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Based on Monte Carlo (MC) computer simulations we study the structure formation of a system of magnetic nanorods. Our model particles consist of fused spheres with permanent magnetic dipole moments, as inspired by recent experiments. The…

Soft Condensed Matter · Physics 2012-03-22 Carlos E. Alvarez , Sabine H. L. Klapp

We have formulated a relaxation mechanism for ferrites and ferromagnetic metals whereby the coupling between the magnetic motion and lattice is based purely on continuum arguments concerning magnetostriction. This theoretical approach…

Materials Science · Physics 2015-05-13 C. Vittoria , S. D. Yoon , A. Widom

In this paper, a theoretical scheme is proposed for shape-programming of thin hyperelastic plates through differential growth. First, starting from the 3D governing system of a hyperelastic (neo-Hookean) plate, a consistent finite-strain…

Computational Engineering, Finance, and Science · Computer Science 2022-02-07 Jiong Wang , Zhanfeng Li , Zili Jin

The direct variational optimization of the two-electron reduced density matrix (2RDM) can provide a reference-independent description of the electronic structure of many-electron systems that naturally captures strong or nondynamic…

Chemical Physics · Physics 2024-06-19 Run R. Li , Marcus D. Liebenthal , A. Eugene DePrince

The discovery of two-dimensional (2D) van der Waals magnetic materials and their heterostructures provided an exciting platform for emerging phenomena with intriguing implications in information technology. Here, based on a multiscale…

Materials Science · Physics 2023-06-02 Nihad Abuawwad , Manuel dos Santos Dias , Hazem Abusara , Samir Lounis

A mean field model is presented for the configuration dependent effective demagnetizing and anisotropy fields in assemblies of exchange decoupled magnetic particles of arbitrary shape which are expressed in terms of the demagnetizing…

Mesoscale and Nanoscale Physics · Physics 2014-08-27 Juan Manuel Martinez-Huerta , Armando Encinas , Joaquin De La Torre Medina , Luc Piraux

One of the most important properties of soft functionalized magnetic composite materials in view of their technological potential is given by the magnetorheological effect. It describes the change in rheological properties such as the shear…

Soft Condensed Matter · Physics 2025-07-31 Lukas Fischer , Andreas M. Menzel

Transition metal dichalcogenides (TMDs) are interesting for understanding fundamental physics of two-dimensional materials (2D) as well as for many emerging technologies, including spin electronics. Here, we report the discovery of…

Numerical methods for modeling thin-film magnetization are primarily focused on computing the current density distribution. The highly nonlinear current-voltage characteristic of type-II superconductors significantly complicates the…

Superconductivity · Physics 2026-05-15 Leonid Prigozhin , Vladimir Sokolovsky

Hard/soft magnetic bilayer thin films have been widely used in data storage technologies and permanent magnet applications. The magnetic configuration and response to temperatures and magnetic fields in these heterostructures are considered…

Magnetomotive ultrasound (MMUS) using magnetic nanoparticle contrast agents has shown promise for thrombosis imaging and quantitative elastometry via magnetomotive resonant acoustic spectroscopy (MRAS). Young's modulus measurements of…

We examine and identify magnetoresistance mechanisms in 2D system containing a sizable concentration of magnetic ions. We argue that some of these mechanisms can serve as a tool to measure spin polarization. Lack of spin degeneracy and…

The harmonic product of tensors---leading to the concept of harmonic factorization---has been defined in a previous work (Olive et al, 2017). In the practical case of 3D crack density measurements on thin or thick walled structures, this…

Classical Physics · Physics 2019-04-25 Rodrigue Desmorat , Boris Desmorat , Marc Olive , Boris Kolev

In recent years, a new class of mixed finite elements -- compatible-strain mixed finite elements (CSMFEs) -- has emerged that uses the differential complex of nonlinear elasticity. Their excellent performance in benchmark problems, such as…

Numerical Analysis · Mathematics 2025-04-29 Mohsen Jahanshahi , Damiano Pasini , Arash Yavari

In solid mechanics, Data-driven approaches are widely considered as the new paradigm that can overcome the classic problems of constitutive models such as limiting hypothesis, complexity, and high dependence on training data. However,…

Soft Condensed Matter · Physics 2020-11-23 Aref Ghaderi , Vahid Morovati , Roozbeh Dargazany

Elasticity image, visualizing the quantitative map of tissue stiffness, can be reconstructed by solving an inverse problem. Classical methods for magnetic resonance elastography (MRE) try to solve a regularized optimization problem…

Image and Video Processing · Electrical Eng. & Systems 2021-05-28 Narges Mohammadi , Marvin M. Doyley , Mujdat Cetin

In this paper, five different approaches for reduced-order modeling of brittle fracture in geomaterials, specifically concrete, are presented and compared. Four of the five methods rely on machine learning (ML) algorithms to approximate…

Computational Engineering, Finance, and Science · Computer Science 2018-06-07 A. Hunter , B. A. Moore , M. K. Mudunuru , V. T. Chau , R. L. Miller , R. B. Tchoua , C. Nyshadham , S. Karra , D. O. Malley , E. Rougier , H. S. Viswanathan , G. Srinivasan

We propose a novel formulation of elastic materials based on high-order interpolants, which fits accurately complex elastic behaviors, but remains conservative. The proposed high-order interpolants can be regarded as a high-dimensional…

Computational Engineering, Finance, and Science · Computer Science 2023-03-07 Antoine Chan-Lock , Jesus Perez , Miguel Otaduy

We propose a mechanism for the recently reported destabilization by an in-plane magnetic field of the conducting phase of low density electrons in 2D. We apply our self-consistent approach based on the memory function formalism to the fully…

Strongly Correlated Electrons · Physics 2007-05-23 J. S. Thakur , D. Neilson

Solving complex partial differential equations is vital in the physical sciences, but often requires computationally expensive numerical methods. Reduced-order models (ROMs) address this by exploiting dimensionality reduction to create fast…

Machine Learning · Computer Science 2026-05-19 Robert Stephany , William Michael Anderson , Youngsoo Choi
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