Using Fourier transform infrared spectroscopy to determine mineral phases in sediments

被引：41

作者：

Hahn, Annette ^{[1
]}

Vogel, Hendrik ^{[2
,3
]}

Ando, Sergio ^{[4
]}

Garzanti, Eduardo ^{[4
]}

Kuhn, Gerhard ^{[5
]}

Lantzsch, Hendrik ^{[1
]}

Schueuerman, Jan ^{[1
]}

Vogt, Christoph ^{[6
]}

Zabel, Matthias ^{[1
]}

机构：

[1] Univ Bremen, MARUM Ctr Marine Environm Sci, D-SPECIAL I Bremen, Germany

[2] Univ Bern, Inst Geol Sci, Bern, Switzerland

[3] Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland

[4] Univ Milano Bicocca, Dept Earth & Environm Sci, Milan, Italy

[5] Helmholtz Zentrum Polar & Meeresforsch AWI, Alfred Wegener Inst, Alten Hafen 26, D-27580 Bremerhaven, Germany

[6] Univ Bremen, Geosci, Cent Lab Crystallog & Appl Mat Sci ZEKAM, Klagenfurter Str 2-4, D-28359 Bremen, Germany

来源：

SEDIMENTARY GEOLOGY | 2018年 / 375卷

关键词：

Method development; Quartz; K-feldspar; lllite; Plagioclase; Smectite; Calcite; Provenance study; QUANTITATIVE-ANALYSIS; PROVENANCE ANALYSIS; SURFACE SEDIMENTS; CHEMICAL-ANALYSIS; LAKE ELGYGYTGYN; SOUTHERN-OCEAN; 637; KA; MU-M; CLAY; REFLECTANCE;

D O I：

10.1016/j.sedgeo.2018.03.010

中图分类号：

P5 [地质学];

学科分类号：

0709 ; 081803 ;

摘要：

In paleoenvironmental studies, the mineralogical composition of sediments is an important indicator. In combination with other indicators, they contribute to the understanding of changes in sediment sourcing as well as in weathering and depositional processes. Fourier transform infrared spectroscopy (FTIRS) spectra contain information on mineralogical composition because each mineral has a unique absorption pattern in the mid-IR range. Although easily obtained, FTIR spectra are often too complex to infer mineral concentrations directly. In this study, we use a calibration set of ca. 200 sediment samples conventionally measured using X-ray diffraction (XRD) in order to develop multivariate, partial least squares (PLS) regression models relating mineral contents to sediment spectra. Good correlations were obtained for the most common minerals (e.g. quartz, K-feldspar, illite, plagio-clase, smectite, calcite). Correlation coefficients ranged from 0.85 to 0.92, coefficients for the validation varied from 0.64 to 0.80, the number of latent variables (PLS regression components) in the models ranged between 3 and 7 and the range of variation of the RMSEcv gradient was from 15.28 to 5.7. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：27 / 35

页数：9

共 76 条

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