Volume-Based Thermodynamics: A Prescription for Its Application and Usage in Approximation and Prediction of Thermodynamic Data
Thermodynamics, as both thermochemistry and thermophysics, is fundamental and central to the science of matterand, in particular, of condensed materials. While extensive data resources for thermodynamic quantities do exist, none of theexperimental, simulation, or theoretical studies can keep pace wi...
| Main Authors: | , |
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| Format: | Journal Article |
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American Chemical Society
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/36301 |
| _version_ | 1848754730713481216 |
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| author | Glasser, Leslie Jenkins, H. D. |
| author_facet | Glasser, Leslie Jenkins, H. D. |
| author_sort | Glasser, Leslie |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Thermodynamics, as both thermochemistry and thermophysics, is fundamental and central to the science of matterand, in particular, of condensed materials. While extensive data resources for thermodynamic quantities do exist, none of theexperimental, simulation, or theoretical studies can keep pace with the rate of synthesis of new materials or provide reliable data forhypothesized materials. Correlation methods can fill this gap. We describe a range of recently developed correlation methods thatrely on volume to predict thermodynamic quantities. In parallel with these, thermodynamic difference rules, which describe howproperties of materials (say, of a group of solvates) may be inferred from corresponding properties of materials that neighbor them incomposition, have recently been reviewed. |
| first_indexed | 2025-11-14T08:45:03Z |
| format | Journal Article |
| id | curtin-20.500.11937-36301 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:45:03Z |
| publishDate | 2011 |
| publisher | American Chemical Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-363012017-09-13T15:51:39Z Volume-Based Thermodynamics: A Prescription for Its Application and Usage in Approximation and Prediction of Thermodynamic Data Glasser, Leslie Jenkins, H. D. Thermodynamics, as both thermochemistry and thermophysics, is fundamental and central to the science of matterand, in particular, of condensed materials. While extensive data resources for thermodynamic quantities do exist, none of theexperimental, simulation, or theoretical studies can keep pace with the rate of synthesis of new materials or provide reliable data forhypothesized materials. Correlation methods can fill this gap. We describe a range of recently developed correlation methods thatrely on volume to predict thermodynamic quantities. In parallel with these, thermodynamic difference rules, which describe howproperties of materials (say, of a group of solvates) may be inferred from corresponding properties of materials that neighbor them incomposition, have recently been reviewed. 2011 Journal Article http://hdl.handle.net/20.500.11937/36301 10.1021/je100683u American Chemical Society restricted |
| spellingShingle | Glasser, Leslie Jenkins, H. D. Volume-Based Thermodynamics: A Prescription for Its Application and Usage in Approximation and Prediction of Thermodynamic Data |
| title | Volume-Based Thermodynamics: A Prescription for Its Application and Usage in Approximation and Prediction of Thermodynamic Data |
| title_full | Volume-Based Thermodynamics: A Prescription for Its Application and Usage in Approximation and Prediction of Thermodynamic Data |
| title_fullStr | Volume-Based Thermodynamics: A Prescription for Its Application and Usage in Approximation and Prediction of Thermodynamic Data |
| title_full_unstemmed | Volume-Based Thermodynamics: A Prescription for Its Application and Usage in Approximation and Prediction of Thermodynamic Data |
| title_short | Volume-Based Thermodynamics: A Prescription for Its Application and Usage in Approximation and Prediction of Thermodynamic Data |
| title_sort | volume-based thermodynamics: a prescription for its application and usage in approximation and prediction of thermodynamic data |
| url | http://hdl.handle.net/20.500.11937/36301 |