通过具有非马尔可夫效应的粒子波动实现聚合物晶体的初级成核

IF 5.1 1区 化学 Q1 POLYMER SCIENCE Macromolecules Pub Date : 2024-06-18 DOI:10.1021/acs.macromol.4c00438
Renkuan Cao, Fan Peng, Cui Nie, Yunhan Zhang, Hao Sun, Ziwei Liu, Tingyu Xu* and Liangbin Li*, 
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引用次数: 0

摘要

数十年来,围绕聚合物晶体一次成核过程中的前序的争论一直吸引着科学家。通过构建圆柱阶次参数(COP),我们在聚合物结晶的分子动力学模拟中观察到了前序-结晶两步成核过程。与经典成核理论(CNT)假定的无定形区和结晶区之间的尖锐界面不同,我们观察到的 COP 曲线呈梯度变化,随着晶核尺寸的增大,COP 值也随之增大。在成核动力学中,我们偏离了 CNT 所描述的马尔可夫过程,即单个粒子无记忆地附着到核上并从核上脱离。相反,我们发现成核是通过具有记忆效应的粒子波动发生的,而这种记忆效应会随着核尺寸的增大而增强,从而导致正反馈。这种通过具有记忆效应的粒子波动成核的机制从根本上不同于 CNT 和以前的非经典成核模型,为理解聚合物的成核提供了一个新的视角。
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Primary Nucleation of Polymer Crystal via Particles Fluctuation with Non-Markovian Effect

The debate surrounding preorders in the primary nucleation of polymer crystals has captivated scientists for decades. By constructing a cylindrical order parameter (COP), we observe a preordering-crystallization two-step nucleation process in a molecular dynamics simulation of polymer crystallization. Instead of the sharp interface between amorphous and crystalline regions assumed by classical nucleation theory (CNT), we observe a gradient COP profile that shifts toward higher COP values as the nucleus size increases. In nucleation dynamics, we depart from the Markov process described in the CNT, where single particles attach to and detach from nuclei without memory. Instead, we find that nucleation occurs through particle fluctuations with a memory effect, which is enhanced as the nucleus size increases, leading to positive feedback. This mechanism of nucleation via particle fluctuations with memory effect fundamentally diverges from CNT and previous nonclassical nucleation models, offering a new perspective on understanding the nucleation of polymers.

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来源期刊
Macromolecules
Macromolecules 工程技术-高分子科学
CiteScore
9.30
自引率
16.40%
发文量
942
审稿时长
2 months
期刊介绍: Macromolecules publishes original, fundamental, and impactful research on all aspects of polymer science. Topics of interest include synthesis (e.g., controlled polymerizations, polymerization catalysis, post polymerization modification, new monomer structures and polymer architectures, and polymerization mechanisms/kinetics analysis); phase behavior, thermodynamics, dynamic, and ordering/disordering phenomena (e.g., self-assembly, gelation, crystallization, solution/melt/solid-state characteristics); structure and properties (e.g., mechanical and rheological properties, surface/interfacial characteristics, electronic and transport properties); new state of the art characterization (e.g., spectroscopy, scattering, microscopy, rheology), simulation (e.g., Monte Carlo, molecular dynamics, multi-scale/coarse-grained modeling), and theoretical methods. Renewable/sustainable polymers, polymer networks, responsive polymers, electro-, magneto- and opto-active macromolecules, inorganic polymers, charge-transporting polymers (ion-containing, semiconducting, and conducting), nanostructured polymers, and polymer composites are also of interest. Typical papers published in Macromolecules showcase important and innovative concepts, experimental methods/observations, and theoretical/computational approaches that demonstrate a fundamental advance in the understanding of polymers.
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