81. For systems in which no termination is involved, as in the case of ‘Living Polymers’, an expression for the degree of polymerization can be found on the basis of:
1. The entire quantity of the initiator dissociation at the same time
2. All the anions formed by the dissociation initiative chain growth essentially simultaneously
3. All the anion compete equally for the monomer and the monomer is consumed more or less equally by all the anions
4. The entire quantity of the monomer dissociation at the same time
2. All the anions formed by the dissociation initiative chain growth essentially simultaneously
3. All the anion compete equally for the monomer and the monomer is consumed more or less equally by all the anions
4. The entire quantity of the monomer dissociation at the same time
(a) 1, 3 and 4 only
(b) 1, 2 and 4 only
(c) 2, 3 and 4 only
(d) 1, 2 and 3 only
(b) 1, 2 and 4 only
(c) 2, 3 and 4 only
(d) 1, 2 and 3 only
Answer: (d)
82. Consider the following statements regarding polymerization:
1. A high degree of polymerization can be achieved only at very low conversions and low temperatures
2. A high degree of polymerization can be achieved only at very high conversions
3. It is essential to start with exactly equimolar quantities of the reactants to achieve a high degree of polymerization
4. The presence of monofunctional impurities drastically reduces the degree of polymerization
1. A high degree of polymerization can be achieved only at very low conversions and low temperatures
2. A high degree of polymerization can be achieved only at very high conversions
3. It is essential to start with exactly equimolar quantities of the reactants to achieve a high degree of polymerization
4. The presence of monofunctional impurities drastically reduces the degree of polymerization
Which of the above statements are correct?
(a) 1, 2 and 3 only
(b) 1, 2 and 4 only
(c) 2, 3 and 4 only
(d) 1, 3 and 4 only
(a) 1, 2 and 3 only
(b) 1, 2 and 4 only
(c) 2, 3 and 4 only
(d) 1, 3 and 4 only
Answer: (c)
83. The average degree of polymerization D𝑝 can be correlated as:
1. D𝑝=2𝑣, when termination occurs by coupling
2. D𝑝=2𝑣/𝑁 , when termination occurs by coupling and disproportionation
3. D𝑝=𝑣, when termination occurs by disproportionation
4. D𝑝=𝑣/𝑁 , when termination occurs by disproportionation
1. D𝑝=2𝑣, when termination occurs by coupling
2. D𝑝=2𝑣/𝑁 , when termination occurs by coupling and disproportionation
3. D𝑝=𝑣, when termination occurs by disproportionation
4. D𝑝=𝑣/𝑁 , when termination occurs by disproportionation
Which of the above statements are correct?
(a) 1, 2 and 3 only
(b) 1, 2 and 4 only
(c) 1, 3 and 4 only
(d) 2, 3 and 4 only
(a) 1, 2 and 3 only
(b) 1, 2 and 4 only
(c) 1, 3 and 4 only
(d) 2, 3 and 4 only
Answer: (c)
84. The kinetic chain length 𝑣 is:
![](data:image/png;base64,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)
Answer: (b)
85. The osmotic pressure (𝜋) of a polymer solution is related to the number-average molecular weight of the polymer by the relation:
![](data:image/png;base64,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)
Answer: (a)
86. Dilatometric method is used to measure:
(a) Viscosity
(b) Atoms
(c) Expansion of coefficient of sample
(d) Accurate measurements of dimensional changes of polymeric samples
(a) Viscosity
(b) Atoms
(c) Expansion of coefficient of sample
(d) Accurate measurements of dimensional changes of polymeric samples
Answer: (c)
87. Which one of the following is used as the chain modifier in order to control the molecular weight in polymerization of butadiene?
(a) Zeigler-Natta catalyst
(b) Dodecyl mercaptan
(c) Polybutadienes
(d) Syndiotactic 1, 2-Polybutadiene
(a) Zeigler-Natta catalyst
(b) Dodecyl mercaptan
(c) Polybutadienes
(d) Syndiotactic 1, 2-Polybutadiene
Answer: (b)
88. Natural rubber is obtained in the form of latex from rubber tree called:
(a) Acacia nilotica
(b) Bauhinia retusa
(c) Hevea brasiliensis
(d) Holarrhena floribunda
(a) Acacia nilotica
(b) Bauhinia retusa
(c) Hevea brasiliensis
(d) Holarrhena floribunda
Answer: (c)
89. Ziegler-Natta catalysts are:
(a) Single-component organometallic compounds
(b) Initiators of polymer catalyst
(c) Special type of coordination catalyst
(d) Resonance-stabilized polymer catalyst
(a) Single-component organometallic compounds
(b) Initiators of polymer catalyst
(c) Special type of coordination catalyst
(d) Resonance-stabilized polymer catalyst
Answer: (c)
90. In Group Transfer Polymerization (GTP), which one of the following pair functions as group transfer catalyst?
(a) Ethyl trimethyl silyl acetate and trimethyl silyl cyanide
(b) 𝛼,𝛽-unsaturated esters and nitrites
(c) Ethyl methyl silyl cyanide and methyl ethyl silyl acetate
(d) Carbonamides silyl cyanide and ketene
(a) Ethyl trimethyl silyl acetate and trimethyl silyl cyanide
(b) 𝛼,𝛽-unsaturated esters and nitrites
(c) Ethyl methyl silyl cyanide and methyl ethyl silyl acetate
(d) Carbonamides silyl cyanide and ketene
Answer: (a)
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