A simple method for obtaining heat capacity coefficients of minerals

Heat capacity data are unavailable or incomplete for many minerals at geologically relevant temperatures. Despite the availability of entropy and enthalpy values in numerous thermodynamic tables (even sometimes at elevated temperatures), there remains need for extrapolation beyond, or interpolation...

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Bibliographic Details
Published inThe American mineralogist Vol. 109; no. 3; pp. 624 - 627
Main Authors Bowman, Samuel, Pathak, Arkajyoti, Agrawal, Vikas, Sharma, Shikha
Format Journal Article
LanguageEnglish
Published Washington Mineralogical Society of America 01.03.2024
Walter de Gruyter GmbH
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Summary:Heat capacity data are unavailable or incomplete for many minerals at geologically relevant temperatures. Despite the availability of entropy and enthalpy values in numerous thermodynamic tables (even sometimes at elevated temperatures), there remains need for extrapolation beyond, or interpolation between, temperatures. This approach inevitably results in estimates for entropy and enthalpy values because the heat capacity coefficients required for optimal thermodynamic treatment are less frequently available. Here we propose a simple method for obtaining heat capacity coeficients of minerals. This method requires only the empirically measured temperature-specific heat capacity for calculation via a matrix algorithm. The system of equations solver is written in the Python computing language and has been made accessible in an online repository. Thermodynamically, the solution to a system of equations represents the heat capacity coefficients that satisfy the mineral-specific polynomial. Direct coefficient calculation will result in more robust thermodynamic data, which are not subject to fitting uncertainties. Using hematite as an example, this method provides results that are comparable to conventional means and is applicable to any solid material. Coeficients vary within the traditional large 950 K temperature interval, indicating that best results should instead utilize a smaller 400 K temperature interval. Examples of large-scale implications include the refinement of geothermal gradient estimation in rapidly subsiding sedimentary basins or metamorphic and hydrothermal evolution.
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USDOE Office of Energy Efficiency and Renewable Energy (EERE)
EE0009597
ISSN:0003-004X
1945-3027
DOI:10.2138/am-2023-9109