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相关概念视频

The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

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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.
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Electron Behavior01:09

Electron Behavior

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Electrons are negatively charged subatomic particles attracted to and orbit around the positively-charged nucleus of an atom. They reside in spaces associated with energy levels called shells and are further organized into subshells and orbitals within each shell.
Electrons Orbit the Nucleus
Electrons are found in specific locations outside of the nucleus. The shell in which an electron resides indicates the general energy level of the electron: those closer to the nucleus have less energy,...
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Electric Field of a Charged Disk01:23

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The simplest case of a surface charge distribution is the uniformly charged disk. Calculating its electric field also helps us calculate the electric field of a large plane of charge.
The system's symmetry is in the cylindrical directions across the plane of the charge. As a result, the electric fields created by various surface charge elements nullify each other in the direction parallel to the surface. Thereby, the resulting electric field is perpendicular to the plane. Since the disk is...
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Imagine a bucket of water. It contains many molecules, of the order of 1026 molecules. Thus, although it contains discrete elements (molecules) at the microscopic level, macroscopically, it can be considered continuous. Small volume elements of water, infinitesimal compared to the bulk of the bucket's volume, still contain many molecules. Under this framework, quantized matter is approximated as continuous for practical purposes.
The electric charge can also be subjected to an analogical...
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Electron Affinity

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The electron affinity (EA) is the energy change for adding an electron to a gaseous atom to form an anion (negative ion).
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Potential Due to a Polarized Object01:29

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A neutral atom consists of a positively charged nucleus surrounded by a negatively charged electron cloud. When placed in an external electric field, the external electric force pulls the electrons and nucleus apart, opposite to the intrinsic attraction between the nucleus and the electrons. The opposing forces balance each other with a slight shift between the center of masses of the nucleus and the electron cloud, resulting in a polarized atom. On the other hand, a few molecules, like water,...
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Updated: May 28, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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使用机器学习预测充电系统的电子密度.

Sherif Abdulkader Tawfik1,2, Sunil Gupta1, Svetha Venkatesh1

  • 1Applied Artificial Intelligence Institute, Deakin University, Geelong, Victoria 3216, Australia.

The journal of physical chemistry. A
|February 13, 2025
PubMed
概括
此摘要是机器生成的。

这项研究增强了DeepDFT机器学习模型,用于预测充电系统的电子密度. 这一进步使得更快,更具成本效益的材料属性的计算,而不牺牲准确性.

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科学领域:

  • 计算化学是一种计算化学.
  • 材料科学是一种材料科学.
  • 机器学习 机器学习

背景情况:

  • 预测电子密度对于使用第一原理方法计算分子和晶体特性至关重要.
  • 机器学习 (ML) 模型可以通过单独从原子结构预测电子密度来加速这些计算.
  • 现有的ML模型很难预测充电系统的电子密度.

研究的目的:

  • 扩展DeepDFT ML模型以准确预测充电系统的电子密度.
  • 为充电系统引入一种新的输入电荷表示.
  • 在各种充电材料类型中验证增强模型.

主要方法:

  • 修改了DeepDFT ML模型,将系统充电作为输入功能.
  • 开发并实施了一种新的输入电荷表示技术.
  • 在各种充电系统上测试该模型,包括有缺陷的矿石,LiCoO2超级电池,钻石缺陷,MOF和分子晶体.

主要成果:

  • 增强的DeepDFT模型成功地预测了充电系统的电子密度.
  • 输入电荷表示方法在多个测试案例中被证明是有效的.
  • 对各种充电材料实现了准确的预测,证明了模型的多功能性.

结论:

  • 修改后的DeepDFT模型为预测充电系统中的电子密度提供了准确而高效的方法.
  • 这项工作克服了基于ML的电子密度预测的重大局限性.
  • 该方法在计算材料科学和化学中具有广泛的适用性.