Pore Size Distribution
Chart overview
Pore size distributions (PSDs) derived from N2 adsorption/desorption isotherms using the BJH or DFT method are fundamental for characterizing mesoporous materials including zeolites, metal-organic frameworks, aerogels, and porous carbons.
Key points
- The distribution reveals the dominant pore diameter, pore volume, and uniformity, while the isotherm shape (Types I-VI) identifies the pore structure.
- BET surface area and PSD together determine catalytic activity, gas storage capacity, drug loading in drug delivery systems, and filtration performance.
Python Tutorial
How to create a pore size distribution in Python
Use the full tutorial for implementation details, troubleshooting, and chart variations in matplotlib, seaborn, and plotly.
How to Plot a Histogram in PythonExample Visualization
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Generate publication-ready pore size distributions with AI in seconds. No coding required – just describe your data and let AI do the work.
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"Create a publication-quality pore size distribution plot from my BET/BJH adsorption data. Plot differential pore volume dV/dD (cm^3/g/nm) on the y-axis versus pore diameter (nm) on the x-axis. Annotate the dominant pore diameter at the peak maximum. Optionally include a second panel with the full N2 adsorption-desorption isotherm (P/P0 on x-axis, quantity adsorbed on y-axis) with adsorption and desorption branches in different colors. Add axis labels with units, BET surface area and total pore volume as an annotation, and a descriptive title."
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Python Code Example
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Figure saved: plotivy-pore-size-distribution.png
Common Use Cases
- 1Characterizing mesoporous silica (SBA-15, MCM-41) for drug delivery and catalysis
- 2Evaluating activated carbon pore networks for CO2 capture and gas storage
- 3Assessing MOF porosity and comparing experimental versus theoretical surface areas
- 4Optimizing synthesis conditions for controlled pore size in templated materials
Pro Tips
Plot both adsorption and desorption branches of the isotherm with distinct markers
Use a logarithmic pore diameter axis to resolve both micro- and mesopore features
Annotate the BET surface area, total pore volume, and average pore diameter as a text box
Overlay multiple samples in the same PSD plot with distinct colors for direct comparison
Long-tail keyword opportunities
High-intent chart variations
Library comparison for this chart
matplotlib
Best when you need full control over axis formatting, annotation placement, and journal-specific styling for pore-size-distribution.
numpy
Useful in specialized workflows that complement core Python plotting libraries for pore-size-distribution analysis tasks.
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