Paper Chromatography Experiment | Interactive Chemistry model

Run the chromatography experiment

Solvent front (cm) Red component (cm) Blue component (cm) Yellow component (cm)

Red component Blue component Yellow component --- solvent front

Red Rf—

Blue Rf—

Yellow Rf—

Travels furthest—

Strongest attraction to paper—

Strongest attraction to solvent—

Component	Distance (cm)	Rf	Relative behaviour

Interpretation: A component with a larger Rf value travels further with the solvent under the same experimental conditions. This generally indicates relatively stronger attraction to the mobile phase and/or weaker attraction to the stationary phase. A smaller Rf indicates greater retention by the stationary phase. Rf values should only be compared meaningfully when experimental conditions are the same.

Explore Paper Chromatography

Change the distances travelled by the separated substances and calculate their retention factors. Observe how the location of each spot on the chromatogram corresponds to its Rf value.

The solvent front must travel farther than each separated component because an Rf value cannot normally exceed 1.

import matplotlib.pyplot as plt

# Paper chromatography measurements
solvent_front = 10.0

components = {
    "Red": 8.2,
    "Blue": 5.4,
    "Yellow": 2.8
}

# Calculate Rf values
rf_values = {}

for name, distance in components.items():
    rf = distance / solvent_front
    rf_values[name] = rf

    print(
        name,
        "distance =",
        distance,
        "cm, Rf =",
        round(rf, 3)
    )

# Identify components
furthest = max(
    components,
    key=components.get
)

least_distance = min(
    components,
    key=components.get
)

print()
print(
    "Travels furthest:",
    furthest
)

print(
    "Most retained by paper:",
    least_distance
)

# Draw a simple chromatogram
x_positions = [1, 2, 3]

plt.figure(figsize=(6, 7))

# Origin line
plt.axhline(
    0,
    linestyle="--",
    label="Origin"
)

# Solvent front
plt.axhline(
    solvent_front,
    linestyle="--",
    label="Solvent front"
)

for x, (name, distance) in zip(
    x_positions,
    components.items()
):
    plt.scatter(
        x,
        distance,
        s=150,
        label=(
            name
            + " Rf="
            + str(round(
                rf_values[name], 2
            ))
        )
    )

plt.xlim(0.5, 3.5)
plt.ylim(-0.5, solvent_front + 1)
plt.xticks(
    x_positions,
    components.keys()
)
plt.ylabel(
    "Distance travelled (cm)"
)
plt.title(
    "Paper Chromatography"
)
plt.legend()
plt.grid(axis="y")
plt.show()

Paper Chromatography Python Model

This Python model calculates Rf values from experimental measurements and plots the positions of separated components. Change the distances and compare the Python output with the interactive chromatogram.