The former is statistical entropy and the latter is thermodynamic entropy. Statistical entropy is more general, while thermodynamic entropy is only defined for systems close to thermodynamic equilibrium. It can be shown (see the box in the link in the post above) that statistical entropy for systems close to thermodynamic equilibrium can be well approximated by thermodynamic entropy.James Brown said:In the definition of entropy, there are two. One is about the degree of randomness and one is about energy that is not available to do work. What is the relationship between them?
Entropy is a measure of the disorder or randomness in a system. It is important in science because it helps us understand the behavior of physical systems and how they change over time.
The two different definitions of entropy are thermodynamic entropy and information entropy. Thermodynamic entropy is a measure of the disorder in a physical system, while information entropy is a measure of the uncertainty or randomness in a set of data.
The two definitions of entropy are related in that they both measure the amount of disorder or randomness in a system. However, they use different mathematical equations and have different applications in science.
The second law of thermodynamics states that the total entropy of a closed system will always increase over time. This means that the disorder or randomness in a system will always tend to increase, rather than decrease.
Entropy is used in many practical applications, such as in thermodynamics, information theory, and statistical mechanics. It is also used in fields such as engineering, chemistry, and biology to understand and predict the behavior of complex systems.