Macromolecular Reaction Engineering最新文献

The free-radical polymerization behavior of methyl methacrylate (MMA) is investigated in the presence and absence of trisilanol isobutyl polyhedral oligomeric silsesquioxane (TSI-POSS) at 70°C and 80°C using a calorimetric approach based on continuous temperature monitoring. The reaction temperature is experimentally recorded, and the corresponding heat flow is estimated from an energy balance, enabling the calculation of monomer conversion and polymerization rate (R_p) as functions of time. The experimental data are further analyzed to estimate the k_t/k_p² ratio (ratio of the termination to the squared propagation rate coefficients), which serves as a comparative indicator of changes in the balance between termination and propagation. The results reveal a non-monotonic evolution of the k_t/k_p² ratio, characterized by an initial decrease followed by an increase and a subsequent decline, suggesting behavior consistent with diffusion-controlled polymerization regimes. The presence of TSI-POSS is associated with a decrease in the polymerization rate and an increase in the k_t/k_p² ratio, suggesting the influence of diffusion-related limitations on the polymerization process. These observations are qualitatively consistent with diffusion-related effects, although independent characterization would be required to confirm the underlying mechanisms.

Polymer reaction kinetics link chemical mechanisms to the evolving polymer microstructure, but describing structural statistics efficiently remains challenging: population-balance models may become intractable, while chain-based Monte Carlo (MC) simulations can be computationally demanding. We review and formalize reaction-related observables (RROs), implemented as cumulative counters—massless, non-chemical entities that record reaction events such as monomer incorporation, branching, scission, and network-forming steps without affecting the mass balances. RROs extend deterministic rate-equation models by embedding event statistics directly into the kinetic framework, providing compact, interpretable observables and enabling reduced descriptions that remain easy to extend across model variants. We illustrate how counter-based evaluations can be used to construct derived structural indicators and heuristic structure–property relations, including examples for crosslinking networks.

Size-exclusion chromatography (SEC) analysis of polymers with nontrivial architectures presents specific challenges, seeing its separation of macromolecules by variations in hydrodynamic volume rather than true molar mass. Care should thus be taken with respect to calibration and detection strategies, with a coupling to (i) other higher scale experimental tools (e.g. rheology), and (ii) modeling techniques worthwhile in view of a detailed molecular characterization at the distributed level. We here formulate a first set of guidelines for improving SEC-based characterization, putting forward the relevance of detailed experimental data recording and error analysis as well as in silico characterization support. We consider both linear homopolymers, copolymers, branched and crosslinked polymers, and highlight that within the polymer community we should further work on the even better embedding of multi-detector approaches and advanced modeling techniques such as kinetic Monte Carlo. Overall this work supports the development of robust workflows for the analysis of advanced polymer materials, bridging the worlds of experimentalists and modelers.

In this work, we present a new class of silane chain-transfer agents (CTAs) for the molecular weight and the molecular weight distribution control during the production of low-density polyethylene (LDPE). These silanes exhibit a wide range of chain-transfer propensity as measured by their C_s values (the ratio of the rate coefficient for hydrogen abstraction and ethylene propagation, k_h/k_p) with the best performers being tris(trimethylsilyl)silane (C_s = 16.0) and trimethylsilylsilane (C_s = 15.7). Density functional theory (DFT) calculations were used to estimate the C_s values. The quantum chemical calculations were validated by pilot-plant experiments for triethylsilane (C_s = 0.22) and tris(trimethylsilyl)silane (C_s = 36.5). Given the expected variability in the pilot-plant data, an excellent agreement between theory and experiment was achieved. Furthermore, a model utilizing the DFT calculated Mulliken charge on the silicon atom to predict the C_s value was developed to facilitate silane screening in the future.

This work presents a dynamic, model-based kinetic measurement method that couples vapor-liquid-equilibrium with reaction kinetics for the bulk-phase polymerization of propylene in a bench-scale reactor. This model couples Peng-Robinson‑based flash calculations with a simplified kinetic scheme (activation, propagation, deactivation). Reactor pressure-time trajectories from polymerizations (at 20°C–30°C) are used as model input. The novelty of this approach lies in explicitly embedding vapor-liquid equilibrium into the dynamic pressure‑based calibration of polymerization kinetics under bulk pre‑polymerization conditions. Through the process of parameter tuning, the simulated and measured reactor pressure drop caused by conversion of liquid propylene to polypropylene in a multi-component mixture are aligned, yielding the simulated polymerization rate and the elementary reaction rate constants. The model reproduces the characteristic pressure decrease and end-point yields within acceptable deviations and demonstrates instantaneous catalyst activity profiles, the activity decay over reaction time, and the temperature response of the catalyst. This approach enables access to detailed catalytic polymerization kinetics of propylene at mild temperatures which are typically used under industrial pre-polymerization reactors.