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Energy Associated With a Charge Distribution01:21

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The work done to bring a charge through a distance r is given by the potential difference between the initial and the final position. To assemble a collection of point charges, the total work done can be expressed in terms of the product of each pair of charges divided by their separation distance, defined with respect to a suitable origin. Solving this expression gives the energy stored in a point charge distribution.
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In an atom, the negatively charged electrons are attracted to the positively charged nucleus. In a multielectron atom, electron-electron repulsions are also observed. The attractive and repulsive forces are dependent on the distance between the particles, as well as the sign and magnitude of the charges on the individual particles. When the charges on the particles are opposite, they attract each other. If both particles have the same charge, they repel each other.
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Energy Diagrams - I01:14

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The dynamics of a mechanical system can be easily understood by interpreting a potential energy diagram. Since energy is a scalar quantity, the interpretation of the dynamics of the system becomes even simpler.
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Anyone who has used a microwave oven knows there is energy in electromagnetic waves. Sometimes, this energy is obvious, such as in the summer sun's warmth. At other times, it is subtle, such as the unfelt energy of gamma rays, which can destroy living cells. Electromagnetic waves bring energy into a system through their electric and magnetic fields. These fields can exert forces and move charges in the system and, thus, do work on them. However, there is energy in an electromagnetic wave,...
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Related Experiment Video

Updated: Jan 6, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

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Analytical energy gradient for the embedded cluster density approximation.

Chen Huang1

  • 1Department of Scientific Computing, Materials Science and Engineering Program, and National High Magnetic Field Laboratory, Florida State University, Tallahassee, Florida 32306, USA.

The Journal of Chemical Physics
|October 10, 2019
PubMed
Summary
This summary is machine-generated.

We developed a variational embedded cluster density approximation (ECDA) for faster density functional theory calculations. This new method enables analytical energy gradients, improving computational efficiency for electronic structure problems.

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Last Updated: Jan 6, 2026

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Materials Science

Background:

  • Kohn-Sham (KS) density functional theory (DFT) is computationally intensive, especially with high-level exchange-correlation (XC) functionals.
  • The previous Embedded Cluster Density Approximation (ECDA) offered a way to scale up KS-DFT but lacked variationality, hindering analytical energy gradient calculations.
  • Variational methods are crucial for accurate geometry optimization and understanding molecular properties.

Purpose of the Study:

  • To introduce a fully variational formulation of the Embedded Cluster Density Approximation (ECDA).
  • To derive the analytical energy gradient for the variational ECDA method.
  • To enable efficient and accurate geometry optimizations in electronic structure calculations.

Main Methods:

  • Developed a variational formulation of ECDA by addressing the Optimized Effective Potential (OEP) problems in density partitioning and potential solving.
  • Regularized the OEP equations to maintain variationality within the ECDA framework.
  • Utilized KS linear responses, calculated via the Sternheimer equation, for XC potential and analytical gradient computations.

Main Results:

  • Successfully derived the analytical energy gradient for the variational ECDA.
  • Validated the analytical energy gradients using a Si2H6 molecule.
  • Applied the method to perform geometry relaxation for a Si6H10 molecule, demonstrating its practical utility.

Conclusions:

  • The new variational ECDA formulation overcomes the limitations of the previous non-variational approach.
  • The derived analytical energy gradients significantly enhance the efficiency of electronic structure calculations.
  • This work paves the way for applying high-level XC functionals in large-scale DFT simulations with improved accuracy and speed.