Vapour Pressure of Liquid Solutions — Predicted 2026
AI-Predicted Question Angles for UPSC 2026
Calculation of Molar Mass of Non-Volatile Solute
highThis is a classic application of the relative lowering of vapour pressure, which is a colligative property. NEET frequently tests the ability to apply this formula ($P_A^0 - P_A / P_A^0 = X_B$) to find an unknown molar mass. It combines mole concept, solution concentration, and Raoult's Law, making it a comprehensive test of understanding. Expect variations in given data (masses, volumes, densities) requiring initial calculations to find moles.
Identification of Deviation Type from Intermolecular Forces/Thermodynamic Data
mediumInstead of directly asking for examples, NEET might provide a scenario describing intermolecular forces (e.g., 'A-B interactions are weaker than A-A and B-B') or thermodynamic data (e.g., '\Delta H_{mixing} > 0') and ask to identify the type of deviation (positive/negative) or the resulting vapour pressure behavior. This tests a deeper conceptual understanding beyond rote memorization of examples.
Properties of Azeotropes and their Formation
mediumQuestions on azeotropes, particularly distinguishing between minimum and maximum boiling azeotropes and their correlation with positive and negative deviations, are recurring. Students should be prepared to identify which type of deviation leads to which type of azeotrope and understand why they cannot be separated by fractional distillation. Examples like ethanol-water (minimum boiling) and nitric acid-water (maximum boiling) are often used.
Vapour Pressure of a Solution with Two Volatile Components
mediumProblems involving the calculation of total vapour pressure using $P_{total} = X_A P_A^0 + X_B P_B^0$ are common. These questions test the direct application of Raoult's Law for ideal solutions containing multiple volatile components. They might also extend to calculating the composition of the vapour phase using Dalton's Law of Partial Pressures ($Y_A = P_A / P_{total}$), adding another layer of complexity.