5 research outputs found

    Characterization of Kerogen and Source Rock Maturation Using Solid-State NMR Spectroscopy

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    Solid-state NMR methods common to the analysis of polymers and other rigid solids are utilized for the study of kerogen, bitumen, and the organic content in source rocks. The use of straightforward nondestructive techniques, primarily employing solid-state NMR, is shown to provide useful information about both individual samples and changes between samples that cover a range of thermal maturities of type II kerogen. In addition to aromatic fraction and chemical structure, one of the most striking changes to isolated kerogen with maturity is the distribution of pore sizes, studied with both <sup>129</sup>Xe NMR and complementary nitrogen physisorption, that may help to understand the process of bitumen generation. Ultimately, direct in situ analysis of source rock samples that allow kerogen and bitumen to be distinguished is desirable, as it would eliminate the time and effort to isolate and prepare kerogen samples. By proper consideration and removal of the background, we find that a clear <sup>13</sup>C NMR signal can be obtained from source rock with total organic carbon weight as low as 2%. Simple <sup>1</sup>H NMR methods are shown to quickly provide a qualitative measurement of the bitumen in source rocks, while <sup>13</sup>C cross-polarization is found to be an easy method to distinguish kerogen from bitumen

    Characteristics of the subjects (Fleurbaix-Laventie Ville-Santé II study).

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    <p>Values are expressed as mean ± standard deviation, or median and interquartiles. Data for leisure time and walking are from the Modifiable Activity Questionnaire.</p

    Mother-offspring correlation for pedometer-assessed physical activity (Fleurbaix-Laventie Ville-Santé II study).

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    <p>Data are interclass correlation coefficients (95%CI) of number of steps standardized for sex and age. Data for physical activity during leisure time are from the Modifiable Activity Questionnaire. The total number of clusters can differ from maximal number of clusters (283) because of missing data.</p

    Familial correlations for pedometer-assessed physical activity (Fleurbaix-Laventie Ville-Santé II study).

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    <p>Data are correlation coefficients (95%CI) of number of steps standardized for sex and age.</p><p>Maximal number of clusters because for each coefficient computation data could be missing.</p
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