How to use the degree of polymerization calculator
Find how many repeat units are in a polymer chain from its average molar mass and repeat unit mass. Enter number average molar mass, repeat unit molar mass in the fields above; the degree of polymerization, check: molar mass from repeat units are computed instantly and plotted on the chart so you can see how the answer changes.
Common searches this calculator answers include “degree of polymerization”, “number of repeat units”, “polymer chain length”, “calculate degree of polymerization”, “find degree of polymerization”.
Formula
Variables
- Mn — Number average molar mass (g/mol)
- Mm — Repeat unit molar mass (g/mol)
Worked example
With number average molar mass = 50000 g/mol, repeat unit molar mass = 104.15 g/mol, the calculator gives degree of polymerization ≈ 480.0768; check: molar mass from repeat units ≈ 50,000 g/mol.
Frequently asked questions
What is the degree of polymerization calculator used for?
Find how many repeat units are in a polymer chain from its average molar mass and repeat unit mass. It helps with questions such as “degree of polymerization”, “number of repeat units”, “polymer chain length”.
What is the formula for the degree of polymerization calculation?
Degree of polymerization = Mn / Mm. Check: molar mass from repeat units (g/mol) = [Degree of polymerization] × Mm. Here Mn is number average molar mass (g/mol), Mm is repeat unit molar mass (g/mol).
What inputs do I need for the degree of polymerization calculator?
You need number average molar mass in g/mol, repeat unit molar mass in g/mol. Each field is pre-filled with a typical example so you can see how the result responds as you edit the numbers.
How do I use the degree of polymerization calculator?
Type values into the input fields. Results and the chart update instantly. Use Reset to restore the example values, Copy results to paste them elsewhere, or Share to copy a link that preserves your inputs.
Is the degree of polymerization result exact?
Calculations use standard formulas and double-precision arithmetic, then display about seven significant figures. Real-world measurements carry uncertainty, so treat results as estimates unless your inputs are exact.