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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?
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The heat capacity of a gas is the amount of heat energy required to raise the temperature of a unit mass of gas by one degree Celsius. It is an important thermodynamic property of gases, and its determination is essential in many industrial and scientific applications. Here are the steps to solve problems related to the heat capacities of gases:
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In convection, thermal energy is carried by the large-scale flow of matter. Ocean currents and large-scale atmospheric circulation, which result from the buoyancy of warm air and water, transfer hot air from the tropics toward the poles and cold air from the poles toward the tropics. The Earth’s rotation interacts with those flows, causing the observed eastward flow of air in the temperate zones. Convection dominates heat transfer by air, and the amount of available space for the airflow...
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When objects at different temperatures are placed in contact with each other but isolated from everything else, they attain thermal equilibrium. A container that prevents heat transfer in or out is called a calorimeter, and the use of a calorimeter to make measurements is called calorimetry. Generally, these measurements involve heat or specific heat capacity. The term "calorimetry problem" is used for any problem where the specified objects are thermally isolated from their...
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Heat transfer between the human body and its environment occurs through four main mechanisms: conduction, convection, radiation, and evaporation.
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Understanding heat transfer mechanisms is essential for understanding how our bodies maintain balance in different environmental conditions. When the environment is thermoneutral, the body is in a state of balance, neither using nor releasing energy to maintain its core temperature. However, when the environment is not thermoneutral, the body employs four heat transfer mechanisms to maintain homeostasis: conduction, convection, evaporation, and radiation. These mechanisms facilitate heat...
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Elastocaloric Thermal Battery: Ultrahigh Heat-Storage Capacity Based on Generative Learning-Designed Phase-Change

Pengfei Dang1, Jinlong Hu2, Yuehui Xian1

  • 1State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, 710049, China.

Advanced Materials (Deerfield Beach, Fla.)
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A novel elastocaloric thermal battery uses generative learning to design phase-change alloys for efficient low-temperature waste heat recycling. This innovative material design achieves superior heat storage and work-to-heat efficiency for diverse thermal energy applications.

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generative learninginverse designphase change alloythermal batterywaste heat recycling

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Area of Science:

  • Materials Science
  • Thermodynamics
  • Artificial Intelligence

Background:

  • Efficient recycling of low-temperature waste heat is crucial for energy sustainability.
  • Existing thermal batteries often lack sufficient heat storage capacity and efficiency.
  • Developing advanced materials for thermal energy storage remains a significant challenge.

Purpose of the Study:

  • To develop an elastocaloric thermal battery utilizing generative learning-designed phase-change alloys.
  • To enable efficient storage and on-demand release of thermal energy from low-temperature waste heat.
  • To accelerate the discovery of materials with tailored thermal properties using an inverse design framework.

Main Methods:

  • Generative learning-enabled inverse design framework for alloy discovery.
  • Tailoring alloy compositions and processing parameters for specific transformation characteristics.
  • Fabrication and testing of the elastocaloric thermal battery prototype.

Main Results:

  • Achieved an ultrahigh figure of merit for heat storage capacity, surpassing existing thermal batteries.
  • Demonstrated a work-to-heat efficiency exceeding 9%.
  • Successfully converted hand-drawn target heat flow curves into tangible material designs.

Conclusions:

  • The developed elastocaloric thermal battery offers a promising solution for low-temperature waste heat recycling.
  • The generative learning inverse design framework significantly expedites material development for tailored property curves.
  • Potential applications include solar thermal collection, electric vehicles, and data center thermal management.