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相关概念视频

Quantum Numbers02:43

Quantum Numbers

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It is said that the energy of an electron in an atom is quantized; that is, it can be equal only to certain specific values and can jump from one energy level to another but not transition smoothly or stay between these levels.
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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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Classifying Matter by State02:49

Classifying Matter by State

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Chemistry is the study of matter and the changes it undergoes. Matter is anything that has mass and occupies space. Matter is all around us; the air, water, soil, mountains, even our bodies are all examples of matter. Matter is divided into three states — solid, liquid, and gas — that are commonly found on earth. The fourth state of matter, plasma, occurs naturally in the interiors of stars. 
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Electron Affinity03:07

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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Classifying Matter by Composition03:35

Classifying Matter by Composition

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Matter: Pure Substances and Mixtures
According to its composition, the matter can be classified into two broad categories — pure substances and mixtures. 
A pure substance is a form of matter that has a constant composition throughout with uniform properties. For example, any sample of sucrose has the same composition and same physical properties, such as melting point, color, and sweetness, regardless of the source from which it is isolated. 
A mixture is composed of two or...
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Physical and Chemical Properties of Matter02:57

Physical and Chemical Properties of Matter

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The characteristics that enable us to distinguish one substance from another are called properties.
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相关实验视频

Updated: Jan 23, 2026

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
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电子量子物质成像实验中的机器学习

Yi Zhang1, A Mesaros1,2, K Fujita3

  • 1Department of Physics, Cornell University, Ithaca, NY, USA.

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|June 21, 2019
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概括
此摘要是机器生成的。

机器学习分析复杂的电子量子物质 (EQM) 图像. 在氧化铜Mott绝缘体中发现隐藏的四个单元细胞周期状态和巧合的阴性EQM状态.

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科学领域:

  • 凝聚物质物理
  • 材料科学
  • 人工智能

背景情况:

  • 传统的科学方法很难处理来自自动仪器的大量复杂数据.
  • 机器学习 (ML) 在分析电子量子物质 (EQM) 的合成数据方面取得了成功.
  • 应用ML对实验EQM数据,如原子尺度图像,是一个新的前沿.

研究的目的:

  • 开发和训练能够识别EQM图像阵列中的隐藏顺序的人工神经网络 (ANN).
  • 使用这些ANN分析载体合氧化铜Mott绝缘体的实验EQM图像数据.
  • 在复杂,杂的实验数据中识别新的电子状态.

主要方法:

  • 一套人工神经网络 (ANN) 的开发和培训.
  • 使用训练有素的ANN进行实验衍生EQM图像阵列的分析.
  • 使用电子量子物质的原子尺度可视化数据.

主要成果:

  • 在复杂和杂的实验EQM图像数据中成功识别了隐藏的顺序.
  • 发现一个与格子相称的,四个单元细胞周期性的,转换对称的EQM状态.
  • 确定一个一致的单向内马特 EQM 状态.

结论:

  • 机器学习,特别是ANN,可以有效地分析复杂的实验EQM数据以发现隐藏的状态.
  • 在氧化铜Mott绝缘体中发现的状态与电子液晶的强合理论一致.
  • 这种方法为数据丰富领域的科学发现提供了强大的新方法.