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Understanding the Microstructural and Macroscopic Evolution of Dynamic Polymer Networks Through Coarse-grained Molecular Dynamics.
Understanding the Microstructural and Macroscopic Evolution of Dynamic Polymer Networks Through Coarse-grained Molecular Dynamics.

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자료유형  
 학위논문
Control Number  
0017161509
International Standard Book Number  
9798382232997
Dewey Decimal Classification Number  
621
Main Entry-Personal Name  
Shaswat Mohanty.
Publication, Distribution, etc. (Imprint  
[S.l.] : Stanford University., 2024
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2024
Physical Description  
188 p.
General Note  
Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
General Note  
Advisor: Wei Cai.
Dissertation Note  
Thesis (Ph.D.)--Stanford University, 2024.
Summary, Etc.  
요약Due to their dynamic cross-linking bonds, highly stretchable and self-healable supramolecular elastomers are promising materials for future soft electronics, biomimetic systems, self-healing plastics, and smart textiles. The dynamic or reversible nature of the cross-links gives rise to interesting macroscopic responses in these materials such as self-healing and rapid stress-relaxation. Here, self-healing refers to the ability of the material to recover its shape and properties in its pristine state after it undergoes significant mechanical deformation such as extensive loading or material rupture. On the other hand, stress-relaxation refers to the relieving of stress in the elastomer when held indefinitely under deformation, a process that is accelerated due to the presence of dynamic cross-links. Though these properties of dynamic polymer networks are well documented, the relationship between bond activity and macroscopic mechanical response, and the self-healing properties of these dynamic polymer networks (DPNs) remains poorly understood. This dissertation aims to understand the dependence of the macroscopic responses of dynamic polymer networks on their microstructural evolution by using a two-pronged approach. The first is to identify a microstructural descriptor that can explain the macroscopic evolution of stress and the state of the material. The second is to identify the multiscale dynamic processes that precisely estimate the stress-relaxation response.For the first prong of our approach, using coarse-grained molecular dynamics (CGMD) simulations, we reveal a fundamental connection between the macroscopic behaviors of DPNs and the shortest paths between distant nodes in the polymer network. Notably, the trajectories of the material on the shortest path-strain map provide key insights into understanding the stress-strain hysteresis, anisotropy, stress relaxation, and self-healing of DPNs. Based on CGMD simulations under various loading histories, we formulate a set of empirical rules that dictate how the shortest path interacts with stress and strain. This lays the foundation for developing a physics-based theory centered around the non-local microstructural feature of shortest paths to predict the mechanical behavior of DPNs. However, these statistics can be costly to compute and difficult to study theoretically. To this end, we introduce a branching random walk (BRW) model to describe the SP statistics from the CGMD model of polymer networks. We postulate that the first passage time (FPT) of the BRW to a given termination site can be used to approximate the statistics of the SP between distant nodes in the polymer network. We develop a theoretical framework for studying the FPT of spatial branching processes and obtain an analytical expression for estimating the FPT distribution as a function of the cross-link density. We demonstrate by extensive numerical calculations that the distribution of the FPT of the BRW model agrees well with the SP distribution from the CGMD simulations. The theoretical estimate and the corresponding numerical implementations of BRW provide an efficient way of approximating the SP distribution in a polymer network. Our results have the physical meaning that by accounting for the realistic topology of polymer networks, extensive bond-breaking is expected to occur at a much smaller stretch than that expected from idealized models assuming periodic network structures. Our work presents the first analysis of polymer networks as a BRW and sets the framework for developing a generalizable spatial branching model for studying the macroscopic evolution of polymeric systems. This analysis identifies the SP between distant cross-links as a key microstructural parameter that governs material evolution and presents a theoretically tractable framework within which the SP evolution estimates can be made.The second prong of our approach is aimed at reconstructing or predicting the exact nature of the stress-relaxation behavior of the DPNs. The stress relaxation response obtained experimentally or from our CGMD simulations exhibits similar stretched exponential or non-exponential decay, which implies the contribution of multiple dynamic processes occurring at different time scales. We first probe the bond-breaking rates by using the transition state theory under different cross-link densities and polymer melt configurations. However, this limits us to the time scale and the length scale associated with a single cross-link. To access the dynamics at different length scales and time scales we computationally model a powerful experimental dynamics characterization technique called X-ray photon correlation spectroscopy (XPCS). Interpretation of the XPCS data regarding underlying physical processes is necessary to establish the connection between the macroscopic responses and the microstructural dynamics. To aid the interpretation of the XPCS data, we present a computational framework to model these experiments by computing the X-ray scattering intensity directly from the atomic positions obtained from CGMD simulations. The time scale of the dynamics accessed by XPCS is controlled by the sampling frequency of the CGMD configurations whereas the size of the CGMD simulation cell controls the extent of the length scales accessed. By repeating the XPCS analysis at different sampling frequencies we can obtain the multiscale dynamics of the DPN simulated by the CGMD method. We found that the distribution of rates revealed by computational XPCS is consistent with the stretched exponential decay of the stress-relaxation response of the system.This dissertation presents a thorough analysis of the SP between distant cross-links as a microstructural descriptor that governs the macroscopically observed mechanical evolution (self-healing and rapid stress relaxation) of the DPN system. In addition, the XPCS analysis of the CGMD simulation trajectory is successful in uncovering the characteristic rates of the dynamic processes that accurately predict the rapid stress-relaxation exhibited by the DPNs. The methods presented in this dissertation to study the microstructural and dynamic evolution are applicable to a large class of elastomeric systems and can aid in the design of the next generation of smart elastomers.
Subject Added Entry-Topical Term  
Mechanical engineering.
Index Term-Uncontrolled  
Coarse-grained molecular dynamics
Index Term-Uncontrolled  
Dynamic polymer networks
Index Term-Uncontrolled  
Cross-linking bond
Index Term-Uncontrolled  
Supramolecular elastomer
Added Entry-Corporate Name  
Stanford University.
Host Item Entry  
Dissertations Abstracts International. 85-11B.
Electronic Location and Access  
로그인을 한후 보실 수 있는 자료입니다.
Control Number  
joongbu:658213

MARC

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■1001  ▼aShaswat  Mohanty.
■24510▼aUnderstanding  the  Microstructural  and  Macroscopic  Evolution  of  Dynamic  Polymer  Networks  Through  Coarse-grained  Molecular  Dynamics.
■260    ▼a[S.l.]▼bStanford  University.  ▼c2024
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2024
■300    ▼a188  p.
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  85-11,  Section:  B.
■500    ▼aAdvisor:  Wei  Cai.
■5021  ▼aThesis  (Ph.D.)--Stanford  University,  2024.
■520    ▼aDue  to  their  dynamic  cross-linking  bonds,  highly  stretchable  and  self-healable  supramolecular  elastomers  are  promising  materials  for  future  soft  electronics,  biomimetic  systems,  self-healing  plastics,  and  smart  textiles.  The  dynamic  or  reversible  nature  of  the  cross-links  gives  rise  to  interesting  macroscopic  responses  in  these  materials  such  as  self-healing  and  rapid  stress-relaxation.  Here,  self-healing  refers  to  the  ability  of  the  material  to  recover  its  shape  and  properties  in  its  pristine  state  after  it  undergoes  significant  mechanical  deformation  such  as  extensive  loading  or  material  rupture.  On  the  other  hand,  stress-relaxation  refers  to  the  relieving  of  stress  in  the  elastomer  when  held  indefinitely  under  deformation,  a  process  that  is  accelerated  due  to  the  presence  of  dynamic  cross-links.  Though  these  properties  of  dynamic  polymer  networks  are  well  documented,  the  relationship  between  bond  activity  and  macroscopic  mechanical  response,  and  the  self-healing  properties  of  these  dynamic  polymer  networks  (DPNs)  remains  poorly  understood.  This  dissertation  aims  to  understand  the  dependence  of  the  macroscopic  responses  of  dynamic  polymer  networks  on  their  microstructural  evolution  by  using  a  two-pronged  approach.  The  first  is  to  identify  a  microstructural  descriptor  that  can  explain  the  macroscopic  evolution  of  stress  and  the  state  of  the  material.  The  second  is  to  identify  the  multiscale  dynamic  processes  that  precisely  estimate  the  stress-relaxation  response.For  the  first  prong  of  our  approach,  using  coarse-grained  molecular  dynamics  (CGMD)  simulations,  we  reveal  a  fundamental  connection  between  the  macroscopic  behaviors  of  DPNs  and  the  shortest  paths  between  distant  nodes  in  the  polymer  network.  Notably,  the  trajectories  of  the  material  on  the  shortest  path-strain  map  provide  key  insights  into  understanding  the  stress-strain  hysteresis,  anisotropy,  stress  relaxation,  and  self-healing  of  DPNs.  Based  on  CGMD  simulations  under  various  loading  histories,  we  formulate  a  set  of  empirical  rules  that  dictate  how  the  shortest  path  interacts  with  stress  and  strain.  This  lays  the  foundation  for  developing  a  physics-based  theory  centered  around  the  non-local  microstructural  feature  of  shortest  paths  to  predict  the  mechanical  behavior  of  DPNs.  However,  these  statistics  can  be  costly  to  compute  and  difficult  to  study  theoretically.  To  this  end,  we  introduce  a  branching  random  walk  (BRW)  model  to  describe  the  SP  statistics  from  the  CGMD  model  of  polymer  networks.  We  postulate  that  the  first  passage  time  (FPT)  of  the  BRW  to  a  given  termination  site  can  be  used  to  approximate  the  statistics  of  the  SP  between  distant  nodes  in  the  polymer  network.  We  develop  a  theoretical  framework  for  studying  the  FPT  of  spatial  branching  processes  and  obtain  an  analytical  expression  for  estimating  the  FPT  distribution  as  a  function  of  the  cross-link  density.  We  demonstrate  by  extensive  numerical  calculations  that  the  distribution  of  the  FPT  of  the  BRW  model  agrees  well  with  the  SP  distribution  from  the  CGMD  simulations.  The  theoretical  estimate  and  the  corresponding  numerical  implementations  of  BRW  provide  an  efficient  way  of  approximating  the  SP  distribution  in  a  polymer  network.  Our  results  have  the  physical  meaning  that  by  accounting  for  the  realistic  topology  of  polymer  networks,  extensive  bond-breaking  is  expected  to  occur  at  a  much  smaller  stretch  than  that  expected  from  idealized  models  assuming  periodic  network  structures.  Our  work  presents  the  first  analysis  of  polymer  networks  as  a  BRW  and  sets  the  framework  for  developing  a  generalizable  spatial  branching  model  for  studying  the  macroscopic  evolution  of  polymeric  systems.  This  analysis  identifies  the  SP  between  distant  cross-links  as  a  key  microstructural  parameter  that  governs  material  evolution  and  presents  a  theoretically  tractable  framework  within  which  the  SP  evolution  estimates  can  be  made.The  second  prong  of  our  approach  is  aimed  at  reconstructing  or  predicting  the  exact  nature  of  the  stress-relaxation  behavior  of  the  DPNs.  The  stress  relaxation  response  obtained  experimentally  or  from  our  CGMD  simulations  exhibits  similar  stretched  exponential  or  non-exponential  decay,  which  implies  the  contribution  of  multiple  dynamic  processes  occurring  at  different  time  scales.  We  first  probe  the  bond-breaking  rates  by  using  the  transition  state  theory  under  different  cross-link  densities  and  polymer  melt  configurations.  However,  this  limits  us  to  the  time  scale  and  the  length  scale  associated  with  a  single  cross-link.  To  access  the  dynamics  at  different  length  scales  and  time  scales  we  computationally  model  a  powerful  experimental  dynamics  characterization  technique  called  X-ray  photon  correlation  spectroscopy  (XPCS).  Interpretation  of  the  XPCS  data  regarding  underlying  physical  processes  is  necessary  to  establish  the  connection  between  the  macroscopic  responses  and  the  microstructural  dynamics.  To  aid  the  interpretation  of  the  XPCS  data,  we  present  a  computational  framework  to  model  these  experiments  by  computing  the  X-ray  scattering  intensity  directly  from  the  atomic  positions  obtained  from  CGMD  simulations.  The  time  scale  of  the  dynamics  accessed  by  XPCS  is  controlled  by  the  sampling  frequency  of  the  CGMD  configurations  whereas  the  size  of  the  CGMD  simulation  cell  controls  the  extent  of  the  length  scales  accessed.  By  repeating  the  XPCS  analysis  at  different  sampling  frequencies  we  can  obtain  the  multiscale  dynamics  of  the  DPN  simulated  by  the  CGMD  method.  We  found  that  the  distribution  of  rates  revealed  by  computational  XPCS  is  consistent  with  the  stretched  exponential  decay  of  the  stress-relaxation  response  of  the  system.This  dissertation  presents  a  thorough  analysis  of  the  SP  between  distant  cross-links  as  a  microstructural  descriptor  that  governs  the  macroscopically  observed  mechanical  evolution  (self-healing  and  rapid  stress  relaxation)  of  the  DPN  system.  In  addition,  the  XPCS  analysis  of  the  CGMD  simulation  trajectory  is  successful  in  uncovering  the  characteristic  rates  of  the  dynamic  processes  that  accurately  predict  the  rapid  stress-relaxation  exhibited  by  the  DPNs.  The  methods  presented  in  this  dissertation  to  study  the  microstructural  and  dynamic  evolution  are  applicable  to  a  large  class  of  elastomeric  systems  and  can  aid  in  the  design  of  the  next  generation  of  smart  elastomers.
■590    ▼aSchool  code:  0212.
■650  4▼aMechanical  engineering.
■653    ▼aCoarse-grained  molecular  dynamics
■653    ▼aDynamic  polymer  networks
■653    ▼aCross-linking  bond
■653    ▼aSupramolecular  elastomer
■690    ▼a0548
■71020▼aStanford  University.
■7730  ▼tDissertations  Abstracts  International▼g85-11B.
■790    ▼a0212
■791    ▼aPh.D.
■792    ▼a2024
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17161509▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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