Statistical mechanical study of the energy and enthalpy distribution functions of some physical systems
碩士 === 國立中央大學 === 物理研究所 === 91 === In statistical mechanics the canonical ensemble theory has been widely used to study the thermodynamic properties of a physical system. Central to this kind of theory is the canonical partition function. Experience shows that an analytical evaluation of the part...
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ndltd-TW-091NCU051980342016-06-22T04:14:30Z http://ndltd.ncl.edu.tw/handle/21914050154444687314 Statistical mechanical study of the energy and enthalpy distribution functions of some physical systems 物理系統之能量與焓分佈之統計力學研究 Chien-Hao Wei 魏建豪 碩士 國立中央大學 物理研究所 91 In statistical mechanics the canonical ensemble theory has been widely used to study the thermodynamic properties of a physical system. Central to this kind of theory is the canonical partition function. Experience shows that an analytical evaluation of the partition function is by no means easy especially for complex systems. An alternative approach within the same theoretical framework is to start with the inverse Laplace transform of partition function. For although this approach to the statistical thermodynamics is no less simpler, the method has the salient traits of resorting to experimental data to extract useful physical quantities. In this work, we re-visit this so-called energy or enthalpy distribution theory. The main advantage in this kind of theory is that, in conjunction with the maximum entropy theory, the energy or enthalpy distribution function can be obtained by resorting only to experimental thermal data. The calculated distribution function can provide insight into the physical system under studied. We illustrate the power of the distribution theory by studying a few selected physical systems. San-Kiong Lai 賴山強 2003 學位論文 ; thesis 79 en_US |
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碩士 === 國立中央大學 === 物理研究所 === 91 ===
In statistical mechanics the canonical ensemble theory has been widely used to study the thermodynamic properties of a physical system. Central to this kind of theory is the canonical partition function. Experience shows that an analytical evaluation of the partition function is by no means easy especially for complex systems. An alternative approach within the same theoretical framework is to start with the inverse Laplace transform of partition function. For although this approach to the statistical thermodynamics is no less simpler, the method has the salient traits of resorting to experimental data to extract useful physical quantities. In this work, we re-visit this so-called energy or enthalpy distribution theory. The main advantage in this kind of theory is that, in conjunction with the maximum entropy theory, the energy or enthalpy distribution function can be obtained by resorting only to experimental thermal data. The calculated distribution function can provide insight into the physical system under studied. We illustrate the power of the distribution theory by studying a few selected physical systems.
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author2 |
San-Kiong Lai |
author_facet |
San-Kiong Lai Chien-Hao Wei 魏建豪 |
author |
Chien-Hao Wei 魏建豪 |
spellingShingle |
Chien-Hao Wei 魏建豪 Statistical mechanical study of the energy and enthalpy distribution functions of some physical systems |
author_sort |
Chien-Hao Wei |
title |
Statistical mechanical study of the energy and enthalpy distribution functions of some physical systems |
title_short |
Statistical mechanical study of the energy and enthalpy distribution functions of some physical systems |
title_full |
Statistical mechanical study of the energy and enthalpy distribution functions of some physical systems |
title_fullStr |
Statistical mechanical study of the energy and enthalpy distribution functions of some physical systems |
title_full_unstemmed |
Statistical mechanical study of the energy and enthalpy distribution functions of some physical systems |
title_sort |
statistical mechanical study of the energy and enthalpy distribution functions of some physical systems |
publishDate |
2003 |
url |
http://ndltd.ncl.edu.tw/handle/21914050154444687314 |
work_keys_str_mv |
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