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相关概念视频

Semiconductors01:22

Semiconductors

1.3K
There is variation in the electrical conductivity of materials - metals, semiconductors, and insulators that are showcased with the help of the energy band diagrams.
Metals such as copper (Cu), zinc (Zn), or lead (Pb) have low resistivity and feature conduction bands that are either not fully occupied or overlap with the valence band, making a bandgap non-existent. This allows electrons in the highest energy levels of the valence band to easily transition to the conduction band upon gaining...
1.3K
Types of Semiconductors01:20

Types of Semiconductors

1.3K
Intrinsic semiconductors are highly pure materials with no impurities. At absolute zero, these semiconductors behave as perfect insulators because all the valence electrons are bound, and the conduction band is empty, disallowing electrical conduction. The Fermi level is a concept used to describe the probability of occupancy of energy levels by electrons at thermal equilibrium. In intrinsic semiconductors, the Fermi level is positioned at the midpoint of the energy gap at absolute zero. When...
1.3K
Network Covalent Solids02:18

Network Covalent Solids

15.9K
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
15.9K
Energy Bands in Solids01:01

Energy Bands in Solids

1.7K
Isolated atoms have discrete energy levels that are well described by the Bohr model. And, it quantifies the energy of an electron in a hydrogen atom as En. Higher quantum numbers 'n' yield less negative, closer electron energy levels.
 Band Formation:
When atoms are brought close together, as in a solid, these discrete energy levels begin to split due to the overlap of electron orbitals from adjacent atoms. This split occurs because of the Pauli exclusion principle, which states...
1.7K
Valence Bond Theory02:42

Valence Bond Theory

10.9K
Coordination compounds and complexes exhibit different colors, geometries, and magnetic behavior, depending on the metal atom/ion and ligands from which they are composed. In an attempt to explain the bonding and structure of coordination complexes, Linus Pauling proposed the valence bond theory, or VBT, using the concepts of hybridization and the overlapping of the atomic orbitals. According to VBT, the central metal atom or ion (Lewis acid) hybridizes to provide empty orbitals of suitable...
10.9K
Lewis Structures of Molecular Compounds and Polyatomic Ions02:54

Lewis Structures of Molecular Compounds and Polyatomic Ions

44.0K
To draw Lewis structures for complicated molecules and molecular ions, it is helpful to follow a step-by-step procedure as outlined:
44.0K

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Monolayer Contact Doping of Silicon Surfaces and Nanowires Using Organophosphorus Compounds
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Monolayer Contact Doping of Silicon Surfaces and Nanowires Using Organophosphorus Compounds

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在中以无序的原子网络进行分类

Tao Chen1, Jeroen van Gelder1, Bram van de Ven1

  • 1NanoElectronics Group, MESA+ Institute for Nanotechnology and BRAINS Center for Brain-Inspired Nano Systems, University of Twente, Enschede, The Netherlands.

Nature
|January 17, 2020
PubMed
概括
此摘要是机器生成的。

研究人员开发了一种基于的新型纳米材料系统,用于高效的并行非线性分类. 这种以神经网络为灵感的方法在纳米尺度上执行复杂的计算,为节能计算铺平了道路.

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Fabrication and Optimization of Type II Silicon Clathrate Films
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Fabrication and Optimization of Type II Silicon Clathrate Films

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科学领域:

  • 材料科学
  • 计算神经科学
  • 机器学习

背景情况:

  • 生物和人工神经网络在分类任务中表现出色.
  • 机器学习中的非线性预测可以改善分类,但在计算上却很昂贵.
  • 物理材料提供高计算密度,并行性和非线性投影的能量效率.

研究的目的:

  • 为非线性分类和特征提取开发纳米级并行方法.
  • 在可调节的配剂网络中利用跳跃导电的非线性.
  • 展示一个小型,节能计算的新模式.

主要方法:

  • 使用中可调节的原子网络.
  • 使用人工进化来重新配置用于特定计算功能的配方网络.
  • 在布尔逻辑门和手写数字分类 (修改国家标准与技术研究所数据库) 上测试了系统.

主要成果:

  • 成功实现了所有布尔逻辑门到室温,证明了非线性分类.
  • 进化后的多潘特网络在手写数字上进行了四输入二进制分类,比线性分类器更准确.
  • 基于材料的过器可以大大提高分类的准确性.

结论:

  • 建立了基于的电子产品的范式,使得小尺寸和节能计算成为可能.
  • 展示了纳米级材料系统对复杂计算任务的潜力.
  • 这种方法为非线性分类提供了传统的,计算上昂贵的方法的有希望的替代方案.