Macromolecular Theory and Simulations最新文献

The discrete cosine transform (DCT) and Chebyshev series expansion (CSE) have the capability of approximating the functions with zero error at specific points known as nodes. Based on this property, this study introduces an isoconversional analysis method for complex reactions using the DCT or CSE models for the conversion function, applicable to both isothermal and nonisothermal conditions. The new method was applied to the kinetic data from simulated reactions as well as the thermal degradation of the polymer coating of an optical fiber. The results demonstrate that the DCT and CSE facilitate the calculation of kinetic parameters with very high accuracy. Notably, the conversion function and pre-exponential factor of complex multistage reactions, with multiple peaks in reaction rate curves, can be accurately estimated using the new approach. The GNU Octave/MATLAB codes have been made available to readers, enabling them to apply the novel method to their own kinetic data.

Brownian dynamics are used to investigate the scattering functions of ideal and excluded volume ring polymers in two to seven spatial dimensions. The scattering functions for ideal and excluded volume polymers examined are in very good agreement with theoretical predictions in all dimensions. As the dimension is increased, the scattering functions for the excluded volume rings converge toward the ideal results, although more slowly than in the case of linear polymers. These findings indicate that excluded volume rings behave more and more as ideal ones as the dimension gets larger, with dimension four being the cross-over point.

The understanding of molecular interactions and charge delocalization mechanisms under polythiophene system environments is essential to improving their catalytic function in energy and electronic capacities. In this study a more holistic computational research approach is used to assess the conformational dynamics and interfacial compatibility of polythiophene with different carbon nanomaterials: graphene, carbon nanotubes (CNTs), fullerene (C60), and carbon nanoparticles. Interaction energies (Eint) and structural conformations were evaluated using quantum mechanical density functional theory (DFT) and reactive force field (ReaxFF) simulations in Materials Studio to further rationalize electronic coupling and charge delocalization. Polythiophene–graphene interface exhibited a highly favorable interaction energy (−205.94 kJ/mol) among those studied, favoring π–π stacking and making charge transfer highly effective, with CNTs being the next most favorable (−39.11 kJ/mol) compared to fullerene (−25.29 kJ/mol) and carbon nanoparticles (−21.97 kJ/mol). These findings offer valuable molecular-level insights for the rational design of polythiophene-based catalytic composites, paving the way for improved performance in photocatalysis, electrocatalysis, and molecular electronics.

The recursive method of Miller and Macosko for calculating the average properties of linear and non-linear A + B step-growth polymers is extended to give formulae for the site- and weight-average functionality, and the site-average mass of a polymerising mixture at any extent of conversion of functional groups. These parameters are necessary for the calculation of the weight average molecular weight of polymer systems. All derived formulae are fully validated using the output of Stockmayer's equation, by means of two examples, one branched and one linear step growth polymer, which are then combined in a second stage to show the application of the new expressions to polymeric reactants in the pre-gel state, without the need for analytical expressions for chain length or functionality distributions. This second stage is also validated using Stockmayer's equation. The new formulae apply to any co-reactive chemistries used in step polymerization. In linear A₂ + B₂ step polymerization, processed to less than complete reaction, use of these new recursive relations yields a new, simpler method to identify the abundance of chains with minority A groups at both ends, chains with one A group and one B group, and chains with majority B groups at both ends.

Predicting the fatigue life of rubber components accurately has proven challenging, as existing methods often produce significant discrepancies compared to experimental results. This study presents a novel approach based on the combination of Abaqus and Endurica software, which can more accurately predict the fatigue life of rubber components, focusing on the impact of self-heating. To address this, we took a Carbon Black-Filled Natural lateral stop as an example, developed a thermo-mechanical coupling approach that incorporates temperature-dependent material parameters, derived by combining dynamic mechanical analysis tests and planar tension tests. This allowed us to capture the influence of temperature on the rubber's mechanical properties. Simulations incorporating self-heating effects demonstrated remarkable accuracy, with a maximum deviation of 15.6% from experimental data. This is a significant improvement compared to simulations neglecting self-heating, which exhibited a minimum deviation of 96.9%. This finding highlights the importance of considering self-heating effects in fatigue life prediction of rubber components. This approach has the potential to significantly enhance the durability and performance of rubber components across various applications by enabling more accurate predictions, leading to improved component design and longer service life.