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相关概念视频

Path Between Thermodynamics States01:21

Path Between Thermodynamics States

3.1K
Consider the two thermodynamic processes involving an ideal gas that are represented by paths AC and ABC in Figure 1:
3.1K
Thermodynamic Potentials01:26

Thermodynamic Potentials

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Thermodynamic potentials are state functions that are extremely useful in analyzing a thermodynamic system. They have dimensions of energy. The four important thermodynamic potentials are internal energy, enthalpy, Helmholtz free energy, and Gibbs free energy. These thermodynamic potentials can be expressed using two of the following variables: pressure, volume, temperature, and entropy. These two variables are expressed as the rate of change of the thermodynamic potential with respect to other...
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Thermodynamic Systems01:06

Thermodynamic Systems

5.0K
A thermodynamic system is a set of objects whose thermodynamic properties are of interest. The system is considered to be embedded in its surroundings or the environment. The system and its environment can exchange heat and do work on each other through a boundary that separates them. However, the immediate surroundings of the system interact with it directly and therefore have a much stronger influence on its behavior and properties.
Consider an example of  tea boiling in a kettle. The...
5.0K
Gibbs Free Energy and Thermodynamic Favorability02:23

Gibbs Free Energy and Thermodynamic Favorability

6.7K
The spontaneity of a process depends upon the temperature of the system. Phase transitions, for example, will proceed spontaneously in one direction or the other depending upon the temperature of the substance in question. Likewise, some chemical reactions can also exhibit temperature-dependent spontaneities. To illustrate this concept, the equation relating free energy change to the enthalpy and entropy changes for the process is considered:
6.7K
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
Heating and Cooling Curves02:44

Heating and Cooling Curves

22.7K
When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance, q, and its...
22.7K

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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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热力学一致的图表神经网络.

Jan G Rittig1, Alexander Mitsos1,2,3

  • 1Process Systems Engineering (AVT.SVT), RWTH Aachen University Forckenbeckstraße 51 52074 Aachen Germany amitsos@alum.mit.edu.

Chemical science
|October 21, 2024
PubMed
概括
此摘要是机器生成的。

我们开发了图形神经网络 (GE-GNN),以准确预测混合物特性. 这种方法确保了活性系数的热力学一致性,这对于化学过程建模至关重要.

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科学领域:

  • 热力学是一种热力学.
  • 机器学习 机器学习
  • 化学工程是化学工程的重要组成部分.

背景情况:

  • 预测活性系数对于化学过程设计至关重要.
  • 现有的模型往往面临着热力学一致性和适用性的局限性.
  • 准确预测构成依赖性质是一个关键的挑战.

研究的目的:

  • 引入一种新的图形神经网络 (GE-NN) 方法来预测活动系数.
  • 使用基本的热力学原理,确保预测中的热力学一致性.
  • 开发一个没有热力学建模局限性的模型.

主要方法:

  • 开发过多的吉布斯自由能量图神经网络 (GE-GNN).
  • 使用自动区分来进行端到端的学习活动系数.
  • 通过预测摩尔过剩的吉布斯自由能量来确保热力学一致性.

主要成果:

  • 在预测二进制混合物的活性系数方面取得了高准确性.
  • 证明了固有的热力学一致性,没有额外的损失条款.
  • 该GE-GNN模型显示没有热力学建模的限制.

结论:

  • GE-GNN提供了一种强大且热力学上一致的方法来预测混合物特性.
  • 这种方法促进了机器学习在化学热力学中的应用.
  • 该模型提供了对化学过程优化至关重要的可靠预测.