Nov 2025· Nanotechnology· Vol 37· 1 citation· 22 references
MedicinePhysics
Abstract
The rapid development of two-dimensional (2D) materials has reshaped modern nanoscience, offering properties that differ fundamentally from their bulk counterparts. As experimental discovery accelerates, the need for reliable computational techniques has become increasingly important. Within the framework of density functional theory, this review explores the critical role of exchange-correlation (XC) functionals in predicting key material properties such as structural, optoelectronic, magnetic, and thermal properties. We examine the challenges posed by quantum confinement, anisotropic screening, and van der Waals interactions, which conventional functionals often fail to describe. Advanced approaches, including meta-generalized gradient approximation, hybrid functionals, and many-body perturbation theory (e.g. GW and Bethe–Salpeter equation), are assessed for their improved accuracy in capturing electronic structure and excitonic effects. We further discuss the non-universality of functionals across different 2D material families and the emerging role of machine learning to enhance computational efficiency. Finally, the review outlines current limitations and emerging strategies, providing a roadmap for advancing XC functionals and beyond, to enable the practical design and application of 2D materials.
We present a novel exchange correlation functional, C09x-PBEc, which combines C09 exchange with PBE correlation, to accurately model the ferroelectric properties of perovskites while retaining the computational efficiency of GGA functionals. With a growing interest in developing machine learning interatomic potentials...
Density functional theory (DFT) has become one of the principal theoretical frameworks for
investigating the electronic structure, energetics and properties of atoms, molecules, solids and interfaces. Its
importance arises from its favorable balance between computational cost and predictive capability compared with man...
Hariharan Vaiyapuri Manemaran, Girija Kesavan· International Journal of Mul...· 0 citations
Accurately predicting excited-state properties of heterogeneous systems remains a central challenge in computational chemistry and materials science. Dielectric-dependent hybrid functionals have achieved notable success for bulk semiconductors and insulators, but their reliance on a scalar macroscopic dielectric consta...
Jia-Wei Zhan, Giulia Galli· Journal of Chemical Theory a...· 2 citations
The present work revisits the methods within CP2K that turn electronic structure into dynamics, transport, and spectroscopic response, highlighting CP2K's unique capability to unify quantum chemistry with quantum and statistical mechanics within a versatile, holistic simulation environment.
Jan Wilhelm, Anna-Sophia Hehn, Hossam Elgabarty et al.· 1 citation· ⚡1
Delocalisation error has been argued to be the greatest outstanding challenge in density-functional theory (DFT). One of the most promising routes to minimise this error is development of local hybrid functionals, in which the fraction of exact-exchange mixing is position dependent. However, existing local hybrids capa...
The application of density functional theory to heterogeneous catalysis is hindered by the shortcomings of conventional density functional approximations. We combine machine learning with explicitly non-local physically informed descriptors and introduce an exchange-correlation functional (CIDER26SS) framework regulari...
M. S. Abdallah, Zhuo-Tao Jin, Boris Kozinsky et al.· 1 citation· ⚡1
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