Composition Analysis of an Apatite Crystal using a Space-Prototype Mass Spectrometric Instrument and Machine Learning for Unsupervised Mineralogical Phase Detection
- Physics Institute, Space Research and Planetary Sciences, University of Bern, Bern, Switzerland
We present the analysis of a 2.06 Ga apatite crystal obtained from an ultramafic phoscorite rock from the Phalaborwa Complex (Limpopo Province, South Africa) [1]. A space-prototype laser ablation ionisation mass spectrometer (LIMS) [2,3] was used to study the chemical composition of the sample. Mass spectra were recorded from a sample area of 0.6x0.6 mm2, with a spatial resolution of 30 μm and sub-micrometre depth resolution.
Apatite is a calcium phosphate mineral expressed by the chemical stoichiometric formula [Ca5(PO4)3(F, Cl, OH)]. The halogen site, occupied by F, Cl, and OH, corresponds to an isomorpous series with fluor-, chlor- and hydroxyl-apatite end members, respectively. Apatite, being an accessory mineral in igneous and other rocks, commonly contains a range of other elements that do not fit well into the major rock forming minerals, such as rare earth elements (REE). These are suitable targets for investigating physical and chemical conditions in igneous rocks and the volatile evolution of magmas.
The analysis of the spectra recorded with our LIMS system for the abundances of the elements of interest at each location were performed in two steps. First, the abundances of each element across the sampled area were compiled in element maps. And second, an unsupervised machine learning algorithm based on clustering and network analysis was applied to the data set of analysed mass spectra to separate it into groups of distinct chemical composition. Subsequently, a more detailed analysis was conducted on each of the recovered groups to assign the corresponding mineral. In addition to the group of spectra belonging to apatite, which was assigned to fluorapatite, other minerals were identified, amongst others olivine. This method yields an unsupervised approach to identify different mineralogical entities present within a sample. This network analysis method was previously applied to a 1.88 Ga Gunflint sample (Ontario, Canada) to separate spectra recorded from the host (chert) from spectra containing signatures of organic matter from fossilized microbes [4].
Given that the data were recorded using a miniature mass spectrometer designed for space flight, this analysis demonstrates the analytical capabilities of our LIMS system that could be achieved in-situ on other planetary bodies in our Solar System, for example on the Moon or on Mars. The current performance of this miniature LIMS instrument to study the chemical composition of apatite is sufficiently high to measure volatiles (H, F, Cl) and nearly all relevant mineral and partially trace elements (Na, C, Mg, Si, S, K, Mn, Fe, Sr, Ba), including REE (La, Ce, Pr, Sm) which allows for a systematic quantitative analysis of their distribution.
[1] Tulej, M. et al., 2022, https://doi.org/10.3390/universe8080410.
[2] Riedo, A. et al., 2012, https://doi.org/10.1002/jms.3104.
[3] Tulej, M. et al., 2021, https://doi.org/10.3390/app11062562.
[4] Lukmanov, R.A. et al., 2022, https://doi.org/10.3389/frspt.2022.718943
How to cite: Gruchola, S., Tulej, M., Keresztes Schmidt, P., Lukmanov, R., Riedo, A., and Wurz, P.: Composition Analysis of an Apatite Crystal using a Space-Prototype Mass Spectrometric Instrument and Machine Learning for Unsupervised Mineralogical Phase Detection, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11898, https://doi.org/10.5194/egusphere-egu23-11898, 2023.