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相关概念视频

Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

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The motion of molecules in a gas is random in magnitude and direction for individual molecules, but a gas of many molecules has a predictable distribution of molecular speeds. This predictable distribution of molecular speeds is known as the Maxwell-Boltzmann distribution. The distribution of molecular speeds in liquids is comparable to that of gases but not identical and can help to understand the phenomenon of the boiling and vapor pressure of a liquid. Consider that a molecule requires a...
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Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

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A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
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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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The importance of understanding acceleration spans our day-to-day experiences, as well as the vast reaches of outer space and the tiny world of subatomic physics. In everyday conversation, to accelerate means to speed up. For instance, we are familiar with the acceleration of our car; the harder we apply our foot to the gas pedal, the faster we accelerate. The greater the acceleration, the greater the change in velocity over a given time. Acceleration is widely seen in experimental physics. In...
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The word "gas" comes from the Flemish word meaning "chaos," first used to describe vapors by the chemist J. B. van Helmont. Consider a container filled with gas, with a continuous and random motion of molecules. During collisions, the velocity component parallel to the wall is unchanged, and the component perpendicular to the wall reverses direction but does not change in magnitude. If the molecule’s velocity changes in the x-direction, then its momentum is changed.
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When a fluid is in constant acceleration, the pressure and buoyant force equations are modified. Suppose a beaker is placed in an elevator accelerating upward with a constant acceleration, a. In the beaker, assume there is a thin cylinder of height h with an infinitesimal cross-sectional area, ΔS.
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在CASTEP中用于分子动力学的机器学习加速.

Tamás K Stenczel1, Zakariya El-Machachi2, Guoda Liepuoniute1

  • 1Engineering Laboratory, University of Cambridge, Cambridge CB2 1PZ, United Kingdom.

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概括

我们开发了一种计算方法,将机器学习 (ML) 潜力与CASTEP模拟集成在一起,从而实现准确的材料建模. 这种方法验证了ML模型与密度函数理论 (DFT) 数据进行可靠的预测.

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科学领域:

  • 计算材料科学科学 计算材料科学
  • 材料建模 材料建模
  • 机器学习应用 机器学习应用

背景情况:

  • 机器学习 (ML) 原子间潜力为材料建模提供了希望,但对于新系统通常需要显著的专业知识.
  • 已建立的密度函数理论 (DFT) 包被广泛使用,但可以是计算密集的.
  • 将ML潜力与第一原则方法相结合,对于推进材料发现至关重要.

研究的目的:

  • 介绍一种计算方法,用于将CASTEP模拟软件与机动装配和ML原子间潜力的评估相结合.
  • 建立一个框架,通过与DFT参考数据进行定期比较,系统地提高ML的潜在准确性.
  • 在材料模拟中展示这种综合方法的实际应用.

主要方法:

  • 开发了一个计算框架,将CASTEP,一个第一原则模拟包,与ML原子间潜力模型相结合.
  • 在模拟过程中实施了ML潜力的飞行安装和评估方案.
  • 使用定期对DFT参考数据进行检查,以确保和量化不断变化的ML模型的准确性.

主要成果:

  • 通过CASTEP模拟成功集成ML原子间潜力开发.
  • 证明了使用DFT参考数据用于实时ML模型验证和改进的有效性.
  • 应用该方法来执行碳纳米结构的高温分子动力学模拟与验证的ML潜力.

结论:

  • 提出的计算方法方便在材料建模中使用ML原子间潜力,通过DFT验证确保准确性.
  • 这种方法降低了在复杂的模拟中利用ML潜力的进入障碍.
  • 免费可用的代码支持计算材料科学和ML应用的学术研究.