Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

2.4K
Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
2.4K
Overview of Microscopy Techniques01:22

Overview of Microscopy Techniques

10.5K
The early pioneers of microscopy opened a window into the invisible world of microorganisms. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes that leveraged nonvisible light, such as fluorescence microscopy that uses an ultraviolet light source and electron microscopy that uses short-wavelength electron beams. These advances significantly improved magnification, image resolution, and contrast. By comparison, the...
10.5K
Atomic Force Microscopy01:08

Atomic Force Microscopy

3.4K
Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...
3.4K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Strength-ductility synergy in lightweight aluminium alloys with nano-layered fibres and core-shell nano-particles.

Nature communications·2026
Same author

Voltage-Triggered Emergent Dynamics in Strongly Coupled Nanomagnet Networks for Neuromorphic Computing.

ACS nano·2026
Same author

Non-Surgical and Surgical Management of Peri-Implant Diseases and Defects in Zirconia Implants: A Scoping Review.

The International journal of oral & maxillofacial implants·2026
Same author

From 2D MXenes to 3D Carbides: Transformation of Ti<sub>3</sub>C<sub>2</sub>T<sub><i>z</i></sub> Thin Films into TiC<sub><i>x</i></sub> Carbide Nanolayers.

Nano letters·2026
Same author

Effect of Progressive Versus Standard Implant Thread Designs on Primary Stability and Insertion Torque: An In Vitro Study.

The International journal of oral & maxillofacial implants·2026
Same author

Plasma-Engineered Hydroxyl Defects in NiO: A DFT-Supported-Spectroscopic Analysis of Oxygen-Hole States and Implications for Water Oxidation.

Journal of the American Chemical Society·2026

相关实验视频

Updated: Jul 17, 2025

Atom Probe Tomography Analysis of Exsolved Mineral Phases
08:14

Atom Probe Tomography Analysis of Exsolved Mineral Phases

Published on: October 25, 2019

7.4K

一个机器学习框架,用于量化原子探头断层数据中的化学分离和微观结构特征.

Alaukik Saxena1, Nikita Polin1, Navyanth Kusampudi1

  • 1Max-Planck-Institut für Eisenforschung GmbH, Max-Planck-Straße 1, 40237 Düsseldorf, Germany.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
|August 28, 2023
PubMed
概括
此摘要是机器生成的。

我们开发了一种机器学习策略,用于半自动分析原子探头断层扫描 (APT) 数据. 该方法有效地识别材料相,并量化其组成和微观结构.

关键词:
铁合金的SmCo合金原子探头断层扫描 (tomography) 是一种原子探头.图像分割 图像细分 图像细分交叉路口检测检测检测器机器学习是机器学习.

更多相关视频

Atom Probe Tomography Studies on the CuIn,GaSe2 Grain Boundaries
09:51

Atom Probe Tomography Studies on the CuIn,GaSe2 Grain Boundaries

Published on: April 22, 2013

12.9K
Picometer-Precision Atomic Position Tracking through Electron Microscopy
15:04

Picometer-Precision Atomic Position Tracking through Electron Microscopy

Published on: July 3, 2021

7.4K

相关实验视频

Last Updated: Jul 17, 2025

Atom Probe Tomography Analysis of Exsolved Mineral Phases
08:14

Atom Probe Tomography Analysis of Exsolved Mineral Phases

Published on: October 25, 2019

7.4K
Atom Probe Tomography Studies on the CuIn,GaSe2 Grain Boundaries
09:51

Atom Probe Tomography Studies on the CuIn,GaSe2 Grain Boundaries

Published on: April 22, 2013

12.9K
Picometer-Precision Atomic Position Tracking through Electron Microscopy
15:04

Picometer-Precision Atomic Position Tracking through Electron Microscopy

Published on: July 3, 2021

7.4K

科学领域:

  • 材料科学 材料科学 材料科学
  • 数据科学数据科学数据科学
  • 计算材料科学科学 计算材料科学

背景情况:

  • 原子探头断层扫描 (APT) 对于分析多组件材料至关重要.
  • 对APT数据的定量分析通常需要大量的人类专业知识来定义感兴趣的区域.
  • 了解分离和微观结构的相互作用是先进材料的关键.

研究的目的:

  • 引入一个计算效率高的机器学习策略,用于APT数据的半自动分析.
  • 识别组成上不同的领域并量化它们的几何和组成特征.
  • 克服复杂材料系统中手动分析的局限性.

主要方法:

  • 一个多阶段的机器学习管道,包括将数据粗粒化为voxels和组合统计数据.
  • 组合空间中的聚类用于相位识别,其次是基于密度的聚类用于实时空间细分.
  • 通过主要组件分析或基于U-Net的复杂形态的语义细分来完善细分.

主要成果:

  • 在 Sm- ((Co,Fe) -Zr-Cu 合金中成功地半自动识别和细分组成上不同的相.
  • 与沉物几何相对应的组成分布和分离效应的详细映射.
  • 解开交织的,板状沉物相的演示.

结论:

  • 开发的机器学习方法显著提高了APT数据分析的效率和客观性.
  • 这种方法可以详细描述复杂材料中的微观结构-组成关系.
  • 它为定量分析提供了一个强大的框架,而不仅仅依赖于voxel组合.