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Related Concept Videos

Approximate Integration01:24

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In many practical and theoretical contexts, the exact value of a definite integral may be inaccessible. This limitation typically arises when the antiderivative of a function is either unknown or cannot be expressed in a closed mathematical form. Alternatively, it can occur when a function is defined not by a formula but by a finite set of empirical data points, such as those collected during experiments. In these cases, approximate integration techniques provide a valuable solution.One of the...
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Linearization is a mathematical technique used to approximate complex, nonlinear functions with simpler linear models in the vicinity of a chosen reference point. The method is based on the idea that, although a function may be difficult to evaluate exactly, its behavior near a specific input value can often be closely approximated by the tangent line at that point. This approach is particularly useful when small deviations from a known value are involved.Consider the square root function, for...
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A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
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Continuous probability distributions are used to model random variables that can take on any real value within a specified range. These variables do not take on isolated or countable values but rather exist on a continuum. For example, the height of an individual can be measured with increasing precision—such as 163.5 or 165.25 centimeters—demonstrating that height is a continuous random variable.The behavior of such variables is described using a probability density function (PDF),...
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Long-range-corrected Rung 3.5 density functional approximations.

Benjamin G Janesko1, Emil Proynov1, Giovanni Scalmani2

  • 1Department of Chemistry and Biochemistry, Texas Christian University, Fort Worth, Texas 76110, USA.

The Journal of Chemical Physics
|March 17, 2018
PubMed
Summary
This summary is machine-generated.

New density functional theory approximations, Rung 3.5 functionals, overcome limitations in atomic cores and density tails. Range-separated Hartree-Fock exchange improves accuracy for chemical reactions and material properties.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Materials Science

Background:

  • Density functional theory (DFT) approximations are crucial for electronic structure calculations.
  • Existing Rung 3.5 functionals, while flexible, struggle with accuracy in atomic cores and density tails.
  • Semilocal approximations and exact Hartree-Fock (HF) exchange have limitations that Rung 3.5 aims to bridge.

Purpose of the Study:

  • To develop new Rung 3.5 functionals that address limitations in atomic cores and density tails.
  • To introduce range-separated admixture of HF exchange into Rung 3.5 approximations.
  • To provide a framework for more flexible range-separated Rung 3.5 approximations in DFT.

Main Methods:

  • Development of three novel Rung 3.5 functionals: LRC-ωΠLDA, SLC-ΠLDA, and LRC-ωΠLDA-AC.
  • Implementation of a new Rung 3.5 scheme capable of analytic fourth derivatives.
  • Testing the functionals against established benchmarks including atomization energies, reaction barriers, and electronic properties.

Main Results:

  • LRC-ωΠLDA and SLC-ΠLDA show an 8-fold improvement in atomization energies and reaction barriers over full-range ΠLDA.
  • LRC-ωΠLDA-AC achieves accuracy comparable to standard long-range corrected schemes like LC-ωPBE.
  • New functionals provide more accurate highest occupied orbital energies and correctly describe complex electronic phenomena, including charge-transfer complexes and defect-induced spin distributions.

Conclusions:

  • The developed range-separated Rung 3.5 functionals significantly enhance the accuracy of DFT calculations.
  • These functionals effectively address the limitations of previous approximations in specific electronic regions.
  • The study establishes a versatile framework for future development of advanced DFT approximations.