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相关概念视频

Fermi Level Dynamics01:12

Fermi Level Dynamics

228
The vacuum level denotes the energy threshold required for an electron to escape from a material surface. It is usually positioned above the conduction band of a semiconductor and acts as a benchmark for comparing electron energies within various materials.
Electron affinity in semiconductors refers to the energy gap between the minimum of its conduction band and the vacuum level and it is a critical parameter in determining how easily a semiconductor can accept additional electrons.
The work...
228
Accelerating Fluids01:17

Accelerating Fluids

1.0K
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.
The motion of the liquid within this infinitesimal cylinder is considered to obtain the pressure difference. Three vertical forces act on this liquid:
1.0K
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.4K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.4K
Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

3.9K
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...
3.9K
Equilibrium Conditions for a Particle01:23

Equilibrium Conditions for a Particle

1.1K
When an object is in equilibrium, it is either at rest or moving with a constant velocity. There are two types of equilibrium: static and dynamic. Static equilibrium occurs when an object is at rest, while dynamic equilibrium occurs when an object is moving with a constant velocity. In both cases, there must be a balance of forces acting on the object.
To understand the concept of equilibrium, let us first consider the forces acting on an object. When different forces act on an object, they can...
1.1K
Maxwell's Thermodynamic Relations01:23

Maxwell's Thermodynamic Relations

2.6K
Maxwell's thermodynamic relations are very useful in solving problems in thermodynamics. Each of Maxwell's relations relates a partial differential between quantities that can be hard to measure experimentally to a partial differential between quantities that can be easily measured. These relations are a set of equations derivable from the symmetry of the second derivatives and the thermodynamic potentials.
All thermodynamic potentials are exact differentials. Therefore, their second-order...
2.6K

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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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用图形处理单元加速相对论精确两组分密度函数理论计算.

Mikael Kovtun1, Eleftherios Lambros1, Aodong Liu1

  • 1Department of Chemistry, University of Washington Seattle, Washington 98115, United States.

Journal of chemical theory and computation
|September 3, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了密度函数理论中交换相关性潜能计算的GPU加速. 这显著加快了相对论电子结构模拟的速度,提供了相当大的计算能力.

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Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids
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相关实验视频

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科学领域:

  • 计算化学是一种计算化学.
  • 材料科学是一种材料科学.
  • 量子力学就是量子力学.

背景情况:

  • 交换相关性潜力的数值集成是计算密集的.
  • 图形处理单元 (GPU) 提供了巨大的并行处理能力.
  • 相对论,二元密度函数理论 (DFT) 需要大量的计算资源.

研究的目的:

  • 在GauXC库中实现和评估GPU加速用于交换相关性潜力计算.
  • 评估相对论 DFT 计算的绩效效益.
  • 为了能够更有效地模拟重元素系统.

主要方法:

  • 在GauXC库中实现GPU加速交换关联潜能集成.
  • 对铜,银和金币金属集群的基准计算.
  • 基于GPU的性能与传统的基于CPU的计算进行比较.

主要成果:

  • 与CPU计算相比,通过GPU加速实现了显著的加速度.
  • 一个GPU卡显示了相当于大约400个CPU核心的计算能力.
  • 加速随着系统大小的增加,表明可扩展性更大的模拟.
  • 支持任意角动量基础函数可提高重元素的适用性.

结论:

  • 该GPU加速实现为相对论电子结构计算提供了相当大的加速.
  • 这一进步使得DFT中的更高效和更广泛的计算研究成为可能.
  • 这种方法对未来具有显著的潜力,在计算化学和材料科学中要求更高的模拟.