Hauptseite > Publikationsdatenbank > The Initiation Mechanism of Butadiene Polymerization in Aliphatic Hydrocarbons: A Full Mechanistic Approach > print |
001 | 817897 | ||
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100 | 1 | _ | |a Lühmann, Nicole |0 P:(DE-Juel1)144193 |b 0 |e Corresponding author |
245 | _ | _ | |a The Initiation Mechanism of Butadiene Polymerization in Aliphatic Hydrocarbons: A Full Mechanistic Approach |
260 | _ | _ | |a Washington, DC |c 2016 |b Soc. |
336 | 7 | _ | |a article |2 DRIVER |
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520 | _ | _ | |a An in situ 1H NMR study has been carried out to examine the anionic initiation mechanism of 1,3-butadiene and tert-butyllithium (t-BuLi) using n-heptane as solvent. Additionally, mixtures of model compounds have been investigated ex situ to simulate very early stages of polymerization. The analysis of the NMR spectra in combination with density functional theory (DFT) calculations proves the coexistence of cross-aggregates of t-BuLi and initiated chains and their crucial role for the initiation mechanism. From the low concentrations of these species showing a characteristic maximum at t ≈ 50 min and the increase of the overall initiation rate constant with ongoing initiation, we propose a double-stage autocatalytic mechanism for this process. We first assume a fairly small reactivity of butadiene and t-BuLi, which exists under these reaction conditions as a tetrameric aggregate. However, after the reaction of the first t-BuLi unit with a monomer molecule, the reactivity of the remaining three t-BuLi units in the aggregate is increased considerably. The crucial second step of the autocatalytic mechanism is based on the unimer exchange between partially or fully initiated t-BuLi aggregates and the residual unreacted t-BuLi tetramers. As a result, the initiation rate constantly increases and leads to a sigmoidal consumption of initiator molecules during the polymerization. In addition, the time-dependent cross-aggregate concentrations are used as a benchmark for a full mechanistic approach compiling all literature assumptions. Numerical modeling allows a semiquantitative description of the data. |
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