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相关概念视频

Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

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In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
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Space Trusses01:25

Space Trusses

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A space truss is a three-dimensional counterpart of a planar truss. These structures consist of members connected at their ends, often utilizing ball-and-socket joints to create a stable and versatile framework. The space truss is widely used in various construction projects due to its adaptability and capacity to withstand complex loads.
At the core of a space truss lies the fundamental unit known as the tetrahedron. This structure is composed of six members that form a three-dimensional shape...
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Elastic Collisions: Case Study01:15

Elastic Collisions: Case Study

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Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
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Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

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It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
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Space Trusses: Problem Solving01:29

Space Trusses: Problem Solving

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A space truss is a three-dimensional counterpart of a planar truss. These structures consist of members connected at their ends, often utilizing ball-and-socket joints to create a stable and versatile framework. Due to its adaptability and capacity to withstand complex loads, the space truss is widely used in various construction projects.
Consider a tripod consisting of a tetrahedral space truss with a ball-and-socket joint at C. Suppose the height and lengths of the horizontal and vertical...
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Elastic Collisions: Introduction01:00

Elastic Collisions: Introduction

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An elastic collision is one that conserves both internal kinetic energy and momentum. Internal kinetic energy is the sum of the kinetic energies of the objects in a system. Truly elastic collisions can only be achieved with subatomic particles, such as electrons striking nuclei. Macroscopic collisions can be very nearly, but not quite, elastic, as some kinetic energy is always converted into other forms of energy such as heat transfer due to friction and sound. An example of a nearly...
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通过超空间优化和TETRIS播种改进结构搜索.

Daviti Gochitashvili1, Maxwell Meyers1, Cindy Wang2

  • 1Department of Physics, Applied Physics, and Astronomy, Binghamton University-SUNY, Binghamton, New York 13902, USA. kolmogorov@binghamton.edu.

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超空间结构的全球优化 (GOSH) 被扩展到纳米粒子和固体的神经网络潜力. 虽然4D优化显示了适度的收益,但TETRIS启发的包装显著提高了结构搜索效率.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 计算化学的计算化学
  • 凝聚物质物理学 凝聚物质物理学

背景情况:

  • 先进的结构预测方法对于材料发现至关重要.
  • 超空间结构的全球优化 (GOSH) 提供了一种新的方法.
  • 将GOSH扩展到像Behler-Parrinello神经网络 (NN) 这样的精确潜力是一个关键的挑战.

研究的目的:

  • 为了将GOSH形式主义扩展到Behler-Parrinello神经网络潜力.
  • 评估GOSH与NN潜力的纳米粒子和晶体固体上的性能.
  • 为了比较4D优化与偏向初始配置生成的有效性.

主要方法:

  • 使用Behler-Parrinello NN潜力的GOSH的实施.
  • 与高效的本地最小化算法集成.
  • 基于Lennard-Jones集群,Au/Cu-Pd-Ag纳米粒子,二进制Sn合金和B/BC框架的基准测试,使用NN潜力和密度函数理论.

主要成果:

  • 四维优化为集群放松提供了适度的改进,但增加了计算成本.
  • 具有NN潜力的GOSH显著帮助纳米合金中的原子交换.
  • 产生初始配置的TETRIS启发的包装对全球结构搜索效率产生了更直接的影响.

结论:

  • 将GOSH扩展到NN潜力是可行的,但需要仔细考虑计算成本.
  • 有偏差的初始配置生成策略为加速全球结构搜索提供了更有效的途径.
  • 该研究为复杂材料系统的结构预测优化提供了见解.