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We present an efficient implementation of a surface Green's-function method for atomistic modeling of surfaces within the framework of density functional theory using a pseudopotential localized basis set approach. In this method, the…

Electrostatic interactions play crucial roles in biophysical processes such as protein folding and molecular recognition. Poisson-Boltzmann equation (PBE)-based models have emerged as widely used in modeling these important processes.…

Computational Physics · Physics 2017-04-11 Ruxi Qi , Wesley M. Botello-Smith , Ray Luo

Solving partial differential equations (PDEs) on fine spatio-temporal scales for high-fidelity solutions is critical for numerous scientific breakthroughs. Yet, this process can be prohibitively expensive, owing to the inherent complexities…

Numerical Analysis · Mathematics 2024-04-09 Yulong Lu , Wuzhe Xu

Function approximation is crucial in Flexible Electronics (FE), where applications demand efficient computational techniques within strict constraints on size, power, and performance. Devices like wearables and compact sensors are…

Hardware Architecture · Computer Science 2026-02-12 Paula Carolina Lozano Duarte , Aradhana Dube , Georgios Zervakis , Mehdi Tahoori , Sani Nassif

Recently, Tao and Mo (TM) derived a meta-generalized gradient approximation functional based on a model exchange-correlation hole. In this work, the performance of this functional is assessed on standard test sets, using the…

Chemical Physics · Physics 2017-01-04 Yuxiang Mo , Guocai Tian , Roberto Car , Viktor N. Staroverov , Gustavo E. Scuseria , Jianmin Tao

A general procedure for the optimization of atomic density-fitting basis functions is designed with the balance between accuracy and numerical stability in mind. Given one-electron wavefunctions and energies, weights are assigned to the…

Chemical Physics · Physics 2020-10-13 Dimitri N. Laikov

The Squared-Gradient approximation to the Modified-Core Van der Waals density functional theory model is developed. A simple, explicit expression for the SGA coefficient involving only the bulk equation of state and the interaction…

Soft Condensed Matter · Physics 2011-05-03 James F. Lutsko

The construction of meta generalized gradient approximations based on the density matrix expansion (DME) is considered as one of the most accurate technique to design semilocal exchange energy functionals in two-dimensional density…

Materials Science · Physics 2018-05-09 Abhilash Patra , Subrata Jana , Prasanjit Samal

Approximations to the exact density functional for the exchange-correlation energy of a many-electron ground state can be constructed by satisfying constraints that are universal, i.e., valid for all electron densities. Gedanken densities…

Chemical Physics · Physics 2015-06-19 John P. Perdew , Adrienn Ruzsinszky , Jianwei Sun , Kieron Burke

In this paper, we want to clarify the Gibbs phenomenon when continuous and discontinuous finite elements are used to approximate discontinuous or nearly discontinuous PDE solutions from the approximation point of view. For a simple step…

Numerical Analysis · Mathematics 2022-08-03 Shun Zhang

In this article, we use hybrid density functional (HSE06) to study the crystal and electronic structures and optical properties of well known phase change memory material $\mathrm{Ge_{2}Sb_{2}Te_{5}}$. We calculate the structural…

Materials Science · Physics 2015-06-05 T. Kaewmaraya , M. Ramzan , 1 H. Löfås , Rajeev Ahuja

We investigate fundamental properties of meta-generalized-gradient approximations (meta-GGAs) to the exchange-correlation energy functional, which have an implicit density dependence via the Kohn-Sham kinetic-energy density. To this…

Chemical Physics · Physics 2014-12-10 F. G. Eich , Maria Hellgren

Density functionals at the level of the Generalized Gradient Approximation (GGA) and a plane-wave basis set are widely used today to perform ab initio molecular dynamics (AIMD) simulations. Going up in the ladder of accuracy of density…

Computational Physics · Physics 2021-10-18 Sagarmoy Mandal , Ritama Kar , Tobias Kloeffel , Bernd Meyer , Nisanth N. Nair

In generic classical and quantum many-body systems, where typically energy and particle number are the only conserved quantities, stationary states are described by thermal equilibrium. In contrast, integrable systems showcase an infinite…

Quantum Gases · Physics 2026-01-13 Alvise Bastianello , Alexey Tikan , Francois Copie , Stephane Randoux , Pierre Suret

A recent study of Mejia-Rodriguez and Trickey [Phys. Rev. A 96, 052512 (2017)] showed that the deorbitalization procedure (replacing the exact Kohn-Sham kinetic-energy density by an approximate orbital-free expression) applied to…

Materials Science · Physics 2018-10-10 Fabien Tran , Péter Kovács , Leila Kalantari , Georg K. H. Madsen , Peter Blaha

The gradient expansion of the kinetic energy functional, when applied for atoms or finite systems, usually grossly overestimates the energy in the fourth order and generally diverges in the sixth order. We avoid the divergence of the…

Quantum Physics · Physics 2015-08-28 A. Sergeev , R. Jovanovic , S. Kais , F. H. Alharbi

Finite element simulations have been used to solve various partial differential equations (PDEs) that model physical, chemical, and biological phenomena. The resulting discretized solutions to PDEs often do not satisfy requisite physical…

Numerical Analysis · Mathematics 2022-03-17 Vidhi Zala , Robert M. Kirby , Akil Narayan

By investigating the crystalline structure of ground-state orthorhombic SrRuO$_3$, we present a benchmark study of some of the most popular density functional theory (DFT) approaches from the local density approximation (LDA),…

Materials Science · Physics 2016-08-03 Š. Masys , V. Jonauskas

We have investigated the electronic structure of fluorite Cu$_{2}$Se using density functional theory calculations within the LDA, PBE and AM05 approximations as well as with the non-local hybrid PBE0 and HSE approximations. Our results show…

Materials Science · Physics 2013-03-04 Mikael Råsander , Lars Bergqvist , Anna Delin

Partial differential equations (PDEs) are important tools to model physical systems and including them into machine learning models is an important way of incorporating physical knowledge. Given any system of linear PDEs with constant…

Machine Learning · Statistics 2023-11-03 Marc Härkönen , Markus Lange-Hegermann , Bogdan Raiţă