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This work presents an alternative, general, and in-principle exact extension of electronic Kohn-Sham density functional theory (KS-DFT) to the fully quantum-mechanical molecular problem. Unlike in existing multi-component or…

Chemical Physics · Physics 2024-05-14 Emmanuel Fromager , Benjamin Lasorne

Molecular mechanics (MM) potentials have long been a workhorse of computational chemistry. Leveraging accuracy and speed, these functional forms find use in a wide variety of applications in biomolecular modeling and drug discovery, from…

Gradient-domain machine learning (GDML) is an accurate and efficient approach to learn a molecular potential and associated force field based on the kernel ridge regression algorithm. Here, we demonstrate its application to learn an…

Computational Physics · Physics 2020-06-24 Jiang Wang , Stefan Chmiela , Klaus-Robert Müller , Frank Noè , Cecilia Clementi

In recent years, molecular dynamics (MD) simulations have emerged as a pivotal tool for understanding the structure, dynamics, and phase behavior in charged soft matter systems. To explore phenomena across greater length and time scales in…

Computational Physics · Physics 2024-07-18 Benjamin Bobin Ye , Shensheng Chen , Zhen-Gang Wang

Quantum mechanical methods like Density Functional Theory (DFT) are used with great success alongside efficient search algorithms for studying kinetics of reactive systems. However, DFT is prohibitively expensive for large scale…

Computational Physics · Physics 2022-09-02 Mathias Schreiner , Arghya Bhowmik , Tejs Vegge , Peter Bjørn Jørgensen , Ole Winther

Predicting interfacial thermodynamics across molecular and continuum scales remains a central challenge in computational science. Classical density functional theory (cDFT) provides a first-principles route to connect microscopic…

Computational Physics · Physics 2026-01-01 Edoardo Monti , Peter Yatsyshin , Konstantinos Gkagkas , Andrew B. Duncan

In this paper, we investigate the energy minimization model of the ensemble Kohn-Sham density functional theory for metallic systems, in which a pseudo-eigenvalue matrix and a general smearing approach are involved. We study the invariance…

Numerical Analysis · Mathematics 2022-01-19 Xiaoying Dai , Stefano de Gironcoli , Bin Yang , Aihui Zhou

Understanding how structural flexibility affects the properties of metal-organic frameworks (MOFs) is crucial for the design of better MOFs for targeted applications. Flexible MOFs can be studied with molecular dynamics simulations, whose…

Materials Science · Physics 2024-05-13 Abhishek Sharma , Stefano Sanvito

We show that non-relativistic Quantum Mechanics can be faithfully represented in terms of a classical diffusion process endowed with a gauge symmetry of group Z_4. The representation is based on a quantization condition for the realized…

Probability · Mathematics 2007-11-23 Claudio Albanese

We study the accuracy of Kohn-Sham density functional theory (DFT) for warm- and hot-dense matter (WDM and HDM). Specifically, considering a wide range of systems, we perform accurate ab initio molecular dynamics simulations with…

Computational Physics · Physics 2024-11-21 Phanish Suryanarayana , Arpit Bhardwaj , Xin Jing , Shashikant Kumar , John E. Pask

Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical…

Chemical Physics · Physics 2019-06-25 K. T. Schütt , M. Gastegger , A. Tkatchenko , K. -R. Müller , R. J. Maurer

Molecular Dynamics - Green's Functions Reaction Dynamics (MD-GFRD) is a multiscale simulation method for particle dynamics or particle-based reaction-diffusion dynamics that is suited for systems involving low particle densities. Particles…

Chemical Physics · Physics 2017-12-06 Luigi Sbailò , Frank Noé

In most cases the ultrafast dynamics of resonantly excited molecules are considered, and almost always computed in the molecular frame, while experiments are carried out in the laboratory frame. Here we provide a formalism in terms of a lab…

Chemical Physics · Physics 2022-11-09 Margaret Gregory , Simon Neville , Michael Schuurman , Varun Makhija

Due to the wide range of timescales that are present in macromolecular systems, hierarchical multiscale strategies are necessary for their computational study. Coarse-graining (CG) allows to establish a link between different system…

Micro-scale mechanisms, such as inter-particle and particle-fluid interactions, govern the behaviour of granular systems. While particle-scale simulations provide detailed insights into these interactions, their computational cost is often…

Fundamental understanding of interatomic forces in molecules must emerge from quantum mechanics, yet widely used empirical force fields rely on simplified mechanistic approximations that often fail to capture the complexity of many-body…

A quantitative and predictive theory of quantum light-matter interactions in ultra thin materials involves several fundamental challenges. Any realistic model must simultaneously account for the ultra-confined plasmonic modes and their…

This paper derives and demonstrates a new, purely density-based ab initio approach for calculation of the energies and properties of many-electron systems. It is based upon the discovery of relationships that govern the "mechanics" of the…

Chemical Physics · Physics 2024-09-04 James C. Ellenbogen

We propose a lattice density-functional theory for {\it ab initio} quantum chemistry or physics as a route to an efficient approach that approximates the full configuration interaction energy and orbital occupations for molecules with…

Strongly Correlated Electrons · Physics 2019-04-19 J. P. Coe

Accurately modeling chemical reactions at the atomistic level requires high-level electronic structure theory due to the presence of unpaired electrons and the need to properly describe bond breaking and making energetics. Commonly used…