Building analogs in the lab: spectral characterization of a synthetic Nakhlite.

Introduction

Silicates are the main constituent of volcanic terrains on terrestrial planets in the Solar system. On Earth, we know that volcanic terrains are constituted by lava flows and fragmented pyroclasts whose texture presents both glassy and crystalline phases. Understanding the influence of glass/crystal ratio on the spectral response of volcanic rocks is therefore focal to interpret remotely sensed spectra that are commonly used to interpret the geology of terrestrial planets. Thus, we performed spectral characterization of lab-made mafic volcanic products which were synthesized in the petro-vulcanology research group (PVRG) labs to present different degrees of crystallinity.

Samples preparation and characterization

Samples were created by mixing powdered oxides to mimic the composition of a Nakhlite meteorite. The powder was melted at 1450°C to form a silicate melt, which was then quickly cooled to produce a glass and divided into four sub-samples. As observable in Fig. 1, one sub-sample was rapidly cooled in air to form Nglass, while the other three were slowly cooled (52-60°C per hour) to target temperatures of approximately 1200°C (N12), 1100°C (N11), and 1000°C (N10).

Figure 1: Cooling ramps for the syntheses of products with different crystallization degree

The synthesized samples were analyzed using X-ray powder diffraction (XRPD), and quantitative phase analysis (QPA) was performed using the Rietveld profile fitting method with internal standards to determine amorphous content. Crystallized samples (N10, N11, and N12) showed peaks corresponding to various crystalline phases including Augite, Cristobalite, Magnetite, and Hematite. Quantitative analyses are reported in as reported in Figure 2.

Figure 2: Mineralogical assemblage of the produced samples

Reflectance analysis

Spectroscopic characterization was performed with SHINE (SpectropHotometer with variable INcidence and Emergence) at the Cold Surface Spectroscopy facility (CSS) of IPAG laboratory. This setup allows the collection of spectra in the visible (VIS) and near-infrared (NIR) ranges (0.35–4.5 µm) across a broad range of illumination (0–30°) and emergence angles (e=0-70°) at room temperature. Both illumination and emergence angles are zenithal angles, measured from the normal direction to the surface. Approximately 2 g of powdered samples (grain size < 80 µm). All acquired spectra are shown in Figure 3 where they are divided in four subgraphs representing the four samples N10, N11, N12 and Nglass.

Figure 3: VNIR spectra of four samples at different acquisition geometries.

Principal component analyses (PCA)

Our set of spectra was analyzed using PCA and K-Means clustering to visualize differences and similarities between the spectra from an unsupervised machine learning perspective. Principal component analysis was then performed without normalization, retaining the first two PCs, which encompass ~99.82% of the total variance (Figure 3a). The elbow method was used to determine the optimal number of clusters, resulting in 3 clusters (Figure 4). This led to a well-defined classification with only 3 misclassified samples. The mean spectra from each cluster were visibly similar to the spectra of each class, with low standard deviation for Nglass and N12, and higher for the cluster comprising N10 and N11. The resulting PCs are explainable from the loadings, showing that the first PC mainly represents the shape of a Nglass spectrum, while the second PC considers the height of the shoulder before ~800 nm and the dip after that point.

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Figure 4: Clustering of spectra after PCA analyses

Future perspectives

We have observed how, for samples with identical chemical composition and different mineralogical assemblage, the spectral response within Visible and Near InfraRed (VNIR) can be substantially different. The mechanism influencing the shape of spectra results in fact from a complex interaction of the spectral response of different mineral/amorphous phases. In this way, the shape is easily misinterpreted as the features of the different phases which are often no longer recognizable. A PCA analyses helped us to understand which are the features that can be accounted for the interpretation of this kind of igneous materials, but a more comprehensive study on different compositions is needed for a complete assessment of this approach.
Acknowledgements
This work was carried on thanks to ASI-UniPG agreement 2019-2-HH.0 and in the framework of Trans-National Access research project selected and funded by Europlanet-2024 RI (European Union’s Horizon 2020 RI under grant agreement No. 871149)