Entropy and spontaneity

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Nature of science:

Theories can be superseded—the idea of entropy has evolved through the years as a result of developments in statistics and probability. (2.2)

Understandings:
  • Entropy (S) refers to the distribution of available energy among the particles. The more ways the energy can be distributed the higher the entropy.
  • Gibbs free energy (G) relates the energy that can be obtained from a chemical reaction to the change in enthalpy (ΔH), change in entropy (ΔS), and absolute temperature (T).
  • Entropy of gas>liquid>solid under same conditions.

Applications and skills:

  • Prediction of whether a change will result in an increase or decrease in entropy by considering the states of the reactants and products.
  • Calculation of entropy changes (ΔS) from given standard entropy values (S°) .
  • Application of ∆G° = ∆H° - T∆S° in predicting spontaneity and calculation of various conditions of enthalpy and temperature that will affect this.
  • Relation of ΔG to position of equilibrium.

Guidance:

  • Examine various reaction conditions that affect ΔG.
  • ΔG is a convenient way to take into account both the direct entropy change resulting from the transformation of the chemicals, and the indirect entropy change of the surroundings as a result of the gain/loss of heat energy.
  • Thermodynamic data is given in section 12 of the data booklet.
International-mindedness:
  • Sustainable energy is a UN initiative with a goal of doubling of global sustainable energy resources by 2030.

Theory of knowledge:

  • Entropy is a technical term which has a precise meaning. How important are such technical terms in different areas of knowledge?

Utilization:
Syllabus and cross-curricular links:
Topic 5.2—Hess’s Law
Topic 5.3—bond enthalpy
Topic 7.1—equilibrium
Option C.1—quality of energy
Physics option B.2—thermodynamics
Aims:

  • Aims 1, 4 and 7: Use of databases to research hypothetical reactions capable of generating free energy.
  • Aim 6: Experiments investigating endothermic and exothermic processes could be run numerous times to compare reliability of repetitive data and compare to theoretical values.

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