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

397
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...
397
Biasing of Metal-Semiconductor Junctions01:27

Biasing of Metal-Semiconductor Junctions

810
Biasing metal-semiconductor junctions involves applying a voltage across the junction. Specifically, the metal is connected to a voltage source, while the semiconductor is grounded. This technique is essential for controlling the direction and magnitude of current flow in electronic devices, including diodes, transistors, and photovoltaic cells.
In Schottky junctions, where the semiconductor is n-type, applying a positive voltage to the metal relative to the semiconductor reduces its Fermi...
810
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.6K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.6K
Atomic Absorption Spectroscopy: Atomization Methods01:25

Atomic Absorption Spectroscopy: Atomization Methods

1.9K
Atomic Absorption Spectroscopy (AAS) atomizes samples through flame atomization or electrothermal atomization. Flame atomization typically involves a nebulizer and spray chamber assembly to combine the sample with a fuel–oxidant mixture, creating a fine aerosol mist that enters a burner. Typically, the fuel and oxidant are combined in an approximately stoichiometric ratio. However, for atoms that are easily oxidized, a fuel-rich mixture may be more advantageous. Only about 5% of the...
1.9K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.4K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.4K
Load-frequency control01:28

Load-frequency control

785
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
785

You might also read

Related Articles

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

Sort by
Same author

Correction to "Tuning the Directional Solubility of Ionic Liquids through Multicomponent Ions for Low-Temperature Desalination".

Journal of the American Chemical Society·2026
Same author

Excess entropy scaling explains the enhanced dynamics of the ionic liquid 1-ethyl-3-methylimidazolium chloride in external electric fields.

Physical chemistry chemical physics : PCCP·2025
Same author

Monte Carlo methods, 70 years after "Equation of state calculations by fast computing machines" by Nicholas Metropolis, Arianna Rosenbluth, Marshall Rosenbluth, Augusta Teller, and Edward Teller (1953).

The Journal of chemical physics·2025
Same author

Assessing Polymorph Stability and Phase Transitions at Finite Temperature: Integrating Crystal Structure Prediction, Lattice Dynamics, and Molecular Dynamics.

Journal of chemical theory and computation·2025
Same author

Structure, dynamics, and electrochemistry of choline chloride/ethylene glycol eutectic solvents at an electrode surface explored by molecular dynamics simulations.

The Journal of chemical physics·2025
Same author

Structure and dynamics of water-in-salt LiTFSI electrolytes from first-principles molecular dynamics simulations.

The Journal of chemical physics·2025

Related Experiment Video

Updated: Mar 29, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

13.5K

Continuous Fractional Component Monte Carlo:  An Adaptive Biasing Method for Open System Atomistic Simulations.

Wei Shi1, Edward J Maginn1

  • 1Department of Chemical and Biomolecular Engineering, University of Notre Dame, 182 Fitzpatrick Hall, Notre Dame, Indiana 46556-5637.

Journal of Chemical Theory and Computation
|December 4, 2015
PubMed
Summary

A novel Monte Carlo method efficiently inserts and deletes molecules using a coupling parameter and bias potential. This simulation technique accurately predicts fluid properties and phase behavior.

More Related Videos

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

2.3K
Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function
05:57

Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function

Published on: April 26, 2024

965

Related Experiment Videos

Last Updated: Mar 29, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

13.5K
Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

2.3K
Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function
05:57

Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function

Published on: April 26, 2024

965

Area of Science:

  • Computational Chemistry
  • Statistical Mechanics
  • Molecular Simulation

Background:

  • Traditional Monte Carlo methods face challenges with molecule insertion and deletion.
  • Open system molecular dynamics and expanded ensemble Monte Carlo offer partial solutions.
  • Accurate simulation of chemical potential and phase equilibria is crucial for materials science.

Purpose of the Study:

  • To introduce a new open system Monte Carlo procedure addressing insertion/deletion difficulties.
  • To apply the method to grand canonical and osmotic ensembles.
  • To validate the method's accuracy for volumetric properties and phase behavior.

Main Methods:

  • Developed a Monte Carlo procedure with gradual molecule insertion/deletion.
  • Utilized a continuous coupling parameter and an adaptive bias potential.
  • Applied the technique to Lennard-Jones fluid, water, and a CO2-ethanol binary system.

Main Results:

  • The method successfully overcomes insertion and deletion challenges in Monte Carlo simulations.
  • Accurate prediction of volumetric properties for Lennard-Jones fluid and water.
  • Correctly reproduced the phase behavior of the CO2-ethanol binary system.

Conclusions:

  • The new open system Monte Carlo procedure is a robust and accurate simulation technique.
  • It offers a significant improvement for systems requiring variable particle numbers.
  • The method is applicable to diverse systems, including mixtures and different ensembles.