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Hybrid quantum mechanics / molecular mechanics (QM/MM) models successfully describe the properties of biological macromolecules. However, most QM/MM methodologies are constrained to unrealistic gas phase models, thus limiting their…

Chemical Physics · Physics 2022-11-08 Simone Bonfrate , Nicolas Ferré , Miquel , Huix-Rotllant

We report a new Quantum Mechanical/Molecular Dynamics (QM/MD) simulation loop to model the coupling between the electron and atom dynamics in solid/liquid interfacial systems. The method can describe simultaneously both the quantum…

Materials Science · Physics 2021-02-03 Joshua D Elliott , Alessandro Troisi , Paola Carbone

We introduce and discuss a hybrid quantum-mechanics molecular-mechanics (QM-MM) approach for Car-Parrinello DFT simulations with pseudopotentials and planewaves basis, designed for the treatment of periodic systems. In this implementation…

Materials Science · Physics 2016-07-20 Diego Hunt , Veronica M. Sanchez , Damian A. Scherlis

QM/MM hybrid methods employ accurate quantum (QM) models only in regions of interest (defects) and switch to computationally cheaper interatomic potential (MM) models to describe the crystalline bulk. We develop two QM/MM hybrid methods for…

Numerical Analysis · Mathematics 2015-09-23 Huajie Chen , Christoph Ortner

Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used.…

Chemical Physics · Physics 2018-01-17 Anton V. Sinitskiy , Gregory A. Voth

We report a novel hybrid method of simultaneous atomistic simulation of solids in critical regions (contacts surfaces, cracks areas, etc.), along with continuum modeling of other parts. The continuum is treated in terms of quasi-atoms of…

Materials Science · Physics 2026-02-17 Artem Chuprov , Egor E. Nuzhin , Alexey A. Tsukanov , Nikolay V. Brilliantov

A QM/MM implementation for periodic systems is reported. This is done for the case of molecules and for systems with two and three-dimensional periodicity, which is suitable to model electrolytes in contact with electrodes. Tests on…

Materials Science · Physics 2015-11-12 K. Doll , T. Jacob

Quantum mechanics/molecular mechanics (QM/MM) hybrid models allow one to address chemical phenomena in complex molecular environments. Whereas this modeling approach can cope with a large system size at moderate computational costs, the…

Computational Physics · Physics 2023-01-10 Katja-Sophia Csizi , Markus Reiher

We report the development and implementation of hybrid methods that combine quantum mechanics (QM) with molecular mechanics (MM) to theoretically characterize thiolated gold clusters. We use, as training systems, structures such as…

Materials Science · Physics 2012-08-06 Sandipan Banerjee , John A. Montgomery , José A. Gascón

We extend the Quantum Memory Matrix (QMM) framework, originally developed to reconcile quantum mechanics and general relativity by treating space-time as a dynamic information reservoir, to incorporate the full suite of Standard Model gauge…

General Physics · Physics 2025-04-08 Florian Neukart , Eike Marx , Valerii Vinokur

A general polarizable embedded (PE) quantum mechanics/molecular mechanics scheme for periodic systems is presented, describing mutual polarization of the two subsystems. The QM system, described with density functional theory (DFT), is…

Geometric Machine Learning (GML) has shown that respecting non-Euclidean geometry in data spaces can significantly improve performance over naive Euclidean assumptions. In parallel, Quantum Machine Learning (QML) has emerged as a promising…

We present an implementation of the quantum mechanics/molecular mechanics (QM/MM) method for periodic systems using GPU accelerated QM methods, a distributed multipole formulation of the electrostatics, and a pseudo-bond treatment of the…

Chemical Physics · Physics 2024-11-26 Chenghan Li , Garnet Kin-Lic Chan

Universal machine-learning interatomic potentials (uMLIPs) enable reactive molecular simulations with near-DFT accuracy, yet applying them efficiently to large, realistic condensed-phase systems remains computationally demanding. Here we…

Materials Science · Physics 2026-03-25 Yu Miyazaki , Atsuhiro Tomita , Akihide Hayashi , So Takamoto , Mizuki Takemoto , Hodaka Mori

The QMol-grid package provides a suite of routines for performing quantum-mechanical simulations in atomic and molecular systems, currently implemented in one spatial dimension. It supports ground- and excited-state calculations for the…

Computational Physics · Physics 2024-11-19 Francois Mauger , Cristel Chandre

Heliospheric plasmas require multi-scale and multi-physics considerations. On one hand, MHD codes are widely used for global simulations of the solar-terrestrial environments, but do not provide the most elaborate physical description of…

Computational Physics · Physics 2020-12-09 S. P. Moschou , I. V. Sokolov , O. Cohen , G. Toth , J. J. Drake , Z. Huang , C. Garraffo , J. D. Alvarado-Gómez , T. Gombosi

Interacting spin systems in solids underpin a wide range of quantum technologies, from quantum sensors and single-photon sources to spin-defect-based quantum registers and processors. We develop a quantum-computer-aided framework for…

Quantum Physics · Physics 2026-01-30 Juan Naranjo , Thi Ha Kyaw , Gaurav Saxena , Kevin Ferreira , Jack S. Baker

The implementation and validation of the adaptive buffered force QM/MM method in two popular packages, CP2K and AMBER are presented. The implementations build on the existing QM/MM functionality in each code, extending it to allow for…

Developing efficient path integral (PI) methods for atomistic simulations of vibrational spectra in heterogeneous condensed phases and interfaces has long been a challenging task. Here, we present the h-CMD method, short for hybrid centroid…

Chemical Physics · Physics 2025-05-08 Dil K. Limbu , Nathan London , Md Omar Faruque , Mohammad R. Momeni

MLMOD is a software package for incorporating machine learning approaches and models into simulations of microscale mechanics and molecular dynamics in LAMMPS. Recent machine learning approaches provide promising data-driven approaches for…

Machine Learning · Computer Science 2023-10-24 Paul J. Atzberger
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