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21-Mat-A3 Structure and Characterization of Materials · Dec-12-Mtl-A3 2018

Question 7 of 8

Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)

Notes on this paper

Paper format. National Exams, December 2018 — 12-Mtl-A3, Structure and Characterization of Materials. Three hours, open book, any non-communicating calculator permitted. Eight questions constitute a complete exam paper; all eight are solved here.

Reference texts. The answers below are keyed to the standard undergraduate materials-science references recommended for this syllabus code:

Question 7 (20 marks)

Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.

Part (a) — copolymer architectures. A copolymer contains two (or more) distinct repeat-unit (mer) types, denoted here A and B, arranged along the chain in one of several characteristic patterns:

Part (b) Given.

QuantityValue
Number-average degree of polymerization, $\bar X_n$2500
Weight-average degree of polymerization, $\bar X_w$2000
Number-average molecular weight, $\bar M_n$81,500 g/mol
Weight-average molecular weight, $\bar M_w$67,200 g/mol

Find. Whether this data set can describe a real random poly(ethylene-propylene) copolymer.

Approach. Check whether the stated averages satisfy the one relationship that must always hold for any real molecular-weight distribution: $\bar M_w\geq\bar M_n$ (equivalently $\bar X_w\geq\bar X_n$), before even considering the ethylene/propylene composition.

  1. Test the fundamental inequality. For any distribution of chain lengths, the weight average is a second-moment (variance-weighted) average and the number average is a first-moment (simple) average; it is a basic statistical identity that $\bar M_w/\bar M_n = \bar X_w/\bar X_n = \text{PDI}\geq1$, with equality only for a perfectly monodisperse (every chain identical) sample. Checking the given numbers: $$\text{PDI (from }X\text{)} = \frac{\bar X_w}{\bar X_n} = \frac{2000}{2500} = 0.80$$ $$\text{PDI (from }M\text{)} = \frac{\bar M_w}{\bar M_n} = \frac{67{,}200}{81{,}500} = 0.825$$
  2. Conclusion. Both computed ratios are less than 1, which is impossible for any real polymer sample — a weight-average value can never fall below the corresponding number-average value, regardless of composition or copolymer architecture. $$\boxed{\text{Not possible: both stated PDIs} < 1}$$
  3. Cross-check for completeness (not the deciding factor, but consistent). The implied average mer masses, $\bar M_n/\bar X_n=81{,}500/2500=32.6$ g/mol and $\bar M_w/\bar X_w=67{,}200/2000=33.6$ g/mol, both fall sensibly between pure polyethylene's mer mass (28.05 g/mol) and pure polypropylene's (42.08 g/mol) — e.g. 32.6 g/mol implies about 32% propylene by mole fraction — so the composition numbers alone look plausible. The data set is rejected purely on the $\bar M_w\geq\bar M_n$ statistical requirement, independent of whether the implied composition is chemically reasonable.
CheckResult
$\bar X_w/\bar X_n$0.80 (must be $\geq1$)
$\bar M_w/\bar M_n$0.825 (must be $\geq1$)
Possible?No — violates $\bar M_w\geq\bar M_n$