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Flory–Schulz distribution

The Flory–Schulz distribution is a discrete probability distribution named after Paul Flory and Günter Victor Schulz that describes the relative ratios of polymers of different length that occur in an ideal step-growth polymerization process. The probability mass function (pmf) for the mass fraction of chains of length is:

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Flory–Schulz distribution
Probability mass function
Parameters 0 < a < 1 (real)
Support k ∈ { 1, 2, 3, ... }
PMF a 2 k ( 1 a ) k 1 {\displaystyle a^{2}k(1-a)^{k-1}}
CDF 1 ( 1 a ) k ( 1 + a k ) {\displaystyle 1-(1-a)^{k}(1+ak)}
Mean 2 a 1 {\displaystyle {\frac {2}{a}}-1}
Median W ( ( 1 a ) 1 a log ( 1 a ) 2 a ) log ( 1 a ) 1 a {\displaystyle {\frac {W\left({\frac {(1-a)^{\frac {1}{a}}\log(1-a)}{2a}}\right)}{\log(1-a)}}-{\frac {1}{a}}}
Mode 1 log ( 1 a ) {\displaystyle -{\frac {1}{\log(1-a)}}}
Variance 2 2 a a 2 {\displaystyle {\frac {2-2a}{a^{2}}}}
Skewness 2 a 2 2 a {\displaystyle {\frac {2-a}{\sqrt {2-2a}}}}
Excess kurtosis ( a 6 ) a + 6 2 2 a {\displaystyle {\frac {(a-6)a+6}{2-2a}}}
MGF a 2 e t ( ( a 1 ) e t + 1 ) 2 {\displaystyle {\frac {a^{2}e^{t}}{\left((a-1)e^{t}+1\right)^{2}}}}
CF a 2 e i t ( 1 + ( a 1 ) e i t ) 2 {\displaystyle {\frac {a^{2}e^{it}}{\left(1+(a-1)e^{it}\right)^{2}}}}
PGF a 2 z ( ( a 1 ) z + 1 ) 2 {\displaystyle {\frac {a^{2}z}{((a-1)z+1)^{2}}}}

The Flory–Schulz distribution is a discrete probability distribution named after Paul Flory and Günter Victor Schulz that describes the relative ratios of polymers of different length that occur in an ideal step-growth polymerization process. The probability mass function (pmf) for the mass fraction of chains of length k {\displaystyle k} is: w a ( k ) = a 2 k ( 1 a ) k 1 . {\displaystyle w_{a}(k)=a^{2}k(1-a)^{k-1}{\text{.}}}

In this equation, k is the number of monomers in the chain,1 and 0<a<1 is an empirically determined constant related to the fraction of unreacted monomer remaining.2

The form of this distribution implies is that shorter polymers are favored over longer ones — the chain length is geometrically distributed. Apart from polymerization processes, this distribution is also relevant to the Fischer–Tropsch process that is conceptually related, where it is known as Anderson-Schulz-Flory (ASF) distribution, in that lighter hydrocarbons are converted to heavier hydrocarbons that are desirable as a liquid fuel.

The pmf of this distribution is a solution of the following equation: { ( a 1 ) ( k + 1 ) w a ( k ) + k w a ( k + 1 ) = 0 , w a ( 0 ) = 0 , w a ( 1 ) = a 2 . } {\displaystyle \left\{{\begin{array}{l}(a-1)(k+1)w_{a}(k)+kw_{a}(k+1)=0{\text{,}}\\[10pt]w_{a}(0)=0{\text{,}}w_{a}(1)=a^{2}{\text{.}}\end{array}}\right\}} As a probability distribution, if X and Y are two independent and geometrically distributed random variables with parameter a {\displaystyle a} taking values in { 0 , 1 , } {\displaystyle \{0,1,\cdots \}} , then w a ( k ) = P ( X + Y + 1 = k ) {\displaystyle w_{a}(k)=\mathbb {P} \left(X+Y+1=k\right)} This in turn means that the Flory-Schulz distribution is a shifted version of the negative binomial distribution, with parameters r = 2 {\displaystyle r=2} and p = a {\displaystyle p=a} .

References

References

  1. Flory, Paul J. (October 1936). "Molecular Size Distribution in Linear Condensation Polymers". Journal of the American Chemical Society. 58 (10): 1877–1885. doi:10.1021/ja01301a016. ISSN 0002-7863.
  2. IUPAC, Compendium of Chemical Terminology, 5th ed. (the "Gold Book") (2025). Online version: (2006–) "most probable distribution". doi:10.1351/goldbook.M04035