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A Fractal Landscape Dynamics Approach to Understanding Particle Motion in Soft Jammed Materials
A Fractal Landscape Dynamics Approach to Understanding Particle Motion in Soft Jammed Materials
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151059
- ISBN
- 9798382834559
- DDC
- 660
- 서명/저자
- A Fractal Landscape Dynamics Approach to Understanding Particle Motion in Soft Jammed Materials
- 발행사항
- [Sl] : University of Pennsylvania, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 116 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
- 주기사항
- Advisor: Crocker, John C.
- 학위논문주기
- Thesis (Ph.D.)--University of Pennsylvania, 2024.
- 초록/해제
- 요약Soft jammed materials are disordered viscoelastic solids, composed of densely packed particles, that are commonly found both in the natural world and in a wide range of manufactured products. Their applications are widespread across various industries and technologies, including food, pharmaceuticals, agriculture and cosmetics. Understanding the fundamental physics and mathematics behind their highly complex particle motion and distinct response to external stress is essential for their improved design and stability, as well as the development of new materials with unique mechanical properties. Further, it is crucial for the development of theoretical models that better describe the complex interactions and dynamics of these materials. This thesis is centered around the observation that soft jammed materials exhibit fractal landscape dynamics, where the particles' motion is not merely random but follows patterns influenced by the system's underlying fractal energy landscape. Through experimental observations, theoretical models, and numerical simulations of ripening dense emulsions and foams, this work reveals two major findings. First, it demonstrates the numerical relationships between energy landscape geometry, microscopic particle dynamics, and macroscopic rheology through a novel high-dimensional approach. Second, it introduces a simplistic random walk model that generates fractal paths with specified dimensions, successfully reflecting the complex individual particle dynamics in a ripening foam after fitting to the data. This finding affirms the presence of fractal landscape dynamics as an explanation for behaviors such as non-Gaussian particle displacements, intermittent rearrangement events, and power-law rheology. Further exploration within this work extends the high-dimensional analysis framework to the dynamics of stock market prices, drawing an intriguing parallel between the motion of individual stocks and emulsion droplets. Lastly, the machine-learning metric of 'softness' is explored as a method to predict particle rearrangements in a ripening foam, showing that simply a particle's number of neighbors achieves a surprisingly high prediction accuracy. This thesis not only enhances our understanding of soft jammed materials but also opens new avenues for applying fractal landscape dynamics across different materials and research fields.
- 일반주제명
- Chemical engineering
- 일반주제명
- Energy
- 일반주제명
- Materials science
- 일반주제명
- Computational chemistry
- 일반주제명
- Particle physics
- 키워드
- Dense emulsion
- 키워드
- Energy landscape
- 키워드
- Jammed materials
- 키워드
- Ripening foam
- 기타저자
- University of Pennsylvania Chemical and Biomolecular Engineering
- 기본자료저록
- Dissertations Abstracts International. 85-12B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520250211151059
■006m o d
■007cr#unu||||||||
■020 ▼a9798382834559
■035 ▼a(MiAaPQ)AAI31142730
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a660
■1001 ▼aRodriguez-Cruz, Clary.
■24512▼aA Fractal Landscape Dynamics Approach to Understanding Particle Motion in Soft Jammed Materials
■260 ▼a[Sl]▼bUniversity of Pennsylvania▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a116 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-12, Section: B.
■500 ▼aAdvisor: Crocker, John C.
■5021 ▼aThesis (Ph.D.)--University of Pennsylvania, 2024.
■520 ▼aSoft jammed materials are disordered viscoelastic solids, composed of densely packed particles, that are commonly found both in the natural world and in a wide range of manufactured products. Their applications are widespread across various industries and technologies, including food, pharmaceuticals, agriculture and cosmetics. Understanding the fundamental physics and mathematics behind their highly complex particle motion and distinct response to external stress is essential for their improved design and stability, as well as the development of new materials with unique mechanical properties. Further, it is crucial for the development of theoretical models that better describe the complex interactions and dynamics of these materials. This thesis is centered around the observation that soft jammed materials exhibit fractal landscape dynamics, where the particles' motion is not merely random but follows patterns influenced by the system's underlying fractal energy landscape. Through experimental observations, theoretical models, and numerical simulations of ripening dense emulsions and foams, this work reveals two major findings. First, it demonstrates the numerical relationships between energy landscape geometry, microscopic particle dynamics, and macroscopic rheology through a novel high-dimensional approach. Second, it introduces a simplistic random walk model that generates fractal paths with specified dimensions, successfully reflecting the complex individual particle dynamics in a ripening foam after fitting to the data. This finding affirms the presence of fractal landscape dynamics as an explanation for behaviors such as non-Gaussian particle displacements, intermittent rearrangement events, and power-law rheology. Further exploration within this work extends the high-dimensional analysis framework to the dynamics of stock market prices, drawing an intriguing parallel between the motion of individual stocks and emulsion droplets. Lastly, the machine-learning metric of 'softness' is explored as a method to predict particle rearrangements in a ripening foam, showing that simply a particle's number of neighbors achieves a surprisingly high prediction accuracy. This thesis not only enhances our understanding of soft jammed materials but also opens new avenues for applying fractal landscape dynamics across different materials and research fields.
■590 ▼aSchool code: 0175.
■650 4▼aChemical engineering
■650 4▼aEnergy
■650 4▼aMaterials science
■650 4▼aComputational chemistry
■650 4▼aParticle physics
■653 ▼aDense emulsion
■653 ▼aEnergy landscape
■653 ▼aFractal landscape dynamics
■653 ▼aJammed materials
■653 ▼aRipening foam
■690 ▼a0542
■690 ▼a0794
■690 ▼a0798
■690 ▼a0219
■690 ▼a0791
■71020▼aUniversity of Pennsylvania▼bChemical and Biomolecular Engineering.
■7730 ▼tDissertations Abstracts International▼g85-12B.
■790 ▼a0175
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17160675▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
