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In this work, we report observations of phase transitions in 2D multistable mechanical metamaterials that are initiated by collisions of soliton-like pulses in the metamaterial. Analogous to first-order phase transitions in crystalline…

Pattern Formation and Solitons · Physics 2023-02-24 Weijian Jiao , Hang Shu , Vincent Tournat , Hiromi Yasuda , Jordan R. Raney

Van der Waals In$_2$Se$_3$ has garnered significant attention due to its unique properties and wide applications associated with its rich polymorphs and polymorphic phase transitions. Despite extensive studies, the vast complex polymorphic…

Materials Science · Physics 2025-06-27 Mingfeng Liu , Jiantao Wang , Peitao Liu , Qiang Wang , Zhibo Liu , Yan Sun , Xing-Qiu Chen

We develop a framework to understand the mechanics of metamaterial sheets on curved surfaces. Here we have constructed a continuum elastic theory of mechanical metamaterials by introducing an auxiliary, scalar gauge-like field that absorbs…

Soft Condensed Matter · Physics 2023-11-02 Sourav Roy , C. D. Santangelo

Biomolecular machines transduce between different forms of energy. These machines make directed progress and increase their speed by consuming free energy, typically in the form of nonequilibrium chemical concentrations. Machine dynamics…

Statistical Mechanics · Physics 2018-10-05 Aidan I Brown , David A Sivak

In many systems, nucleation of a stable solid may occur in the presence of other (often more than one) metastable phases. These may be polymorphic solids or even liquid phases. In such cases, nucleation of the solid phase from the melt may…

Materials Science · Physics 2013-04-08 Mantu Santra , Rakesh S. Singh , Biman Bagchi

This paper presents the analysis of metasurfaces, here called reconfigurable intelligent surface. The analysis is performed by numerical simulations that implement the finite-difference time-domain method. The metasurface has been modeled…

Applied Physics · Physics 2023-09-25 Emanuel Colella , Luca Bastianelli , Valter Mariani Primiani , Franco Moglie

Atomistic control of phase boundaries is crucial for optimizing the functional properties of solid-solution ferroelectrics, yet their microstructural mechanisms remain elusive. Here, we harness machine-learning-driven molecular dynamics to…

Materials Science · Physics 2025-05-09 Weiru Wen , Fan-Da Zeng , Ben Xu , Bi Ke , Zhipeng Xing , Hao-Cheng Thong , Ke Wang

Disentangling the mechanistic details of a chemical reaction pathway is a hard problem that often requires a considerable amount of chemical intuition and a component of luck. Experiments struggle in observing short-life metastable…

Chemical Physics · Physics 2019-08-01 Valerio Rizzi , Dan Mendels , Emilia Sicilia , Michele Parrinello

Efficient synthesis recipes are needed both to streamline the manufacturing of complex materials and to accelerate the realization of theoretically predicted materials. Oftentimes the solid-state synthesis of multicomponent oxides is…

Materials Science · Physics 2024-04-10 Jiadong Chen , Samuel R. Cross , Lincoln J. Miara , Jeong-Ju Cho , Yan Wang , Wenhao Sun

This study presents a computational framework to investigate and predict the complicated multiphase properties of eco-friendly lead-free piezoelectric materials, which are crucial for sustainable technological progress. Although their…

Quantum imaging employs the nonclassical correlation of photons to break through the noise limitation of classical imaging, realizing high sensitivity, high SNR imaging and multifunctional image processing. To enhance the flexibility and…

Machine learning is applied to investigate the phase transition of two-dimensional complex plasmas. The Langevin dynamics simulation is employed to prepare particle suspensions in various thermodynamic states. Based on the resulted particle…

Plasma Physics · Physics 2023-07-25 He Huang , Vladimir Nosenko , Han-Xiao Huang-Fu , Hubertus M. Thomas , Cheng-Ran Du

Non-imaging optical lenses can shape the light intensity from incoherent sources to a desired target intensity profile, which is important for applications in lighting, solar light concentration, and optical beam shaping. Their surface…

Atomistic or ab-initio molecular dynamics simulations are widely used to predict thermodynamics and kinetics and relate them to molecular structure. A common approach to go beyond the time- and length-scales accessible with such…

Atomistic modeling of solid-solid battery interfaces is essential for understanding electro-chemo-mechanical coupling, but the complex interfacial chemistry and heterogeneous environments pose major challenges for quantum-accurate,…

Materials Science · Physics 2026-01-27 Xiaoqing Liu , Xinyu Yu , Yangshuai Wang , Zhe-Tao Sun , Zedong Luo , Kehan Zeng , Teng Zhao , Shou-Hang Bo , Zhenli Xu

A `polydisperse' system has an infinite number of conserved densities. We give a rational procedure for projecting its infinite-dimensional free energy surface onto a subspace comprising a finite number of linear combinations of densities…

Statistical Mechanics · Physics 2007-05-23 Peter Sollich , Michael E Cates

Accurate free energy representations are crucial for understanding phase dynamics in materials. We employ a scale-bridging approach to incorporate atomistic information into our free energy model by training a neural network on DFT-informed…

Computational Physics · Physics 2025-03-12 Jamie Holber , Krishna Garikipati

Stochastic systems often exhibit multiple viable metastable states that are long-lived. Over very long timescales, fluctuations may push the system to transition between them, drastically changing its macroscopic configuration. In realistic…

Statistical Mechanics · Physics 2023-04-14 Tobias Grafke , Alessandro Laio

The adoption of detailed mechanisms for chemical kinetics often poses two types of severe challenges: First, the number of degrees of freedom is large; and second, the dynamics is characterized by widely disparate time scales. As a result,…

Dynamical Systems · Mathematics 2025-10-01 Eliodoro Chiavazzo , C. William Gear , Carmeline J. Dsilva , Neta Rabin , Ioannis G. Kevrekidis

Various methods going beyond density-functional theory (DFT), such as DFT+U, hybrid functionals, meta-GGAs, GW, and DFT-embedded dynamical mean field theory (eDMFT), have been developed to describe the electronic structure of correlated…

Strongly Correlated Electrons · Physics 2020-07-16 Subhasish Mandal , Kristjan Haule , Karin M. Rabe , David Vanderbilt