Function domains and the universal matrix functional of multi-state density functional theory DOI
Yangyi Lu, Jiali Gao

The Journal of Chemical Physics, Год журнала: 2025, Номер 162(10)

Опубликована: Март 11, 2025

On the basis of recent advancements in Hamiltonian matrix density functional for multiple electronic eigenstates, this study delves into mathematical foundation multistate theory (MSDFT). We extend a number physical concepts at core Kohn–Sham DFT, such as representability, to functional. In work, we establish existence universal many states proper generalization Lieb ground state. Consequently, variation principle MSDFT can be rigorously defined within an appropriate domain densities, thereby providing solid framework DFT both state and excited states. further show that analytical structure is considerably constrained by subspace symmetry invariance properties, requiring ensuring all elements are variationally optimized coherent manner until spanned lowest eigenstates obtained. This work solidifies theoretical treat using theory.

Язык: Английский

Best‐Practice DFT Protocols for Basic Molecular Computational Chemistry** DOI
Markus Bursch, Jan‐Michael Mewes, Andreas Hansen

и другие.

Angewandte Chemie International Edition, Год журнала: 2022, Номер 61(42)

Опубликована: Сен. 14, 2022

Nowadays, many chemical investigations are supported by routine calculations of molecular structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share these quantum-chemical applies density functional theory (DFT) evaluated in atomic-orbital basis sets. This work provides best-practice guidance on the numerous methodological technical aspects DFT three parts: Firstly, we set stage introduce a step-by-step decision tree to choose computational protocol that models experiment as closely possible. Secondly, present recommendation matrix guide choice depending task at hand. A particular focus is achieving an optimal balance between accuracy, robustness, efficiency through multi-level approaches. Finally, discuss selected representative examples illustrate recommended protocols effect choices.

Язык: Английский

Процитировано

493
Best‐Practice DFT Protocols for Basic Molecular Computational Chemistry** DOI Creative Commons
Markus Bursch, Jan‐Michael Mewes, Andreas Hansen

и другие.

Angewandte Chemie, Год журнала: 2022, Номер 134(42)

Опубликована: Сен. 14, 2022

Abstract Nowadays, many chemical investigations are supported by routine calculations of molecular structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share these quantum‐chemical applies density functional theory (DFT) evaluated in atomic‐orbital basis sets. This work provides best‐practice guidance on the numerous methodological technical aspects DFT three parts: Firstly, we set stage introduce a step‐by‐step decision tree to choose computational protocol that models experiment as closely possible. Secondly, present recommendation matrix guide choice depending task at hand. A particular focus is achieving an optimal balance between accuracy, robustness, efficiency through multi‐level approaches. Finally, discuss selected representative examples illustrate recommended protocols effect choices.

Язык: Английский

Процитировано

98
GPAW: An open Python package for electronic structure calculations DOI Creative Commons
Jens Jørgen Mortensen, Ask Hjorth Larsen, Mikael Kuisma

и другие.

The Journal of Chemical Physics, Год журнала: 2024, Номер 160(9)

Опубликована: Март 7, 2024

We review the GPAW open-source Python package for electronic structure calculations. is based on projector-augmented wave method and can solve self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, numerical atomic orbitals. The representations are complementary mutually independent be connected by transformations via grid. This multi-basis feature renders highly versatile unique among similar codes. By virtue of its modular structure, code constitutes an ideal platform implementation new features methodologies. Moreover, it well integrated with Atomic Simulation Environment (ASE), providing a flexible dynamic user interface. In addition to ground-state DFT calculations, supports many-body GW band structures, optical excitations from Bethe-Salpeter Equation, variational calculations excited states in molecules solids direct optimization, real-time propagation Kohn-Sham within time-dependent DFT. A range more advanced methods describe magnetic non-collinear magnetism also now available. addition, calculate non-linear tensors solids, charged crystal point defects, much more. Recently, support graphics processing unit (GPU) acceleration has been achieved minor modifications thanks CuPy library. end outlook, describing some future plans GPAW.

Язык: Английский

Процитировано

88
Ab initio quantum chemistry with neural-network wavefunctions DOI
Jan Hermann,

James Spencer,

Kenny Choo

и другие.

Nature Reviews Chemistry, Год журнала: 2023, Номер 7(10), С. 692 - 709

Опубликована: Авг. 9, 2023

Язык: Английский

Процитировано

62
Ensemble Density Functional Theory of Ground and Excited Energy Levels DOI
Emmanuel Fromager

The Journal of Physical Chemistry A, Год журнала: 2025, Номер unknown

Опубликована: Янв. 20, 2025

A Kohn–Sham (KS) density-functional energy expression is derived for any (ground or excited) state within a given many-electron ensemble along with the stationarity condition it fulfills respect to density, thus giving access both physical levels and individual-state densities, in principle exactly. We also provide working equations evaluation of latter from true static density–density linear response function. Unlike Gould's recent potential functional approach excited states [arXiv:2404.12593], we use density as sole basic variable. While state-specific KS naturally emerges present formalism, at exact Hartree-exchange-only (Hx) level approximation, standard implementation orbital-optimized theory recovered when recycling regular ground-state Hx-correlation this context.

Язык: Английский

Процитировано

2
Development and Applications of the Density-Based Theory of Chemical Reactivity DOI
Chunying Rong, Dongbo Zhao, Xin He

и другие.

The Journal of Physical Chemistry Letters, Год журнала: 2022, Номер 13(48), С. 11191 - 11200

Опубликована: Ноя. 29, 2022

Density functional theory, which is well-recognized for its accuracy and efficiency, has become the workhorse modeling electronic structure of molecules extended materials in recent decades. Nevertheless, establishing a density-based conceptual framework to appreciate bonding, stability, function, reactivity, other physicochemical properties still an unaccomplished task. In this Perspective, we at first provide overview four pathways currently available literature tackle matter, including orbital-free density direct use density-associated quantities, information-theoretic approach. Then, highlight several advances employing these approaches realize new understandings chemical concepts such as covalent noncovalent interactions, cooperation, frustration, homochirality, chirality hierarchy, electrophilicity, nucleophilicity, regioselectivity, stereoselectivity. Finally, few possibilities future development relatively uncharted territory. Opportunities are abundant, they all ours taking.

Язык: Английский

Процитировано

42
The quest for superheavy elements and the limit of the periodic table DOI
Odile R. Smits, Ch. E. Düllmann, P. Indelicato

и другие.

Nature Reviews Physics, Год журнала: 2023, Номер 6(2), С. 86 - 98

Опубликована: Дек. 11, 2023

Язык: Английский

Процитировано

35
Ultrahigh capacity and reversible hydrogen storage media based on Li-decorated T-BN monolayers DOI
Yongliang Yong, Qihua Hou, Xiaobo Yuan

и другие.

Journal of Energy Storage, Год журнала: 2023, Номер 72, С. 108169 - 108169

Опубликована: Июль 6, 2023

Язык: Английский

Процитировано

34
A Perspective on Sustainable Computational Chemistry Software Development and Integration DOI Creative Commons

Rosa Di Felice,

Maricris L. Mayes, Ryan M. Richard

и другие.

Journal of Chemical Theory and Computation, Год журнала: 2023, Номер 19(20), С. 7056 - 7076

Опубликована: Сен. 28, 2023

The power of quantum chemistry to predict the ground and excited state properties complex chemical systems has driven development computational software, integrating advances in theory, applied mathematics, computer science. emergence new paradigms associated with exascale technologies also poses significant challenges that require a flexible forward strategy take full advantage existing forthcoming resources. In this context, sustainability interoperability software are among most pressing issues. perspective, we discuss infrastructure needs investments an eye fully utilize resources provide unique tools for next-generation science problems scientific discoveries.

Язык: Английский

Процитировано

28
In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back DOI
Abdulrahman Aldossary, Jorge A. Campos-Gonzalez-Angulo, Sergio Pablo‐García

и другие.

Advanced Materials, Год журнала: 2024, Номер 36(30)

Опубликована: Май 25, 2024

Abstract Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving Schrödinger equations increasing cost with size molecular system. In response, there has been a surge interest in leveraging artificial intelligence (AI) machine learning (ML) techniques silico experiments. Integrating AI ML into increases scalability speed exploration space. remain, particularly regarding reproducibility transferability models. This review highlights evolution from, complementing, or replacing energy property predictions. Starting from models trained entirely on numerical data, journey set forth toward ideal model incorporating physical laws quantum mechanics. paper also reviews existing their intertwining, outlines roadmap future research, identifies areas improvement innovation. Ultimately, goal develop architectures capable accurate transferable solutions equation, thereby revolutionizing experiments within materials science.

Язык: Английский

Процитировано

17