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相关概念视频

Thermosensation01:43

Thermosensation

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Peripheral thermosensation is the perception of external temperature. A change in temperature (on the surface of the skin and other tissues) is detected by a family of temperature-sensitive ion channels called Transient Receptor Potential, or TRP, receptors. These receptors are located on free nerve endings. Those detecting cold temperatures are closer to the surface of the skin than the nerve endings detecting warmth. These thermoTRP channels, while temperature selective, have relatively...
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Thermal expansion and Thermal stress: Problem Solving01:27

Thermal expansion and Thermal stress: Problem Solving

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San Francisco's Golden Gate Bridge is exposed to temperatures ranging from -15 °C to 40 °C. At its coldest, the main span of the bridge is 1275 m long. Assuming that the bridge is made entirely of steel, what is the change in its length between these temperatures?
To solve the problem, first, identify the known and unknown quantities. The initial length (L) of the bridge is 1275 m, the coefficient of linear expansion (α) for steel is 12 x 10-6/°C, and the change in...
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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...
880
Specific Heat01:16

Specific Heat

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The specific heat capacity of a substance refers to the energy required to increase the temperature of one gram of that substance by one degree Celcius. Specific heat capacity is often represented in calories (cal), grams (g), and degrees Celsius (oC), but can also be expressed in joules (J), kilograms (kg), and Kelvin (K), among other units.
For example, increasing the temperature of one gram of water by 1°C requires one calorie of heat energy and can be written as 1 cal/g-°C, or...
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First Law Of Thermodynamics: Problem-Solving01:21

First Law Of Thermodynamics: Problem-Solving

2.7K
The first law of thermodynamics states that the change in internal energy of the system is equal to the net heat transfer into the system minus the net work done by the system. This equation is a generalized form of energy conservation and can be applied to any thermodynamic process.
The following strategies can be used to solve any problem involving the first law of thermodynamics.
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Thermodynamic Systems01:06

Thermodynamic Systems

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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...
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Author Spotlight: Advancing Energy Solutions Using Nanocomposites as Processed Thermoelectric Materials
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闭环错误校正学习加速了热电材料的实验发现.

Hitarth Choubisa1, Md Azimul Haque2, Tong Zhu1

  • 1Department of Electrical and Computer Engineering University of Toronto, Toronto, Ontario, M5S 3G8, Canada.

Advanced materials (Deerfield Beach, Fla.)
|June 28, 2023
PubMed
概括

研究人员开发了一种错误校正学习 (ECL) 策略,以加快新热电材料的发现. 这种方法显著减少了找到优化材料所需的实验,比如新的PbSe:SnSb家族.

关键词:
封闭循环的封闭循环.错误纠正学习的学习方法机器学习是机器学习.热电学 热电学 热电学

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科学领域:

  • 材料科学 材料科学 材料科学
  • 固态物理 固态物理
  • 计算材料科学科学 计算材料科学

背景情况:

  • 发现新的热电材料是复杂的,因为大量的材料组合,兴奋剂的可能性,和合成方法.
  • 传统的高通量选方法,即使是先进的机器学习 (ML),也面临着适应合成和表征变化的挑战.

研究的目的:

  • 开发和应用一个错误校正学习 (ECL) 策略,以实现高效的热电材料发现.
  • 优先考虑在300°C以下的温度下进行材料合成.
  • 识别新型热电材料家族并优化其性能.

主要方法:

  • 整合历史数据和代改进使用实验反通过ECL.
  • 调整ML模型以考虑合成和表征变化.
  • 闭环实验策略侧重于低温 (<300°C) 合成.

主要成果:

  • 一个新的热电材料家族的识别:PbSe与SnSb.合.
  • 优化的材料,2重%的SnSb合PbSe,其功率系数是纯PbSe的两倍以上.
  • 与标准的ML驱动的高通量搜索相比,闭环策略将实验数量减少了多达3倍.

结论:

  • 错误纠正学习 (ECL) 与闭环实验相结合,显著加速了热电材料的发现.
  • 效率的提升是显著的,特别是当ML模型的准确性达到某个值,之后实验路径优化变得关键.