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Temperature evolution of dielectric response, atomic structure, and lattice dynamics in thin film of sodium niobate in the epitaxial NaNbO$_3$/SrRuO$_3$/(001)MgO heterostructure is studied by dielectric measurements, x-ray diffraction, and…

We explore the possibility to perform an in-situ transmission electron microscopy (TEM) thermoelectric characterization of materials. A differential heating element on a custom in-situ TEM microchip allows to generate a temperature gradient…

Materials Science · Physics 2025-01-14 Simon Hettler , Mohammad Furqan , Andres Sotelo , Raul Arenal

Ferroelectric domain nucleation and growth in multiferroic BiFeO3 films is observed directly by applying a local electric field with a conductive tip inside a scanning transmission electron microscope. The nucleation and growth of a…

Data-driven modeling and control of temperature dynamics in mechatronics systems and industrial processes are challenging control engineering problems. This is mainly because the temperature dynamics is inherently infinite-dimensional,…

Systems and Control · Electrical Eng. & Systems 2019-08-08 Aleksandar Haber

This paper proposes a physical-statistical modeling approach for spatio-temporal data arising from a class of stochastic convection-diffusion processes. Such processes are widely found in scientific and engineering applications where…

Applications · Statistics 2020-08-07 Xiao Liu , Kyongmin Yeo , Siyuan Lu

Transmission Electron Microscopy (TEM) is a powerful tool for imaging material structure and characterizing material chemistry. Recent advances in data collection technology for TEM have enabled high-volume and high-resolution data…

Computer Vision and Pattern Recognition · Computer Science 2021-08-24 Josh Kacher , Yao Xie , Sven P. Voigt , Shixiang Zhu , Henry Yuchi , Jordan Key , Surya R. Kalidindi

Simulating finite temperature phase transitions from first-principles is computationally challenging. Recently, molecular dynamics (MD) simulations using machine-learned force fields (MLFFs) have opened a new avenue for finite-temperature…

This tutorial investigates the convergence of statistical mechanics and learning theory, elucidating the potential enhancements in machine learning methodologies through the integration of foundational principles from physics. The tutorial…

Machine Learning · Computer Science 2024-11-26 Star , Liu

Thermodynamic conventions suffer from describing dynamical distinctions, especially when the structural and energetic changes induced by localized rare events are insignificant. By using the ensemble theory in the trajectory space, we…

Statistical Mechanics · Physics 2023-03-30 Qi-Jun Ye , Xin-Zheng Li

We study the static and dynamical properties of DNA in the vicinity of its melting transition, i.e. the separation of the two strands upon heating. The investigation is based on a simple mechanical model which includes the helicoidal…

Statistical Mechanics · Physics 2007-06-19 Maria Barbi , Stefano Lepri , Michel Peyrard , Nikos Theodorakopoulos

Polarization switching mechanisms in ferroelectric materials are fundamentally linked to local domain structure and presence of the structural defects, which both can act as nucleation and pinning centers and create local electrostatic and…

Disordered Systems and Neural Networks · Physics 2021-02-02 Sergei V. Kalinin , Kyle Kelley , Rama K. Vasudevan , Maxim Ziatdinov

Upon intense femtosecond photo-excitation, a many-body system can undergo a phase transition through a non-equilibrium route, but understanding these pathways remains an outstanding challenge. Here, we use time-resolved second harmonic…

Using simulations or experiments performed at some set of temperatures to learn about the physics or chemistry at some other arbitrary temperature is a problem of immense practical and theoretical relevance. Here we develop a framework…

Statistical Mechanics · Physics 2022-10-17 Yihang Wang , Lukas Herron , Pratyush Tiwary

Machine learning has been establishing its potential in multiple areas of condensed matter physics and materials science. Here we develop and use an unsupervised machine learning workflow within a framework of first-principles-based…

Materials Science · Physics 2023-01-02 Adriana Ladera , Ravi Kashikar , S. Lisenkov , I. Ponomareva

Diffuse optical imaging (DOI) offers valuable insights into scattering mediums, but the quest for high-resolution imaging often requires dense sampling strategies, leading to higher imaging errors and lengthy acquisition times. This work…

Optics · Physics 2025-04-07 Ben Wiesel , Shlomi Arnon

Dynamical system properties give rise to effects in Statistical Mechanics. Topological index changes can be the basis for phase transitions. The Euler characteristic is a versatile topological invariant that can be evaluated for model…

Statistical Mechanics · Physics 2007-05-23 Ajay Patwardhan

We use molecular dynamics simulations to understand the mechanisms of polarization switching in ferroelectric BaTiO$_3$ achieved with external electric field. For tetragonal and orthorhombic ferroelectric phases, we determine the switching…

Materials Science · Physics 2009-11-13 Jaita Paul , Takeshi Nishimatsu , Yoshiyuki Kawazoe , Umesh V. Waghmare

Nanoconfined liquid crystals (LCs) and their nanocomposites are driving the next generation of photonic applications. Consequently, deepening our understanding of mesophase stability, defect topology, and the dynamic response of LCs at the…

Stochastic thermodynamics lays down a broad framework to revisit the venerable concepts of heat, work and entropy production for individual stochastic trajectories of mesoscopic systems. Remarkably, this approach, relying on stochastic…

Statistical Mechanics · Physics 2023-01-31 David Guéry-Odelin , Christopher Jarzynski , Carlos A. Plata , Antonio Prados , Emmanuel Trizac

Thermodynamic phase transitions, a central concept in physics and chemistry, are typically controlled by an interplay of enthalpic and entropic contributions. In most cases, the estimation of the enthalpy in simulations is straightforward…

Soft Condensed Matter · Physics 2025-10-30 Yamin Ben-Shimon , Barak Hirshberg , Yohai Bar-Sinai
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