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<p>The emergence of two-dimensional (2D) materials has revolutionized the landscape of condensed matter physics and materials science, offering novel properties and functionalities with broad applicability in electronics, energy storage, catalysis, and quantum technologies. Density functional theory (DFT) has been instrumental in driving the theoretical understanding and predictive modeling of these materials. This review provides a detailed examination of the fundamental principles of DFT and explores the numerous challenges that arise when applying it to 2D systems. Key issues include size and dimensionality effects, van der Waals interactions, structural distortions, phase transitions, electronic correlations, band gap underestimation, charge transfer, surface and interface modeling, and temperature-dependent phenomena. We discuss how these challenges impact the accuracy, scalability, and predictive power of DFT simulations. Furthermore, we highlight recent methodological advancements—including improved exchange–correlation functionals, beyond-DFT methods (e.g., GW, BSE, DFT + U), dimensionality-aware modeling, and machine learning techniques—that have been developed to overcome these limitations. By assessing both the current state and future directions of DFT-based modeling, this review aims to provide a comprehensive resource for researchers engaged in the computational exploration and design of novel 2D materials.</p> Graphical abstract <p></p>

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Review: beyond the surface—exploring the complexities of 2D materials with density functional theory

  • 期刊论文

  • 发表日期：

    2025年7月29日

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  • Mohammed Abdulabbas Hasan,
  • Heider A. Abdulhussein

摘要

The emergence of two-dimensional (2D) materials has revolutionized the landscape of condensed matter physics and materials science, offering novel properties and functionalities with broad applicability in electronics, energy storage, catalysis, and quantum technologies. Density functional theory (DFT) has been instrumental in driving the theoretical understanding and predictive modeling of these materials. This review provides a detailed examination of the fundamental principles of DFT and explores the numerous challenges that arise when applying it to 2D systems. Key issues include size and dimensionality effects, van der Waals interactions, structural distortions, phase transitions, electronic correlations, band gap underestimation, charge transfer, surface and interface modeling, and temperature-dependent phenomena. We discuss how these challenges impact the accuracy, scalability, and predictive power of DFT simulations. Furthermore, we highlight recent methodological advancements—including improved exchange–correlation functionals, beyond-DFT methods (e.g., GW, BSE, DFT + U), dimensionality-aware modeling, and machine learning techniques—that have been developed to overcome these limitations. By assessing both the current state and future directions of DFT-based modeling, this review aims to provide a comprehensive resource for researchers engaged in the computational exploration and design of novel 2D materials.

Graphical abstract