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Related Concept Videos

Molecular Orbital Theory I02:35

Molecular Orbital Theory I

Overview of Molecular Orbital Theory
MO Theory and Covalent Bonding02:40

MO Theory and Covalent Bonding

The molecular orbital theory describes the distribution of electrons in molecules in a manner similar to the distribution of electrons in atomic orbitals. The region of space in which a valence electron in a molecule is likely to be found is called a molecular orbital. Mathematically, the linear combination of atomic orbitals (LCAO) generates molecular orbitals. Combinations of in-phase atomic orbital wave functions result in regions with a high probability of electron density, while...
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Molecular Orbital Energy Diagrams
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Molecular Geometry and Dipole Moments

The VSEPR theory can be used to determine the electron pair geometries and molecular structures as follows:
The Van der Waals Equation01:26

The Van der Waals Equation

The ideal gas law is based on two simplifying assumptions: first, that there are no intermolecular attractions between gas molecules, and second, that the volume occupied by the molecules themselves is negligible compared with the volume of the container. However, these assumptions don't hold up under all conditions - specifically, at high pressures and low temperatures, as gas tends to deviate from ideal gas behavior.The van der Waals equation is an enhanced version of the ideal gas law,...
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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...

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Related Experiment Video

Updated: Jun 3, 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

Time dependent density functional theory with DMol3.

B Delley1

  • 1Paul Scherrer Institute Switzerland, CH-5232 Villigen, Switzerland.

Journal of Physics. Condensed Matter : an Institute of Physics Journal
|March 10, 2011
PubMed
Summary
This summary is machine-generated.

Time-dependent density functional theory (TDDFT) calculations are now feasible with the DMol(3) program, offering efficient and parallelized computations. This implementation accurately predicts atomic multiplets, UV-vis spectra, and excited-state dynamics.

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Last Updated: Jun 3, 2026

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Published on: April 12, 2019

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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Materials Science

Background:

  • Density Functional Theory (DFT) is a powerful method for electronic structure calculations.
  • Time-dependent DFT (TDDFT) extends DFT to study excited states and dynamic properties.
  • Efficient implementation of TDDFT is crucial for broader applicability.

Purpose of the Study:

  • To implement Time-dependent Density Functional Theory (TDDFT) within the DMol(3) program.
  • To assess the computational efficiency and scalability of the TDDFT implementation.
  • To demonstrate the predictive capabilities of the new TDDFT implementation through diverse applications.

Main Methods:

  • Local atomic orbital implementation of DFT.
  • Development and integration of TDDFT algorithms into the DMol(3) software.
  • Parallel computing for enhanced performance.
  • Application to specific chemical systems including transition metal ions, organic molecules, and reaction dynamics.

Main Results:

  • Successful implementation of TDDFT in DMol(3).
  • TDDFT calculation times are comparable to standard DFT-Self Consistent Field (SCF) calculations.
  • The implementation is fully parallelized, enabling efficient computations.
  • Accurate prediction of atomic multiplets for Ti(4+).
  • Simulation of UV-Vis spectra for aromatic organic molecules.
  • Mapping of excited-state potential energy surfaces for the nitroprusside ion.

Conclusions:

  • The developed TDDFT implementation in DMol(3) is computationally efficient and scalable.
  • The method provides accurate quantitative and qualitative predictions for electronic and excited-state properties.
  • This advancement expands the capabilities of DFT for studying complex chemical phenomena.