Calculating Change in Entropy: 1.124J Heat Added to Gas at 300K [Solved]

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In summary, the problem involves adding 1.124J of heat to a gas at 300K, causing the temperature to increase to 600K. The change in entropy of the gas can be found using the equation Delta S = Q/T, where Q is the heat added and T is the absolute temperature. However, since this is a non-calculus based physics class, it is important to check with the teacher for the correct method of solving the problem. The correct solution to the integral is Delta S = (124/300)ln(2), which can be obtained by using the initial and final temperatures of the system in the equation.
  • #1
boburd21
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[SOLVED] Quick Entropy Problem

Homework Statement



1.124J of heat is added to a gas at 300K causing the temperature to increase to 600K. What is the change in entropy of the gas?

Homework Equations


(Delta)S=Q/T


The Attempt at a Solution



I know the simple equation i need. all i need to know is whether to use the Tfinal or the Tinitial in the equation.
Thanks
 
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  • #2
You are going to need to use the more general version of the equation you posted:

[tex]\Delta S = \int \frac{dQ}{T}[/tex]

Start the problem like so: Get dQ in terms of dT and then integrate with respect to T. What will your integral's bounds be in this case?
 
  • #3
Im in a non-calculus based physics class. Any ideas what the teacher would want in this case if integrating is not an option?
 
  • #4
O ok, well, I would assume you would use the initial temperature of the system, but you may want to check with your teacher, since I am not completely sure.
 
  • #5
thanks
 
  • #6
boburd21 said:
Im in a non-calculus based physics class. Any ideas what the teacher would want in this case if integrating is not an option?
If you use either the initial or final temperature, you will be wrong. If you are in a non-calculus class, your teacher should either be giving you the general solution to the integral (which I expect is the case) or not be giving you these kinds of questions. The correct solution to the integal is:

[tex]\Delta S = \int_{T_i}^{T_f}\frac{dQ}{T} = \int_{T_i}^{T_f}\frac{mC_vdT}{T} = mC_v(\ln{T_f} - \ln{T_i}) = mC_v\ln{\frac{{T_f}}{{T_i}}} = \frac{\Delta Q}{\Delta T}\ln{\frac{{T_f}}{{T_i}}} = \frac{124}{300}\ln{2}[/tex]

AM
 
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FAQ: Calculating Change in Entropy: 1.124J Heat Added to Gas at 300K [Solved]

1. What is the "Quick Entropy Problem"?

The "Quick Entropy Problem" is a mathematical puzzle that involves finding the minimum number of questions needed to determine a secret number within a given range. It is commonly used to demonstrate the concept of entropy, which measures the uncertainty or randomness of a system.

2. How do you solve the "Quick Entropy Problem"?

To solve the "Quick Entropy Problem", you can use a binary search algorithm. This involves dividing the range of numbers into two halves and asking a question that eliminates one half of the range with each guess. The number of questions needed to determine the secret number will depend on the size of the range.

3. What is the significance of the "Quick Entropy Problem" in science?

The "Quick Entropy Problem" is significant in science because it demonstrates the concept of entropy, which is a fundamental concept in thermodynamics, information theory, and other fields. It also highlights the importance of using efficient algorithms to solve problems with large amounts of uncertainty or randomness.

4. Can the "Quick Entropy Problem" be applied to real-world situations?

Yes, the "Quick Entropy Problem" can be applied to real-world situations such as cryptography, game theory, and decision-making processes. It can also be used to model natural phenomena like the spread of diseases or the behavior of financial markets.

5. Are there any limitations to the "Quick Entropy Problem"?

One limitation of the "Quick Entropy Problem" is that it assumes the secret number is located within a finite range and can be determined by asking yes or no questions. In real-world situations, the range may be infinite or the questions may not be limited to yes or no answers. Additionally, the algorithm used to solve the problem may not always result in the most efficient solution.

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