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Related papers: Nonlinear Dynamic Force Spectroscopy

200 papers

The common approach to crack dynamics, linear elastic fracture mechanics (LEFM), assumes infinitesimal strains and predicts a $r^{-1/2}$ strain divergence at a crack tip. We extend this framework by deriving a weakly nonlinear fracture…

Materials Science · Physics 2009-11-13 Eran Bouchbinder , Ariel Livne , Jay Fineberg

Ab initio modeling of dynamic structure factors (DSF) and related density response properties in the warm dense matter (WDM) regime is a challenging computational task. The DSF, convolved with a probing X-ray beam and instrument function,…

Deep Feedback Models (DFMs) are a new class of stateful neural networks that combine bottom up input with high level representations over time. This feedback mechanism introduces dynamics into otherwise static architectures, enabling DFMs…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 David Calhas , Arlindo L. Oliveira

Dynamic density functional theory (DDFT) is a promising approach for predicting the structural evolution of a drying suspension containing one or more types of colloidal particles. The assumed free-energy functional is a key component of…

Soft Condensed Matter · Physics 2022-11-23 Mayukh Kundu , Michael P. Howard

The concept of nonlinear modes is useful for the dynamical characterization of nonlinear mechanical systems. While efficient and broadly applicable methods are now available for the computation of nonlinear modes, nonlinear modal testing is…

Systems and Control · Electrical Eng. & Systems 2020-11-18 Maren Scheel , Simon Peter , Remco I. Leine , Malte Krack

This paper aims at a comprehensive understanding on the novel elastic property of double-stranded DNA (dsDNA) discovered very recently through single-molecule manipulation techniques. A general elastic model for double-stranded biopolymers…

Soft Condensed Matter · Physics 2009-10-31 Haijun Zhou , Yang Zhang , Zhong-can Ou-Yang

An accurate force field is the key to the success of all molecular mechanics simulations on organic polymers and biomolecules. Accuracy beyond density functional theory is often needed to describe the intermolecular interactions, while most…

Chemical Physics · Physics 2021-08-13 Xufei Wang , Yuanda Xu , Han Zheng , Kuang Yu

Modern spectroscopic databases provide a wealth of information about the physical processes and environments associated with astrophysical populations. Techniques such as blind source separation (BSS), in which sets of spectra are…

Astrophysics · Physics 2009-11-13 James T. Allen , Paul C. Hewett , Vasily Belokurov , Vivienne Wild

Nonlinear stiffening is a ubiquitous property of major types of biopolymers that make up the extracellular matrices (ECM) including collagen, fibrin and basement membrane. Within the ECM, many types of cells such as fibroblasts and cancer…

To calculate static response properties of a many body system, local density approximation (LDA) can be safely applied. But applicability of LDA is limited for the case of dynamical response functions since dynamics of the system needs to…

Quantum Gases · Physics 2015-12-01 Sudeep Kumar Ghosh

We introduce the notion, and develop the theory of local-noise spectroscopy (LNS) - a tool to study the properties of systems far from equilibrium by means of flux density correlations. As a test bed, we apply it to biased molecular…

Mesoscale and Nanoscale Physics · Physics 2019-02-11 Gabriel Cabra , Massimiliano Di Ventra , Michael Galperin

We review the screening nature and many-body physics foundation of the van der Waals density functional (vdW-DF) method, a systematic approach to construct truly nonlocal exchange-correlation energy density functionals. To that end we…

Materials Science · Physics 2021-12-30 Per Hyldgaard , Yang Jiao , Vivekanand Shukla

Classical dynamical density functional theory (DDFT) has become one of the central modeling approaches in nonequilibrium soft matter physics. Recent years have seen the emergence of novel and interesting fields of application for DDFT. In…

Soft Condensed Matter · Physics 2023-03-21 Michael te Vrugt , Raphael Wittkowski

Detrended fluctuation analysis (DFA) is a scaling analysis method used to quantify long-range power-law correlations in signals. Many physical and biological signals are ``noisy'', heterogeneous and exhibit different types of…

Data Analysis, Statistics and Probability · Physics 2009-11-07 Zhi Chen , Plamen Ch. Ivanov , Kun Hu , H. Eugene Stanley

In this study the possibility of combining commercial Scanning Force Microscopes (SFM) with stretching devices for the investigation of microscopic surface changes during stepwise elongation is investigated. Different types of stretching…

Soft Condensed Matter · Physics 2013-12-11 Sabine Hild , Armin Rosa , Othmar Marti

We present a unified theory for the longitudinal dynamic response of a stiff polymer in solution to various external perturbations (mechanical excitations, hydrodynamic flows, electrical fields, temperature quenches ...) that can be…

Soft Condensed Matter · Physics 2007-05-23 Oskar Hallatschek , Erwin Frey , Klaus Kroy

Single-molecule force-extension experiments have allowed quantitative measurements of the mechanical responses of biomolecules to applied forces explaining their roles in key biological functions. Electrophoretic stretching of charged…

Soft Condensed Matter · Physics 2024-02-21 Ananya Mondal , Greg Morrison

We investigate Machine-Learned Force Fields (MLFFs) trained on approximate Density Functional Theory (DFT) and Coupled Cluster (CC) level potential energy surfaces for the carbon diamond and lithium hydride solids. We assess the accuracy…

We reexamine results obtained with the recently proposed density functional theory framework based on forces (force-DFT) [Tschopp et al., Phys. Rev. E 106, 014115 (2022)]. We compare inhomogeneous density profiles for hard sphere fluids to…

Soft Condensed Matter · Physics 2024-02-28 Florian Sammüller , Sophie Hermann , Matthias Schmidt

Model-based reinforcement learning is a powerful tool, but collecting data to fit an accurate model of the system can be costly. Exploring an unknown environment in a sample-efficient manner is hence of great importance. However, the…

Machine Learning · Computer Science 2023-04-27 Matthieu Blanke , Marc Lelarge