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The recent development of the accurate and efficient semilocal density functionals on the third rung of Jacob's ladder of density functional theory such as the revised regularized strongly constrained and appropriately normed (r2SCAN)…

Computational Physics · Physics 2023-09-25 Haoliang Liu , Xue Bai , Jingliang Ning , Yuxuan Hou , Zifeng Song , Akilan Ramasamy , Ruiqi Zhang , Yefei Li , Jianwei Sun , Bing Xiao

We introduce a computational framework (InterMat) to predict band offsets of semiconductor interfaces using density functional theory (DFT) and graph neural networks (GNN). As a first step, we benchmark OptB88vdW generalized gradient…

Materials Science · Physics 2024-05-28 Kamal Choudhary , Kevin Garrity

Accurate computational predictions of metal-organic frameworks (MOFs) and their properties is crucial for discovering optimal compositions and applying them in relevant technological areas. This work benchmarks density functional theory…

Materials Science · Physics 2025-03-11 Joshua Edzards , Julia Santana Andreo , Holger-Dietrich Saßnick , Caterina Cocchi

Density functional theory within the local or semilocal density approximations (DFT-LDA/GGA) has become a workhorse in electronic structure theory of solids, being extremely fast and reliable for energetics and structural properties, yet…

We propose a range-separated hybrid exchange-correlation functional to calculate solid-state material properties. The functional mixes Hartree-Fock exchange with the semilocal exchange of the meta-generalized gradient approximation…

Materials Science · Physics 2025-02-27 Subrata Jana , Abhishek Bhattacharjee , Suman Mahakal , Szymon Smiga , Prasanjit Samal

We performed density functional calculations to estimate the formation energies of intermetallic alloys. We used two semilocal approximations, the generalized gradient approximation (GGA) by Perdew-Burke-Ernzerhof (PBE) and the strongly…

Materials Science · Physics 2020-11-25 Niraj K. Nepal , Santosh Adhikari , Bimal Neupane , Adrienn Ruzsinszky

Computationally-efficient semilocal approximations of density functional theory at the level of the local spin density approximation (LSDA) or generalized gradient approximation (GGA) poorly describe weak interactions. We show improved…

The Jacob's ladder of density functional theory (DFT) proposes the compelling view that by extending the form of successful approximations -- being guided by exact conditions and selected (least empirical) norms -- upper rungs will do…

Materials Science · Physics 2025-02-25 Jacques K. Desmarais , Alessandro Erba , Giovanni Vignale , Stefano Pittalis

The correct treatment of d electrons is of prime importance in order to predict the electronic properties of the prototype chalcopyrite semiconductors. The effect of d states is linked with the anion displacement parameter u, which in turn…

The density functional theory (DFT) approximations that are the most accurate for the calculation of band gap of bulk materials are hybrid functionals like HSE06, the MBJ potential, and the GLLB-SC potential. More recently, generalized…

Accurate predictions of material properties within the chemical space of transition metal fluorides (TMFs), using density functional theory (DFT) is important for advancing several technological applications. The state-of-the-art semi-local…

Materials Science · Physics 2024-12-17 Dereje Bekele Tekliye , Gopalakrishnan Sai Gautam

The recent TASK meta-GGA density functional [Phys. Rev. Research, 1, 033082 (2019)] is constructed with an enhanced nonlocality in the generalized Kohn-Sham scheme, and therefore harbors great opportunities for band gap prediction. Although…

Materials Science · Physics 2021-06-30 Bimal Neupane , Hong Tang , Niraj K. Nepal , Santosh Adhikari , Adrienn Ruzsinszky

The journey of theoretical study on semiconductors is reviewed in a non-conventional way. We have started with the basic introduction of Hartree-Fock method and introduce the fundamentals of Density Functional Theory (DFT). From the oldest…

Materials Science · Physics 2021-05-04 Sujoy Datta , Debnarayan Jana

The study of defects in materials is of utmost importance for technological applications and the design of new materials. In this work, we analyze the performance of density functional approximations on two prototypical sets of defective…

The band gap is an important parameter of semiconductor materials that influences several functional properties, in particular optical properties. However, a fast and reliable first-principles prediction of band gaps remains a challenging…

Several recent studies have shown that SCAN, a functional belonging to the meta-generalized gradient approximation (MGGA) family, leads to significantly overestimated magnetic moments in itinerant ferromagnetic metals. However, this…

The strongly constrained and appropriately normed (SCAN) semilocal density functional [J. Sun, A. Ruzsinszky, J. P. Perdew \textit{Phys. Rev. Lett.} {\bf 115}, 036402 (2015)] obeys all 17 known exact constraints for…

Materials Science · Physics 2016-09-28 J. G. Brandenburg , J. E. Bates , A. Ruzsinszky , J. Sun , J. P. Perdew

We demonstrate the accuracy of the hybrid functional HSE06 for computing band offsets of semiconductor alloy heterostructures. The highlight of this study is the computation of conduction band offsets with a reliability that has eluded…

Materials Science · Physics 2015-05-19 Amita Wadehra , Jeremy W. Nicklas , John W. Wilkins

In this contribution we assess the performance of two different exchange-correlation functionals in the first-principle prediction of the lattice thermal conductivity of bulk semiconductors, namely the local density approximation (LDA) and…

Materials Science · Physics 2018-11-16 Marco Arrigoni , Georg K. H. Madsen

Kohn-Sham density functional theory (DFT) is nowadays widely used for electronic structure theory simulations, and the accuracy and efficiency of DFT rely on approximations of the exchange-correlation functional. By inclusion of the kinetic…

Materials Science · Physics 2023-06-01 Renxi Liu , Daye Zheng , Xinyuan Liang , Xinguo Ren , Mohan Chen , Wenfei Li
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