TY - JOUR
T1 - Exchange-correlation functionals in 2D materials
T2 - applications, challenges, and limitations
AU - Javed, Ahsan
AU - Shaheen, Mahvish
AU - Shahbaz, Muhammad
AU - Sufyan Ramzan, Muhammad
AU - Ullah, Rafi
AU - Jiang, Wei
N1 - Publisher Copyright:
© 2026 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved. This article is available under the terms of the IOP-Standard License.
PY - 2026/9/11
Y1 - 2026/9/11
N2 - 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.
AB - 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.
KW - exchange-correlation functionals
KW - layered materials
KW - machine learning
KW - many-body methods
KW - pseudopotentials
KW - quantum confinement
UR - https://www.scopus.com/pages/publications/105049226093
U2 - 10.1088/1361-6528/ae9d27
DO - 10.1088/1361-6528/ae9d27
M3 - Review article
C2 - 42633765
AN - SCOPUS:105049226093
SN - 0957-4484
VL - 37
JO - Nanotechnology
JF - Nanotechnology
IS - 36
M1 - 362001
ER -