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Calculating perturbation response properties of materials from first principles provides a vital link between theory and experiment, but is bottlenecked by the high computational cost. Here a general framework is proposed to perform density…

Computational Physics · Physics 2024-03-01 He Li , Zechen Tang , Jingheng Fu , Wen-Han Dong , Nianlong Zou , Xiaoxun Gong , Wenhui Duan , Yong Xu

Deep-learning density functional theory (DFT) shows great promise to significantly accelerate material discovery and potentially revolutionize materials research. However, current research in this field primarily relies on data-driven…

Computational Physics · Physics 2024-08-14 Yang Li , Zechen Tang , Zezhou Chen , Minghui Sun , Boheng Zhao , He Li , Honggeng Tao , Zilong Yuan , Wenhui Duan , Yong Xu

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when…

Density-potential functional theory (DPFT) is an alternative formulation of orbital-free density functional theory that may be suitable for modeling the electronic structure of large systems. To date, DPFT has been applied mainly to quantum…

Materials Science · Physics 2023-04-21 Martin-Isbjörn Trappe , William C. Witt , Sergei Manzhos

Differentiable programming has facilitated numerous methodological advances in scientific computing. Physics engines supporting automatic differentiation have simpler code, accelerating the development process and reducing the maintenance…

Computational Physics · Physics 2023-04-04 Chuin Wei Tan , Chris J. Pickard , William C. Witt

Stochastic and mixed stochastic-deterministic density functional theory (DFT) are promising new approaches for the calculation of the equation-of-state and transport properties in materials under extreme conditions. In the intermediate warm…

Computational Physics · Physics 2023-09-27 Vidushi Sharma , Lee A. Collins , Alexander J. White

Density functional theory (DFT) offers a desirable balance between quantitative accuracy and computational efficiency in practical many-electron calculations. Its central component, the exchange-correlation energy functional, has been…

Density functional theory (DFT) is an essential building block for modern theoretical physics, chemistry, and engineering, especially those concerning electronic properties. Through decades of development, various program packages for…

Materials Science · Physics 2022-11-21 Yusuke Nomura , Ryosuke Akashi

Density Functional Theory (DFT) is widely used for first-principles simulations in chemistry and materials science, but its computational cost remains a key limitation for large systems. Motivated by recent advances in ML-based…

Materials Science · Physics 2026-02-19 Rakshit Kumar Singh , Aryan Amit Barsainyan , Bharath Ramsundar

Unlike covalent two-dimensional (2D) materials like graphene, 2D metals have non-layered structures due to their non-directional, metallic bonding. While experiments on 2D metals are still scarce and challenging, density-functional theory…

Materials Science · Physics 2023-01-06 Kameyab Raza Abidi , Pekka Koskinen

This work presents the formalism and implementation of excited state nuclear forces within density functional linear response theory (TDDFT) using a plane wave basis set. An implicit differentiation technique is developed for computing…

Other Condensed Matter · Physics 2009-11-11 Nikos L. Doltsinis , D. S. Kosov

A density functional theory (DFT) framework is presented that links functional derivatives of free-energy functionals to non-linear static density response functions in quantum many-body systems. Within this framework, explicit expressions…

Density functional theory (DFT) serves as the basis for computational discovery in materials science and chemistry, yet each calculation demands extensive human effort: adjusting algorithms when convergence stalls, revising plans when…

Materials Science · Physics 2026-05-27 Penghui Yang , Zhonghan Zhang , Yue Li , Xinrun Wag , Yanchen Deng , Yuhao Lu , Bijun Tang , Zheng Liu , Bo An

Density Functional Theory (DFT) is widely used for atomistic simulations. However, its reach stays limited due to several limitations such as lack of accurate exchange-correlation functional, requirement of costly O(N 3) diagonalization…

Quantum Physics · Physics 2026-05-18 Namrata Manglani , Samrit Kumar Maity , Shashank Sharma , Soham Phulare , Sanjay Wandhekar

Density functional theory (DFT) is the de facto approach for predicting self-consistent-field electronic structures of ground-state configurations of complex atoms, molecules, and solids and providing their property data for materials…

Materials Science · Physics 2024-01-30 Zi-Kui Liu

Classical Density Functional Theory (DFT) is a statistical-mechanical framework to analyze fluids, which accounts for nanoscale fluid inhomogeneities and non-local intermolecular interactions. DFT can be applied to a wide range of…

Computational Engineering, Finance, and Science · Computer Science 2017-02-07 Andreas Nold , Benjamin D. Goddard , Peter Yatsyshin , Nikos Savva , Serafim Kalliadasis

Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate…

Density Functional Theory (DFT) is one of the most widely used methods for "ab initio" calculations of the structure of atoms, molecules, crystals, surfaces, and their interactions. Unfortunately, the customary introduction to DFT is often…

Physics Education · Physics 2010-12-07 Nathan Argaman , Guy Makov

Phonons are quantized vibrations of a crystal lattice that play a crucial role in understanding many properties of solids. Density functional theory (DFT) provides a state-of-the-art computational approach to lattice vibrations from…

Density Functional Theory (DFT) allows for predicting all the chemical and physical properties of molecular systems from first principles by finding an approximate solution to the many-body Schr\"odinger equation. However, the cost of these…

Machine Learning · Computer Science 2025-06-03 Majdi Hassan , Cristian Gabellini , Hatem Helal , Dominique Beaini , Kirill Neklyudov
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