Chapter 11: Problem 36
Vapor pressure measurements at several different temperatures are shown for mercury. Determine graphically the molar heat of vaporization for mercury. $$ \begin{array}{lccccc} T\left({ }^{\circ} \mathrm{C}\right) & 200 & 250 & 300 & 320 & 340 \\ \hline P(\mathrm{mmHg}) & 17.3 & 74.4 & 246.8 & 376.3 & 557.9 \end{array} $$
Short Answer
Step by step solution
Convert Temperatures to Kelvin
Calculate Natural Logarithm of Pressures
Plot ln(P) Against 1/T
Determine Slope of the Line
Calculate the Molar Heat of Vaporization
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Clausius-Clapeyron Equation
- \(P\) is the vapor pressure of the substance.
- \(\Delta H_{vap}\) represents the molar heat of vaporization.
- \(R\) is the ideal gas constant, valued at 8.314 J/mol·K.
- \(T\) is the absolute temperature in Kelvin.
- \(C\) is a constant that depends on the substance and its state.
Natural Logarithm
- It is the power to which \(e\) must be raised to obtain a given number.
- Converting pressure to its natural logarithm helps interpret non-linear relationships.
- Using \(\ln\) makes equations more manageable for calculations.
Kelvin Conversion
- If the temperature is 200°C, converting to Kelvin would result in a temperature of 473.15 K.
- This conversion is critical, especially when applying the Clausius-Clapeyron equation, which requires absolute temperatures for accuracy.
Vapor Pressure
- It increases with temperature because more molecules have enough energy to escape into the vapor phase.
- Vapor pressure is unique to each substance and varies depending on molecular interactions and temperature.
- Vapor pressure data at various temperatures support analyzing and understanding heat of vaporization calculations.
Graphical Analysis
- Visually represents the data and highlights the linear relationship between \(\ln P\) and \(1/T\).
- The slope of the line indicates the heat of vaporization, serving as a practical tool for calculations.
- It helps detect any anomalies or deviations in the underlying data, ensuring accuracy.