https://doi.org/10.3390/molecules28031099
“The provenance study of archaeological materials is an important step in understanding the cultural and economic life of ancient human communities. One of the most popular approaches in provenance studies is to obtain the chemical composition of material and process it with chemometric methods. In this paper, we describe a combination of the total-reflection X-ray fluorescence (TXRF) method and chemometric techniques (PCA, k-means cluster analysis, and SVM) to study Neolithic ceramic samples from eastern Siberia (Baikal region). A database of ceramic samples was created and included 10 elements/indicators for classification by geographical origin and ornamentation type. This study shows that PCA cannot be used as the primary method for provenance purposes, but can show some patterns in the data. SVM and k-means cluster analysis classified most of the ceramic samples by archaeological site and type with high accuracy. The application of chemometric techniques also showed the similarity of some samples found at sites located close to each other. A database created and processed by SVM or k-means cluster analysis methods can be supplemented with new samples and automatically classified.”
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The study of samples of ancient ceramics is an important source of information about the cultural and economic life of ancient human communities. This is because ceramics were objects of everyday use and may provide a lot of information about trade relations, religious customs, and communication between various communities [1]. The provenance analysis of ceramics is possible through the determination of chemical composition [2]. Quantitative data regarding elemental composition are usually obtained by analyzing powdered ceramic fragments through X-ray fluorescence spectrometry (XRF) [3,4,5], instrumental neutron activation analysis [6,7], and inductively coupled plasma mass spectrometry (ICP-MS) [3,8]. Laser ablation inductively coupled plasma mass spectrometry [7,9] and micro X-ray fluorescence spectrometry (µXRF) [10] can be used for separate analysis of the clay component and inclusions in the ceramic cross-section. Non-destructive characterization of bulk ceramic composition is possible using portable XRF [11,12,13,14,15].
Despite the large number of methods used to analyze ceramics, one of the most popular approaches to chemical analysis in archaeology is the use of XRF spectrometry combined with machine learning techniques to attribute samples to specific places of origin. This popularity is due to the relative ease and accessibility of XRF analysis, its non-destructive nature, its ability to be performed in the field, and the wide range of elements determined. Machine learning methods (chemometric methods, in the context of chemical analysis) allow the extraction of complex and non-obvious correlations between objects and their characteristics in the large volume of data provided by XRF [16]. The arsenal of modern chemometric methods is quite large and includes methods of clustering, classification, and multivariate regression. The choice of specific methods of investigation depends on the problem to be solved. In recent years, the combination of XRF and chemometric methods has become increasingly common in archaeological research. Typical recent works are worth mentioning here. In [17], artificial neural networks (ANNs) and linear discriminant analysis (LDA) methods were successfully applied in combination with XRF and XRD data to attribute the origin of pottery samples to different Greek colonies in Sicily. The accuracy of the classification using ANN was 78% and that of LDA was only 50%. In [18], the potential of two different instrumental methods for hierarchical cluster analysis (HCA) of Medieval and post-Medieval ceramics from the Iberian Peninsula was compared. It was shown that the simpler, non-destructive XRF method achieves almost the same clustering efficiency as the more complex, expensive, and destructive ICP-MS method.
The most popular XRF instruments for archaeological tasks are energy dispersion instruments [18,19,20,21,22,23], including portable XRF instruments [11,12,13,14,15]. These devices offer reliable determination of major elements, but do not provide information about the contents of impurities and trace elements, which, in the context of archaeological research, can be more informative. This problem can be solved by using total-reflection X-ray fluorescence spectrometry (TXRF), the detection limits of which are several orders of magnitude lower than those of traditional XRF. TXRF has been successfully applied to determine the chemical composition of ceramics [24,25,26,27,28]. In these works, it was shown that the limit of detection and limit of quantification of TXRF are adequate for the determination of trace elements in these samples.
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2.1. TXRF Analysis
This research was performed using a TXRF method for the analysis of ceramic samples, successful validation of which was performed in our previous study [35]. The analytical features of the method were not under consideration in this study. Table 1 presents the concentration ranges of the elements in the 81 ceramic samples obtained by TXRF analysis and divided by archaeological sites. Most of the ceramic samples (45) are represented by those from the Popovsky Lug site. Elements of interest were determined not only by the sensitivity and accuracy of the TXRF method, but also by the previous investigations, where element indicators were found [35]. The acid leaching sample preparation of the ceramic allows transferring of the clay component into solution and separation of the insoluble silicate minerals included in the ceramic [24,35]. Using this approach for provenance analysis allows for better identification of sample groups than using the bulk composition of ceramic samples. This method, based on the analysis of the clay components of ceramics, is a perspective to be applied for comparison with the chemical composition of regional clays.
Table 1. Elemental characterization of ceramic samples by TXRF method.
Table 1. Elemental characterization of ceramic samples by TXRF method.
| Archaeological Site (Number of Samples) | Concentration Range (mg/kg) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| V | Cr | Ni | Cu | Zn | Ga | Rb | Sr | Y | Pb | |
| Popovsky Lug (45) | 31–152 | 57–172 | 9–82 | 9–62 | 26–943 | 8–19 | 13–76 | 36–203 | 7–57 | 19–72 |
| Ust-Yamniy (11) | 40–162 | 50–193 | 15–50 | 12–50 | 37–129 | 4–18 | 13–60 | 64–188 | 14–30 | 26–66 |
| Makarovo (9) | 39–126 | 62–142 | 16–44 | 12–31 | 58–114 | 10–15 | 24–63 | 69–168 | 13–27 | 27–51 |
| Ust-Karenga (8) | 0–63 | 26–98 | 6–30 | 12–61 | 38–501 | 11–23 | 20–122 | 21–201 | 3–52 | 21–180 |
| Ust-Yumurchen (4) | 16–99 | 28–163 | 5–59 | 12–42 | 62–83 | 8–14 | 10–43 | 18–260 | 9–20 | 18–49 |
| Shishkino (4) | 54–97 | 90–138 | 30–48 | 21–31 | 46–67 | 10–15 | 23–48 | 42–76 | 8–21 | 25–42 |
Figure 1 shows the spectra of ceramic samples from different sites. To perform the correct interpretation of spectra, all intensities were normalized to the Se-Kα line (internal standard). As can be seen from the spectra, there is either a slight (Ni, Ga, Y, and Pb) or great (Cr, Zn, and Sr) difference among peaks of same elements for samples from different sites. This means that ceramic samples may have similar elemental compositions even if they were found far away from each other.
Figure 1. TXRF spectra (energy range: 4.0–18 keV) of ceramic samples, one of each from different archaeological sites.
3.3. Spectra Acquisition
TXRF elemental analysis was performed using a benchtop spectrometer S2 PICOFOX (Bruker Nano Analytics, Berlin, Germany) equipped with an X-ray tube with a Mo-anode, multilayer monochromator, and 30 mm2 silicon drift detector (energy resolution was <150 eV at Mn-Kα line). Measurement of one sample was carried out in triplicate during 500 s at a 50 kV voltage and a 0.50 mA current. Quartz carriers were used as sample holders and reflectors. The Spectra 7.8.2 software package (Bruker Nano Analytics, Berlin, Germany) was applied for spectra processing.
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