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Equilibrium Conditions for a Particle01:23

Equilibrium Conditions for a Particle

When an object is in equilibrium, it is either at rest or moving with a constant velocity. There are two types of equilibrium: static and dynamic. Static equilibrium occurs when an object is at rest, while dynamic equilibrium occurs when an object is moving with a constant velocity. In both cases, there must be a balance of forces acting on the object.
To understand the concept of equilibrium, let us first consider the forces acting on an object. When different forces act on an object, they can...
Gibbs Free Energy02:39

Gibbs Free Energy

One of the challenges of using the second law of thermodynamics to determine if a process is spontaneous is that it requires measurements of the entropy change for the system and the entropy change for the surroundings. An alternative approach involving a new thermodynamic property defined in terms of system properties only was introduced in the late nineteenth century by American mathematician Josiah Willard Gibbs. This new property is called the Gibbs free energy (G) (or simply the free...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...
Reaction Mechanisms: The Steady-State Approximation01:26

Reaction Mechanisms: The Steady-State Approximation

The steady-state approximation, also referred to as the quasi-steady-state approximation to differentiate it from a true steady state, is a widely used method for simplifying calculations in complex reaction mechanisms. This approach is particularly useful when dealing with multi-step reactions that involve reverse reactions or several steps, which can significantly increase mathematical complexity and make the reactions nearly unsolvable analytically.The steady-state approximation operates on...
Homogeneous Equilibria for Gaseous Reactions02:15

Homogeneous Equilibria for Gaseous Reactions

Homogeneous Equilibria for Gaseous Reactions
For gas-phase reactions, the equilibrium constant may be expressed in terms of either the molar concentrations (Kc) or partial pressures (Kp) of the reactants and products. A relation between these two K values may be simply derived from the ideal gas equation and the definition of molarity. According to the ideal gas equation:
Fermi Level Dynamics01:12

Fermi Level Dynamics

The vacuum level denotes the energy threshold required for an electron to escape from a material surface. It is usually positioned above the conduction band of a semiconductor and acts as a benchmark for comparing electron energies within various materials.
Electron affinity in semiconductors refers to the energy gap between the minimum of its conduction band and the vacuum level and it is a critical parameter in determining how easily a semiconductor can accept additional electrons.
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Updated: Jul 15, 2026

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

Non-Hamiltonian molecular dynamics implementation of the Gibbs ensemble method. I. Algorithm.

Christoph Bratschi1, Hanspeter Huber

  • 1Departement Chemie, Universität Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland.

The Journal of Chemical Physics
|May 5, 2007
PubMed
Summary

This study introduces a novel Gibbs ensemble molecular dynamics algorithm for simulating liquid-vapor coexistence. The method accurately samples probability densities and generates correct exchange probabilities for molecular systems.

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Area of Science:

  • Chemical Physics
  • Computational Chemistry
  • Thermodynamics

Background:

  • Accurate simulation of liquid-vapor coexistence is crucial for understanding phase transitions.
  • Existing molecular dynamics methods face challenges in simulating phase equilibria efficiently.

Purpose of the Study:

  • To introduce and validate a new Gibbs ensemble molecular dynamics algorithm.
  • To apply the algorithm to determine the liquid-vapor coexistence curve of CO2.

Main Methods:

  • Development of a Gibbs ensemble molecular dynamics algorithm using non-Hamiltonian techniques.
  • Implementation of the extended system Nose-Hoover formalism for constant temperature and pressure.
  • Utilizing single particle transfers between subsystems to achieve equal chemical potentials.

Main Results:

  • The developed algorithm correctly samples the desired probability density functions.
  • The method generates accurate exchange probabilities between subsystems.
  • The algorithm is shown to be effective for simulating liquid-vapor coexistence.

Conclusions:

  • The new Gibbs ensemble molecular dynamics algorithm provides a robust method for studying liquid-vapor coexistence.
  • This approach enables accurate determination of phase diagrams for various molecular systems.
  • The algorithm lays the groundwork for future simulations of complex fluid phases.