Degree of Polymerization Calculator
Calculate number-average and weight-average degree of polymerization from molecular weight data.
Why Polymers Need Two Molecular Weights
A polymer sample is not one molecule repeated — it is a distribution of chain lengths. Two averages are therefore needed, and their ratio characterises how broad the distribution is.
| Average | Weights by | Sensitive to | Measured by |
|---|---|---|---|
| Mn (number) | Number of chains | Short chains | Osmometry, end-group analysis |
| Mw (weight) | Mass of chains | Long chains | Light scattering |
| Mz (z-average) | Higher mass moment | Very long chains | Ultracentrifugation |
Because Mw weights long chains more heavily, it is always at least as large as Mn. PDI is therefore always ≥ 1, and equals exactly 1 only for a perfectly uniform sample — which in practice occurs only for proteins and DNA, where synthesis is template-directed.
| PDI | Distribution | Typical origin |
|---|---|---|
| 1.0 | Monodisperse | Proteins, DNA |
| 1.02–1.1 | Very narrow | Living anionic, RAFT, ATRP |
| 1.5–2.0 | Moderate | Step-growth polymerisation |
| 2–5 | Broad | Free radical polymerisation |
| > 10 | Very broad | Branched, e.g. LDPE |
Distribution breadth matters practically. Short chains act as plasticisers, softening the material and lowering its melting range; very long chains raise melt viscosity and complicate processing. Two samples with identical Mn but different PDI behave quite differently.
Worked Examples
Common Mistakes
Mw is always at least Mn because it weights heavier chains more. A calculated PDI under 1 means the input values are wrong.
Xn is defined from Mn, the number average. Using Mw overstates chain length substantially for broad distributions.
For precise work, Mn includes the initiator and terminator fragments. For long chains this is negligible, but for oligomers it matters.
Narrow distribution is not always better. Some applications need a broad distribution for processability, where short chains aid flow.
Frequently Asked Questions
Formula Explorer connections
Interpretation: This formula connects molecular properties, material structure or environmental transport to a macroscopic behavior or exposure estimate. Assumption: Use parameters measured for the same material, solvent, temperature and environment. Empirical correlations may not transfer outside their calibration range.