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関連する概念動画

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...
Intermolecular Forces and Physical Properties02:56

Intermolecular Forces and Physical Properties

Molecular Models02:00

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
Molecular Orbital Theory I02:35

Molecular Orbital Theory I

Overview of Molecular Orbital Theory
Polymers: Molecular Weight Distribution01:10

Polymers: Molecular Weight Distribution

For any given polymer, the weight average molecular weight (Mw) is higher than, if not equal to, the number average molecular weight (Mn). The only situation in which the weight average molecular weight and the number average molecular weight are equal is when a polymer consists only of chains with equal molecular weight. However, this never happens in a synthetic polymer, since it is difficult to control the polymerization process up to a molecular level with accuracy to a hundred percent.
Crystal Density01:19

Crystal Density

The crystal lattice structure of a material allows us to determine how many molecules exist in its unit cell. With this information, alongside the unit-cell parameters - three distance parameters (a, b, c) and three angular parameters (α, β, γ).Density (ρ) = (Z × M) / (a × b × c × NA)where:Z is the number of formula units per unit cellM is the molar mass of the substancea, b, and c are the edge lengths of the unit cellNA is Avogadro’s numberFor a simple cubic lattice, atoms are located only at...

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関連する実験動画

Updated: Jun 28, 2026

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

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

Published on: September 17, 2021

密度関数に関する実験的推薦を基に,機械的に結合した分子の性質を予測する.

Diego Benitez1, Ekaterina Tkatchouk, Il Yoon

  • 1Department of Chemistry and Biochemistry, University of California, Los Angeles, California 90095, USA.

Journal of the American Chemical Society
|October 22, 2008
PubMed
まとめ

密度関数理論 (DFT) は,機械的に相互接続された分子の性質を正確に予測するために苦労します. 新しいM06機能は,構造と興奮エネルギーの精度が向上し,分子設計を支援しています.

さらに関連する動画

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

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

関連する実験動画

Last Updated: Jun 28, 2026

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

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

Published on: September 17, 2021

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

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

科学分野:

  • コンピューティング・ケミストリー
  • ナノテクノロジー ナノテクノロジー
  • マテリアルサイエンス 材料科学

背景:

  • ロタキサンやカタネンなどの機械的に相互接続された分子 (MIM) は,分子電子学において極めて重要であり,ナノアクチュエーターや薬物投与の潜在力を秘めている.
  • 構造,結合,および興奮エネルギーを予測するための正確な定量的基準は,機械的結合を持つ新しいMIMを設計するために必要です.

研究 の 目的:

  • MIMに関連する非結合結合複合体の性質を予測する密度関数理論 (DFT) の有効性を評価する.
  • MIMの正確な計算設計のための適切なDFT関数を特定する.

主な方法:

  • M06-スイートを含む様々な密度関数の評価,構造パラメータ,結合エネルギー,およびモデル非結合結合複合体の興奮エネルギーの予測.
  • DFTの結果を実験データと経験的な力場 (DREIDING) と比較する.

主要な成果:

  • 単一の密度機能は完全に満足できるものではなかったが,M06スイートは著しい改善を示した.
  • M06の機能は,B3LYPと比較して,平間距離 (0.04 Å誤差) と興奮エネルギー (0.08 eV以内) の精度が向上した.
  • M06は,実験値よりも強い結合 (+22.6 kcal mol−1) を予測し,B3LYPとDREIDINGは,アンダーバインディング (それぞれ-29 kcal mol−1) を示した.

結論:

  • 密度機能のM06スイートは,従来の機能と比較して,MIMの構造および電子特性の精度が向上しています.
  • 結合エネルギー予測に対処するためにさらなる精細化が必要ですが,M06ベースのDFTは,高度な分子マシンの合理的な設計を導くために有望であることを示しています.