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Simulation Studies on Dramatically Slow Dynamics of Glass-Forming Liquids and Seemingly Fickian but Heterogeneous Dynamics of a Single Particle in Various Ways

초록/요약

Understanding the fundamental dynamics of liquid particles is essential but complex. In glass-forming liquids, liquid particles experience a dramatic increase in viscosity upon glass transition, which is a transition from liquid to amorphous solid. There is, however, no consensus on the origin and the nature of the glass transition. From one point of view, this phenomenon is attributed to the kinetic trap because of the slow dynamics, on the other hand, another view point asserts that there is a structural motif related to the thermodynamics. In this work, we investigate the presence and the effect of the structural motif upon the glass transition using tracer dynamics, especially the translation-rotation decoupling behavior. In addition, this thesis deals with the seemingly Fickian but heterogeneous dynamics of a single particle. We try to explain this behavior using a memory kernel of a single brownian particle, and also investigate this interesting behavior in a polymer thin film. Chapter 1 deals with the translation-rotation decoupling of tracers in glass-forming liquids. Particles in glass-forming liquids may form domains of locally favorable structures (LFSs) upon supercooling. Whether and how the LFS domains would relate to the slow relaxation of the glass-forming liquids have been issues of interest. In this study, we employ tracers of which structures resemble the LFS domains in Wahnström and Kob-Andersen (KA) glass-forming liquids, and investigate the translation-rotation decoupling of the tracers. We find that the tracer structure affects how the translation and the rotation of tracers decouple, and that information on the local mobility around the LFS domains may be gleaned from the tracer dynamics. According to the Stokes-Einstein (SE) relation and the Debye-Stokes-Einstein (DSE) relation, the ratio of the translational (DT) and rotational (DR) diffusion coefficients is expected to be a constant over a range of T/η, where η and T denote the medium viscosity and temperature, respectively. In supercooled liquids and glasses, however, DT and DR decouple due to dynamic heterogeneity, thus DT/DR not being constant any more. In Wahnström glass-forming liquids, icosahedron LFS domains are the most long-lived ones and the mobility of neighbor particles around the icosahedron LFS domain is suppressed. We find from our simulations that the icosahedron tracers, similar in size and shape to the icosahedron LFS domains, experience drastic translation-rotation decoupling upon cooling. The local mobility of liquid particles around the icosahedron tracers is also suppressed significantly. On the other hand, tracers of FCC and HCP structures do not show translation-rotation decoupling in Wahnström liquid. In KA glass-forming liquids, bicapped square antiprism LFS domains are the most long-lived LFS domains but are not correlated significantly with the local mobility. We find from our simulations that DT and DR of bicapped square antiprism tracers, also similar in size and shape to the bicapped square antiprism LFS domains, do not decouple significantly similarly to tracers of other structures, thus reflecting that the local mobility would not be associated strongly with LFS domains in KA liquid. Chapter 2 deals with the effect of the memory kernel on investigating the seemingly Fickian yet non-Gaussian diffusion. Conventionally, diffusion processes can be explained by using the ensemble-averaged mean-squared displacement (MSD), ⟨Δx(t)^𝟤⟩, where x is the position of a particle. It is called as Fickian diffusion (normal diffusion) when MSD is linear with time t. At first sight, it is tempting to think that the non-Gaussian distribution of the particle distribution is followed by the Fickian diffusion. However, according to recent studies, many biological or active systems are observed to exhibit Fickian diffusion with non-Gaussian distribution. Often, this intriguing behavior is connected by the loss of the independence of random variables, dynamic heterogeneity, and so on. In this work, we try to explain this behavior using a memory kernel of a particle. Recent study suggested the effective algorithm to calculate memory kernel. Using the algorithm suggested, we calculate a memory kernel of a particle with hand-made code. To investigate the effect of the memory kernel, the simulation results from molecular dynamics (MD) are compared with the results through solving generalized lanvegin equation (GLE) using memory kernel as an input. In chapter 3, dynamics of a nanoparticle in a polymer thin film was investigated in molecular level. Adding nanoparticles (NPs) in soft materials is in great importance due to their practical properties on the applications. Recent study showed that the spatial distribution of NPs could affect the glass transition temperature significantly. Understanding the dynamics of nanoparticles microscopically, however, is not a trivial task because of the limited spatial resolution of experiment. In this work, we will perform molecular dynamic simulation using generic course-grained model for polymers and a single nanoparticle. To investigate the dynamics of a nanoparticle of various sizes in a polymer thin film, we calculate the self van Hove correlation function, Gs(r,t). We find that diffusion of NP in the surface is faster than the diffusion of NP in the center. Also, when the size of NP is smaller (larger) than σc, which is the critical size where the first order transition occurs, NP is likely to be located on the surface (center) and Gs(r,t) is Gaussian. As the size of NP approaches to σc, hopping motion along the axis perpendicular to the polymer film is shown and Gs(r,t) is non-Gaussian while Fickian diffusion is still observed.

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초록/요약

Chapter 1 동역학적 특성에 관해 연구하였다. 유리 형성 액체는 유리 온도 근처로 온도가 내려갈수록, 입자들의 움직임이 급격하게 느려지게 되는데, 이러한 느린 동역학적 특성의 물리적 원인이 아직도 잘 이해되지 않고 있다. 그리고 온도가 내려갈수록 빨리 움직이는 입자와 느리게 움직이는 입자가 공간적으로 불균일하게 분포하게 되며, 이러한 불균일한 동역학적 특성으로 인해 회전운동과 병진운동의 시간척도가 분리되는 현상(Translation-rotation decoupling)이 일어나게 된다. 유리 형성 액체는 유리 온도 근처로 온도가 내려갈수록 지엽적으로 선호되는 구조(locally favorable structures, LFS)를 가지는 지역을 형성한다. 이러한 LFS가 유리 형성 액체의 느린 동역학적 특성에 기여를 하는지, 그리고 어떻게 기여를 하는지에 대한 연구는 흥미로운 연구 주제이다. 본 연구에서는, 대표적인 두 유리 형성 액체 모델인, Wanhström 모델 유리 형성 액체와 Kob-Anderson(KA) 모델 유리 형성 액체를 사용하여, 그 속에서 일어나는 지엽적으로 선호되는 구조와 유사한 tracer의 decoupling 현상을 분자 동역학 시뮬레이션을 통해 알아보았다. 그 결과, 추적분자(tracer)의 Translation-rotation decoupling 현상이 사용한 모델에 따라, 그리고 tracer의 모양에 따라 달라진다는 것을 발견하였다. 본 연구를 통해, 서로 다른 모양의 tracer의 decoupling 현상을 관찰함으로서, 실험에서 분석하지 못하는 지엽적 구조가 그 지역의 느린 동역학적 특성에 미치는 영향을 분석할 수 있음을 밝혀낼 수 있었다. Chapter 2에서는 memory kernel이 흥미로운 확산 현상을 설명하는 데에 미치는 영향에 대해 연구하였다. 일반적으로, 확산 현상은 입자들의 평균 이동거리의 제곱을 나타내는 mean-squared displacement (MSD)를 통해 기술된다. 만약, 평균 이동거리의 제곱이 시간의 1승에 비례하게 된다면, 이러한 확산 현상은 Fickian 확산이라 불리며, 흔히 Fickian 확산을 하는 입자들의 이동거리에 대한 확률 분포는 Gaussian 분포를 따를 것이라고 예상된다. 하지만, 많은 생물학적 시스템에서 이러한 흥미로운 확산 현상이 관찰되어 왔다. 본 연구에서는 memory kernel을 이용해서 한 입자의 이러한 흥미로운 확산 현상을 기술하고자 하였다. Chapter 3에서는 얇은 고분자 필름에서 나노 입자의 동역학적 특성에 대해 연구하였다. 고분자 필름은 산업적으로 응용성이 높고 학문적으로 매우 흥미로운 주제이므로 다양한 분야에서 연구되고 있다. 고분자 필름에 나노 입자를 첨가하게 되면, 유리 전이 온도를 크게 변화시킬 수 있고, 첨가된 나노 입자의 크기에 따라 달라지는 나노 입자들의 분포 양상도 고분자 필름의 물리적 특성에 많은 영향을 미친다. 하지만, 크기가 매우 작은 나노 입자들의 공간 배향을 분석하는 것은 공간 분해능의 한계로 인해 실험적으로는 매우 어려운 일이다. 본 연구에서는, 얇은 고분자 필름에 크기가 서로 다른 나노 입자를 첨가하여 분자 동역학 시뮬레이션을 수행하였으며, 이를 통해 서로 다른 크기의 나노 입자의 분포에 따른 확산 현상을 비롯한 동역학적 특성을 분석하였다.

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