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

Electrostatic Boundary Conditions in Dielectrics01:27

Electrostatic Boundary Conditions in Dielectrics

1.3K
When an electric field passes from one homogeneous medium to another, crossing the boundary between the two mediums imparts a discontinuity in the electric field. This results in electrostatic boundary conditions that depend on the type of mediums the field propagates through.
Consider a case where both the mediums across a boundary are two different dielectric materials. Recall that the electric field and electric displacement are proportional and related through the material's...
1.3K
Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

1.0K
Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...
1.0K
Valence Bond Theory and Hybridized Orbitals02:38

Valence Bond Theory and Hybridized Orbitals

19.7K
According to valence bond theory, a covalent bond results when: (1) an orbital on one atom overlaps an orbital on a second atom, and (2) the single electrons in each orbital combine to form an electron pair. The strength of a covalent bond depends on the extent of overlap of the orbitals involved. Maximum overlap is possible when the orbitals overlap on a direct line between the two nuclei.
A σ bond (single bond in a Lewis structure) is a covalent bond in which the electron density is...
19.7K
Thermodynamic Potentials01:26

Thermodynamic Potentials

911
Thermodynamic potentials are state functions that are extremely useful in analyzing a thermodynamic system. They have dimensions of energy. The four important thermodynamic potentials are internal energy, enthalpy, Helmholtz free energy, and Gibbs free energy. These thermodynamic potentials can be expressed using two of the following variables: pressure, volume, temperature, and entropy. These two variables are expressed as the rate of change of the thermodynamic potential with respect to other...
911
Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

589
Passive diffusion is a critical process that allows small lipophilic drugs to cross the cell membrane along a concentration gradient. This mechanism's efficiency depends on four primary factors: the membrane's surface area, the drug's lipid-water partition coefficient, the concentration gradient, and the membrane's thickness.
When administered orally, drugs establish a substantial concentration gradient between the gastrointestinal (GI) lumen and the bloodstream, expediting...
589
Van der Waals Equation01:10

Van der Waals Equation

4.3K
The ideal gas law is an approximation that works well at high temperatures and low pressures. The van der Waals equation of state (named after the Dutch physicist Johannes van der Waals, 1837−1923) improves it by considering two factors.
First, the attractive forces between molecules, which are stronger at higher densities and reduce the pressure, are considered by adding to the pressure a term equal to the square of the molar density multiplied by a positive coefficient a. Second, the volume...
4.3K

You might also read

Related Articles

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

Sort by
Same author

Breaking the upper limit of innovation: China's dual-track regulatory framework for emerging biomedical innovations.

Innovation (Cambridge (Mass.))·2026
Same author

Realization of the Bienenstock-Cooper-Munro rule in a single memristor.

Nature communications·2026
Same author

Hydrogen reduced interstitial-vacancy cluster recombination in metals.

Nature communications·2026
Same author

SIRT6 enhances the therapeutic potential of extracellular vesicles in mitigating osteoarthritis in rat models.

Stem cell research & therapy·2026
Same author

Molecular Diagnostic Yield of Exome Sequencing and Genome Sequencing in Critical Ill Neonates and Infants: A Systematic Review and Meta-Analysis.

Genetics in medicine : official journal of the American College of Medical Genetics·2026
Same author

Non-Arrhenius threshold switching by field-driven dipolar ordering.

Nature communications·2026

Related Experiment Video

Updated: Aug 9, 2025

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid
08:54

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid

Published on: January 25, 2020

5.7K

Oxygen Vacancy Diffusion in Rutile TiO2: Insight from Deep Neural Network Potential Simulations.

Zhihong Wu1, Wen-Jin Yin2, Bo Wen3

  • 1Key Laboratory for Special Functional Materials of Ministry of Education, School of Materials Science and Engineering, Henan University, Kaifeng 475004, China.

The Journal of Physical Chemistry Letters
|February 22, 2023
PubMed
Summary
This summary is machine-generated.

Machine learning potentials accurately simulate titanium dioxide (TiO2) defects, revealing oxygen vacancy stability and diffusion mechanisms at the nanoscale. This accelerates understanding of surface reactions with DFT-level accuracy.

More Related Videos

Tuning Oxide Properties by Oxygen Vacancy Control During Growth and Annealing
06:44

Tuning Oxide Properties by Oxygen Vacancy Control During Growth and Annealing

Published on: June 9, 2023

3.2K
Electric-field Control of Electronic States in WS2 Nanodevices by Electrolyte Gating
10:36

Electric-field Control of Electronic States in WS2 Nanodevices by Electrolyte Gating

Published on: April 12, 2018

11.6K

Related Experiment Videos

Last Updated: Aug 9, 2025

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid
08:54

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid

Published on: January 25, 2020

5.7K
Tuning Oxide Properties by Oxygen Vacancy Control During Growth and Annealing
06:44

Tuning Oxide Properties by Oxygen Vacancy Control During Growth and Annealing

Published on: June 9, 2023

3.2K
Electric-field Control of Electronic States in WS2 Nanodevices by Electrolyte Gating
10:36

Electric-field Control of Electronic States in WS2 Nanodevices by Electrolyte Gating

Published on: April 12, 2018

11.6K

Area of Science:

  • Materials Science
  • Computational Chemistry
  • Surface Science

Background:

  • Defects significantly influence titanium dioxide (TiO2) surface properties and reactivity.
  • Understanding defect behavior is crucial for electronic and catalytic applications of TiO2.

Purpose of the Study:

  • To develop and validate machine learning potentials for simulating defective TiO2 surfaces.
  • To investigate the stability and diffusion dynamics of oxygen vacancies in TiO2.

Main Methods:

  • Trained deep neural network potentials (DPs) using active learning on ab initio data.
  • Validated DPs against density functional theory (DFT) for accuracy.
  • Performed nanosecond-scale molecular dynamics simulations using DPs.

Main Results:

  • DPs demonstrated good consistency with DFT results.
  • Oxygen vacancies were found to be stable at 330 K but converted to more favorable sites at 500 K.
  • DP-predicted oxygen vacancy diffusion barriers matched DFT predictions.

Conclusions:

  • Machine learning potentials offer a DFT-accurate and accelerated approach for molecular dynamics simulations.
  • This method enhances the understanding of microscopic mechanisms in fundamental TiO2 surface reactions.