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Estimating Thermodynamic Quantities Far from Equilibrium
Estimating Thermodynamic Quantities Far from Equilibrium
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260311091459.5
- ISBN
- 9798280761834
- DDC
- 536.7
- 서명/저자
- Estimating Thermodynamic Quantities Far from Equilibrium / Travis Leadbetter
- 발행사항
- [Sl] : University of Pennsylvania, 2025
- 형태사항
- 1 electronic resource (213 pages)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
- 주기사항
- Advisors: Reina, Celia; Purohit, Prashant K. Committee members: Mori, Yoichiro.
- 학위논문주기
- - Ph.D. : University of Pennsylvania, 2025.
- 초록/해제
- 요약In this thesis, a novel framework for constructing macroscopic thermodynamic models arbitrarily far away from equilibrium is presented. This method, rooted in an approximation of the fundamental thermodynamic quantities from stochastic thermodynamics, establishes a connection between microscopic particle systems governed by overdamped Langevin dynamics at a well defined temperature and popular non-equilibrium thermodynamics models used at the macroscopic scale, namely thermodynamics with internal variables and the so-called GENERIC framework. We refer to this new framework as Stochastic Thermodynamics with Internal Variables (STIV). One need only specify a parameterized approximation to the system's density of states, and the STIV framework provides both dynamic and thermodynamic equations without additional phenomenological assumptions or the need to fit to data. The various applications laid out within, including those of the unfolding of coiled-coil proteins, and protein diffusion on DNA, demonstrate both the framework's flexibility and accuracy.Additionally, in the final chapter of this thesis, we highlight how a stochastic model of cross-link bonding can be tuned to produce a wide range of rheological behavior. In particular, for bonding energies with quadratic minima and assuming bond breaking is accelerated due to applied force (as is most often true), the stochastic bonds model predicts a shear thinning response to applied shearing. Finally, Kinetic Monte Carlo simulations and maximum likelihood estimation of model parameters are used to study bond energies and dissipation in solid bridges.
- 언어주기
- English
- 일반주제명
- Statistical physics
- 일반주제명
- Thermodynamics
- 일반주제명
- Applied mathematics
- 키워드
- Coarse graining
- 키워드
- Generic
- 키워드
- Gradient flow
- 기타저자
- University of Pennsylvania Applied Mathematics and Computational Science
- 기본자료저록
- Dissertations Abstracts International. 86-12B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520260311091459.5
■006m o d
■007cr|nu||||||||
■020 ▼a9798280761834
■040 ▼aMiAaPQD▼beng▼cMiAaPQD▼erda
■082 ▼a536.7
■1001 ▼aLeadbetter, Travis▼eauthor.
■24510▼aEstimating Thermodynamic Quantities Far from Equilibrium ▼cTravis Leadbetter
■260 ▼a[Sl]▼bUniversity of Pennsylvania▼c2025
■264 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a1 electronic resource (213 pages)
■336 ▼atext▼btxt▼2rdacontent
■337 ▼acomputer▼bc▼2rdamedia
■338 ▼aonline resource▼bcr▼2rdacarrier
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-12, Section: B.
■500 ▼aAdvisors: Reina, Celia; Purohit, Prashant K. Committee members: Mori, Yoichiro.
■5021 ▼bPh.D.▼cUniversity of Pennsylvania▼d2025.
■520 ▼aIn this thesis, a novel framework for constructing macroscopic thermodynamic models arbitrarily far away from equilibrium is presented. This method, rooted in an approximation of the fundamental thermodynamic quantities from stochastic thermodynamics, establishes a connection between microscopic particle systems governed by overdamped Langevin dynamics at a well defined temperature and popular non-equilibrium thermodynamics models used at the macroscopic scale, namely thermodynamics with internal variables and the so-called GENERIC framework. We refer to this new framework as Stochastic Thermodynamics with Internal Variables (STIV). One need only specify a parameterized approximation to the system's density of states, and the STIV framework provides both dynamic and thermodynamic equations without additional phenomenological assumptions or the need to fit to data. The various applications laid out within, including those of the unfolding of coiled-coil proteins, and protein diffusion on DNA, demonstrate both the framework's flexibility and accuracy.Additionally, in the final chapter of this thesis, we highlight how a stochastic model of cross-link bonding can be tuned to produce a wide range of rheological behavior. In particular, for bonding energies with quadratic minima and assuming bond breaking is accelerated due to applied force (as is most often true), the stochastic bonds model predicts a shear thinning response to applied shearing. Finally, Kinetic Monte Carlo simulations and maximum likelihood estimation of model parameters are used to study bond energies and dissipation in solid bridges.
■546 ▼aEnglish
■590 ▼aSchool code: 0175
■650 4▼aStatistical physics
■650 4▼aThermodynamics
■650 4▼aApplied mathematics
■653 ▼aCoarse graining
■653 ▼aGeneric
■653 ▼aGradient flow
■653 ▼aInternal variables
■653 ▼aStochastic thermodynamics
■7102 ▼aUniversity of Pennsylvania▼bApplied Mathematics and Computational Science.▼edegree granting institution.
■7201 ▼aReina, Celia▼edegree supervisor.
■7201 ▼aPurohit, Prashant K.▼edegree supervisor.
■7730 ▼tDissertations Abstracts International▼g86-12B.
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17357318▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
