| 書目名稱 | Classical Statistical Mechanics with Nested Sampling |
| 編輯 | Robert John Nicholas Baldock |
| 視頻video | http://file.papertrans.cn/228/227130/227130.mp4 |
| 概述 | Nominated as an outstanding PhD thesis by the University of Cambridge, UK.Enables the calculation of partition functions as explicit functions of temperature for realistic models of materials directly |
| 叢書名稱 | Springer Theses |
| 圖書封面 |  |
| 描述 | This thesis develops a nested sampling algorithm into a black box tool for directly calculating the partition function, and thus the complete phase diagram of a material, from the interatomic potential energy function. It represents a significant step forward in our ability to accurately describe the finite temperature properties of materials. In principle, the macroscopic phases of matter are related to the microscopic interactions of atoms by statistical mechanics and the partition function. In practice, direct calculation of the partition function has proved infeasible for realistic models of atomic interactions, even with modern atomistic simulation methods. The thesis also shows how the output of nested sampling calculations can be processed to calculate the complete PVT (pressure–volume–temperature) equation of state for a material, and applies the nested sampling algorithm to calculate the pressure–temperature phase diagrams of aluminium and a model binary alloy. |
| 出版日期 | Book 2017 |
| 關(guān)鍵詞 | Nested Sampling Algorithm; Efficient Derivation of Phase Diagram; Calculation of Partition Function; Cl |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-66769-0 |
| isbn_softcover | 978-3-319-88317-5 |
| isbn_ebook | 978-3-319-66769-0Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | Springer International Publishing AG 2017 |
|Archiver|手機(jī)版|小黑屋|
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