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相关概念视频

Hydrogen Bonds01:04

Hydrogen Bonds

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A hydrogen bond is formed when a weakly positive hydrogen atom already bonded to one electronegative atom (for example, the oxygen in the water molecule) is attracted to another electronegative atom from another polar molecule, such as water (H2O), hydrogen fluoride (HF), or ammonia (NH3). The huge electronegativity difference between the H atom (2.1) and the atom to which it is bonded (4.0 for an F atom, 3.5 for an O atom, or 3.0 for an N atom), combined with the very small size of an H atom...
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Hybridization of Atomic Orbitals II03:35

Hybridization of Atomic Orbitals II

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sp3d and sp3d 2 Hybridization
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Hybridization of Atomic Orbitals I03:24

Hybridization of Atomic Orbitals I

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The mathematical expression known as the wave function, ψ, contains information about each orbital and the wavelike properties of electrons in an isolated atom. When atoms are bound together in a molecule, the wave functions combine to produce new mathematical descriptions that have different shapes. This process of combining the wave functions for atomic orbitals is called hybridization and is mathematically accomplished by the linear combination of atomic orbitals. The new orbitals that...
46.7K
Molecular Models02:00

Molecular Models

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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.
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相关实验视频

Updated: Jun 13, 2025

Neutron Crystallography Data Collection and Processing for Modelling Hydrogen Atoms in Protein Structures
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Neutron Crystallography Data Collection and Processing for Modelling Hydrogen Atoms in Protein Structures

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一个基于机器学习的框架,用于在原子尺度上绘制的地图.

Qingkun Zhao1,2, Qi Zhu2, Zhenghao Zhang1

  • 1Department of Engineering Mechanics, State Key Laboratory of Fluid Power and Mechatronic Systems, Center for X-mechanics, Zhejiang University, Hangzhou 310027, People's Republic of China.

Proceedings of the National Academy of Sciences of the United States of America
|September 16, 2024
PubMed
概括

一个新的机器学习框架,Atom-H,使得原子的原子尺度成像. 这一突破为的脆化和金属中的物质降解提供了关键的见解.

关键词:
原子尺度成像 原子尺度成像气的化物是化物.格子缺陷 格子缺陷机器学习是机器学习.

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Quantification of Hydrogen Concentrations in Surface and Interface Layers and Bulk Materials through Depth Profiling with Nuclear Reaction Analysis
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Quantification of Hydrogen Concentrations in Surface and Interface Layers and Bulk Materials through Depth Profiling with Nuclear Reaction Analysis

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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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相关实验视频

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Quantification of Hydrogen Concentrations in Surface and Interface Layers and Bulk Materials through Depth Profiling with Nuclear Reaction Analysis
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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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科学领域:

  • 材料科学 材料科学 材料科学
  • 纳米技术 纳米技术
  • 计算科学 计算科学

背景情况:

  • 对于清洁能源和工业至关重要,但会导致材料降解,如脆性.
  • 在原子尺度上像气这样的光原子的成像是一个重要的科学挑战.
  • 了解与材料的相互作用对于开发强大的技术至关重要.

研究的目的:

  • 介绍Atom-H,一种用于原子规模气成像的机器学习框架.
  • 为了可视化的分布和材料缺陷的局部应力.
  • 为引发的机械行为提供原子层面的洞察力.

主要方法:

  • 开发了一种通用的机器学习框架,名为Atom-H.
  • 使用高分辨率电子显微镜图像作为输入数据.
  • 应用框架来分析金属材料中的分布和应力.

主要成果:

  • 原子-H精确地对原子和局部应力在晶格缺陷 (位移,粒边界,裂,相边界) 的图像.
  • 该框架提供了对纯金属 (Ni,Fe,Ti) 和合金 (FeCr) 的控制机械行为的原子级洞察力.
  • 证明了能够高精度地绘制"隐形"原子的能力.

结论:

  • 原子-H为研究缩提供了一个强大的新工具.
  • 该框架在材料科学和工程领域有直接的应用.
  • 预计Atom-H将推进跨科学学科的"隐形"原子的绘制.