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相关概念视频

Principle of Virtual Work: Problem Solving01:13

Principle of Virtual Work: Problem Solving

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The principle of virtual work is an essential concept in the field of mechanics and engineering. This is used to solve problems related to the equilibrium of a structure or system. It is based on the assumption that if a system is in equilibrium, the work done by all the forces during a virtual displacement is zero. This principle is applied by considering virtual displacements of the system and the corresponding work done by internal and external forces.
To apply the principle of virtual work,...
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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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Frames: Problem Solving II01:26

Frames: Problem Solving II

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Consider a hydraulic hoist supporting a load of 1 kN. Assuming a simplified schematic representation of this frame structure, the force acting on BD and BF members can be determined.
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Frames: Problem Solving I01:24

Frames: Problem Solving I

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Consider a jib crane with an external load suspended from the pulley. The dimensions of the crane members are shown in the figure. A systematic analysis of the frame structure is required to determine the reaction forces at the pin joints, assuming that the pulleys are frictionless.
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Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

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Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
Next,...
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Overview of Electron Microscopy01:25

Overview of Electron Microscopy

9.3K
The wavelengths of visible light ultimately limit the maximum theoretical resolution of images created by light microscopes. Most light microscopes can only magnify 1000X, and a few can magnify up to 1500X. Electrons, like electromagnetic radiation, can behave like waves, but with wavelengths of 0.005 nm, they produce significantly greater resolution up to 0.05 nm as compared to 500 nm for visible light. An electron microscope (EM) can create a sharp image that is magnified up to 2,000,000X.
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相关实验视频

Updated: Jul 25, 2025

Modeling an Enzyme Active Site using Molecular Visualization Freeware
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Modeling an Enzyme Active Site using Molecular Visualization Freeware

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通过研讨会为材料信息学教育提供框架.

Arun Mannodi-Kanakkithodi1, Austin McDannald2, Shijing Sun3

  • 1Materials Engineering, Purdue University, West Lafayette, USA.

MRS bulletin
|June 26, 2023
PubMed
概括
此摘要是机器生成的。

材料信息学教育对于培养未来科学家在数据科学,人工智能 (AI) 和机器学习 (ML) 方面至关重要. 实践研讨会有效地向研究人员介绍用于材料数据分析的AI/ML工具.

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A Technical Guide for Performing Spectroscopic Measurements on Metal-Organic Frameworks
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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
  • 计算科学 计算科学

背景情况:

  • 材料信息学领域需要熟练掌握数据科学,人工智能和ML的科学家.
  • 传统的课程往往缺乏这些领域的综合培训.

研究的目的:

  • 突出材料信息学教育的重要性.
  • 为材料研究人员详细介绍AI/ML研讨会的结构和成功情况.
  • 倡导将AI/ML培训纳入材料科学教育.

主要方法:

  • 在2022年的MRS会议上,对材料数据的AI/ML进行了实践研讨会.
  • 专注于基本的AI/ML概念,算法和实际应用.
  • 利用竞赛来增强参与和学习.

主要成果:

  • 成功地向材料研究人员介绍了AI/ML工具和概念.
  • 证明了研讨会在促进AI/ML的实际应用方面的有效性.
  • 收到了积极的反和未来车间整合的计划.

结论:

  • 实践研讨会是材料科学家学习和应用AI/ML的有效方法.
  • 在AI/ML的继续教育对于材料信息学的进步至关重要.
  • 研讨会为传播AI/ML知识提供了一个可扩展和可访问的平台.