Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

122
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
122
Dynamic Equilibrium02:20

Dynamic Equilibrium

56.9K
A reversible chemical reaction represents a chemical process that proceeds in both forward (left to right) and reverse (right to left) directions. When the rates of the forward and reverse reactions are equal, the concentrations of the reactant and product species remain constant over time and the system is at equilibrium. A special double arrow is used to emphasize the reversible nature of the reaction. The relative concentrations of reactants and products in equilibrium systems vary greatly;...
56.9K
Phase Transitions02:31

Phase Transitions

20.9K
Whether solid, liquid, or gas, a substance's state depends on the order and arrangement of its particles (atoms, molecules, or ions). Particles in the solid pack closely together, generally in a pattern. The particles vibrate about their fixed positions but do not move or squeeze past their neighbors. In liquids, although the particles are closely spaced, they are randomly arranged. The position of the particles are not fixed—that is, they are free to move past their neighbors to...
20.9K
Phase Transitions: Sublimation and Deposition02:33

Phase Transitions: Sublimation and Deposition

18.4K
Some solids can transition directly into the gaseous state, bypassing the liquid state, via a process known as sublimation. At room temperature and standard pressure, a piece of dry ice (solid CO2) sublimes, appearing to gradually disappear without ever forming any liquid. Snow and ice sublimate at temperatures below the melting point of water, a slow process that may be accelerated by winds and the reduced atmospheric pressures at high altitudes. When solid iodine is warmed, the solid sublimes...
18.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Correction to "Online Mass Spectrometry Investigation of SEI Formation on Carbon Electrode Surfaces in Sodium-Ion Batteries: Oxygen and Additive Effects".

ACS applied energy materials·2026
Same author

Recurrent convolutional neural networks for modeling nonadiabatic dynamics of quantum-classical systems.

Physical review. E·2026
Same author

Echo state network for coarsening dynamics of charge density waves.

Physical review. E·2026
Same author

Robust calibration and quantification of FRET signals using multiplexed biosensor barcoding.

iScience·2025
Same author

Gapless dispersive continuum in a modulated quantum kagome antiferromagnet.

Nature communications·2025
Same author

Calibration of FRET-based biosensors using multiplexed biosensor barcoding.

bioRxiv : the preprint server for biology·2024

Related Experiment Video

Updated: Oct 16, 2025

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

3.3K

Arrested Phase Separation in Double-Exchange Models: Large-Scale Simulation Enabled by Machine Learning.

Puhan Zhang1, Gia-Wei Chern1

  • 1Department of Physics, University of Virginia, Charlottesville, Virginia 22904, USA.

Physical Review Letters
|October 15, 2021
PubMed
Summary
This summary is machine-generated.

Electronic phase separation dynamics were simulated using deep-learning potentials. Correlation-induced freezing arrested phase separation by self-trapping holes, impacting colossal magnetoresistance materials.

More Related Videos

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.3K
Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids
08:04

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids

Published on: May 27, 2020

8.6K

Related Experiment Videos

Last Updated: Oct 16, 2025

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

3.3K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.3K
Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids
08:04

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids

Published on: May 27, 2020

8.6K

Area of Science:

  • Condensed Matter Physics
  • Computational Materials Science
  • Statistical Mechanics

Background:

  • Electronic phase separation is crucial for understanding materials with colossal magnetoresistance (CMR).
  • The single-band double-exchange model provides a framework for studying such phenomena.
  • Simulating these dynamics requires accurate interatomic potentials.

Purpose of the Study:

  • To investigate the dynamics of electronic phase separation in the single-band double-exchange model.
  • To explore the role of correlations and magnetic ordering in phase separation.
  • To understand the mechanism behind arrested phase separation.

Main Methods:

  • Large-scale dynamical simulations employing deep-learning neural-network potentials.
  • Neural-network potentials trained using exact diagonalization solutions for small system sizes.
  • Analysis of hole dynamics, ferromagnetic cluster formation, and spin-spin correlations.

Main Results:

  • Observed correlation-induced freezing behavior during phase separation.
  • Identified stabilization of hole aggregation via ferromagnetic clusters (Hund's coupling).
  • Discovered premature disruption of cluster growth by self-trapped holes due to antiferromagnetic correlations, leading to arrested phase separation.

Conclusions:

  • The study reveals a novel mechanism for arrested phase separation driven by electron-hole correlations.
  • Findings offer insights into the complex dynamics governing phase separation in CMR materials.
  • Deep-learning potentials enable accurate simulations of large-scale correlated electron systems.