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相关概念视频

Atomic Orbitals02:44

Atomic Orbitals

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An atomic orbital represents the three-dimensional regions in an atom where an electron has the highest probability to reside. The radial distribution function indicates the total probability of finding an electron within the thin shell at a distance r from the nucleus. The atomic orbitals have distinct shapes which are determined by l, the angular momentum quantum number. The orbitals are often drawn with a boundary surface, enclosing densest regions of the cloud.
33.1K
Electronic Structure of Atoms02:28

Electronic Structure of Atoms

20.9K

An atom comprises protons and neutrons, which are contained inside the dense, central core called the nucleus, with electrons present around the nucleus. Taking into account the wave–particle duality of electrons and the uncertainty in position around the nucleus, quantum mechanics provides a more accurate model for the atomic structure. It describes atomic orbitals as the regions around the nucleus where electrons of discrete energy exist, characterized by four quantum...
20.9K
VSEPR Theory02:37

VSEPR Theory

9.0K
Valence shell electron-pair repulsion theory (VSEPR theory) enables us to predict the molecular structure around a central atom from an examination of the number of bonds and lone electron pairs in its Lewis structure. The VSEPR model assumes that electron pairs in the valence shell of a central atom will adopt an arrangement that minimizes repulsions between these electron pairs by maximizing the distance between them. The electrons in the valence shell of a central atom form either bonding...
9.0K
Valence Bond Theory and Hybridized Orbitals02:38

Valence Bond Theory and Hybridized Orbitals

18.8K
According to valence bond theory, a covalent bond results when: (1) an orbital on one atom overlaps an orbital on a second atom, and (2) the single electrons in each orbital combine to form an electron pair. The strength of a covalent bond depends on the extent of overlap of the orbitals involved. Maximum overlap is possible when the orbitals overlap on a direct line between the two nuclei.
A σ bond (single bond in a Lewis structure) is a covalent bond in which the electron density is...
18.8K
VSEPR Theory and the Basic Shapes02:52

VSEPR Theory and the Basic Shapes

67.4K
Overview of VSEPR Theory
67.4K
The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

41.9K
Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.
41.9K

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相关实验视频

Updated: May 30, 2025

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids
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设计空间的E(3) - 相当的原子中心的原子间潜力.

Ilyes Batatia1,2, Simon Batzner3, Dávid Péter Kovács1

  • 1Engineering Laboratory, University of Cambridge, Cambridge, UK.

Nature machine intelligence
|January 29, 2025
PubMed
概括

机器学习通过创造新的原子间潜力,彻底改变了分子动力学模拟. 一个统一的数学框架连接了原子集群扩张和神经等差原子间潜力 (NequIP),导致了像BOTnet.net这样的简化,准确的模型.

关键词:
原子模型是原子模型.计算化学是一种计算化学.计算方法 计算方法分子动力学分子动力学

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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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科学领域:

  • 计算材料科学科学 计算材料科学
  • 计算化学计算化学
  • 机器学习 机器学习

背景情况:

  • 机器学习已经显著提升了分子动力学模拟.
  • 机器学习的新架构 - - 原子间潜能 - - 已经迅速出现.
  • 原子集群扩张和神经等价原子间潜力 (NequIP) 是最近显著的发展.

研究的目的:

  • 为现有的机器学习原子间潜能模型构建一个统一的数学框架.
  • 为系统地探索这些模型的设计空间提供一个工具.
  • 通过废弃研究分析NequIP中的关键设计选择.

主要方法:

  • 开发了一个统一原子集群扩张和NequIP的数学框架.
  • 扩展原子集群扩展到一个多层架构.
  • 解释了线性化NequIP作为一个多项式模型的散化.
  • 对NequIP进行了废除研究,重点关注域内和域外的准确性和推断.

主要成果:

  • 该框架统一了原子集群扩张和NequIP.
  • 废弃性研究确定了NequIP准确性的关键设计选择.
  • 开发了一个简化的模型,BOTnet (体序张量网络).
  • 博特网展示了可解释的架构,并保持了基准数据集的准确性.

结论:

  • 一个统一的框架为机器学习的原子间潜力提供了见解.
  • 博特网提供了一个简单,准确和可解释的替代方案.
  • 了解设计选择对于开发高精度潜能至关重要.