteries [6,7], formation energies of oxygen vacancies in perovskites [8], and I will discuss the applicability of this formalism for improving band gaps with respect to standard DFT [9] and its use for searching of novel materials for the photocatalytic water splitting [10]. Finally, I will present the extension of this framework to the calculations of phonons [11] and electron-phonon coupling [12] in selected transition-metal compounds. These tools are implemented in the open-source Quantum ESPRESSO distribution [13] and are available to the community at large.
[1] V.L. Campo Jr and M. Cococcioni, J. Phys.: Condens. Matter. 22, 055602 (2010).
[2] I. Timrov, N. Marzari, M. Cococcioni, Phys. Rev. B 98, 085127 (2018).
[3] I. Timrov, N. Marzari, M. Cococcioni, Phys. Rev. B 103, 045141 (2021).
[4] I. Timrov, N. Marzari, M. Cococcioni, Comput. Phys. Commun. 279, 108455 (2022).
[5] I. Timrov, F. Aquilante, L. Binci, M. Cococcioni, N. Marzari, Phys. Rev. B 102, 235159 (2020).
[6] I. Timrov, F. Aquilante, M. Cococcioni, N. Marzari, PRX Energy 1, 033003 (2022).
[7] I. Timrov, M. Kotiuga, N. Marzari, Phys. Chem. Chem. Phys. 25, 9061. (2023).
[8] C. Ricca, I. Timrov, M. Cococcioni, N. Marzari, U. Aschauer, Phys. Rev. Research 2, 023313 (2020).
[9] N.E. Kirchner-Hall, W. Zhao, Y. Xiong, I. Timrov, I. Dabo, Appl, Sci. 11, 2395 (2021).
[10] Y. Xiong et al., Energy Environ. Sci. 14, 2335 (2021).
[11] A. Floris, I. Timrov, B. Himmetoglu, N. Marzari, S. de Gironcoli, M. Cococcioni, Phys. Rev. B 101, 064305 (2020).
[12] J.-J. Zhou, J. Park, I. Timrov, A. Floris, M. Cococcioni, N. Marzari, M. Bernardi, Phys. Rev. Lett. 127, 126404 (2021).
[13] P. Giannozzi et al., J. Phys.: Condens. Matter 29, 465901 (2017).
