Multi-modal characterization of ultramafic rock: Precursors relevant to serpentinization and hydrogen generation

Abstract

Natural hydrogen (H₂) generated by the reaction of ultramafic rocks with water is increasingly recognized as a promising low-carbon energy resource with the analysis of rock mineralogy and structural characteristics recognized to play a crucial role in assessing its subsurface generation potential. In this study, micro-computed tomography (micro-CT), micro-X-ray fluorescence spectroscopy (micro-XRF), X-ray diffraction (XRD), and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS) are employed to analyze the density, elemental distribution, mineral composition, and surface spatial relationships of an ultramafic rock sample. In addition, deep learning-based image analysis is employed to achieve high-resolution mineral phase characterization, enabling quantitative analysis of the spatial distribution, co-location, and contact surfaces of the mineral phases. Focusing on a particular sample that was considered a likely initiator of hydrogen generation due to its mineral contents, our results indicate that the sample is primarily composed of Fe-Mg-rich olivine and silicate minerals, with most olivine phases being Mg-rich forsterite or mixtures of forsterite and Fe-rich fayalite. The sample also contains Fe-S sulfides and high-density metal-enriched phases, including Ni-rich phases that may enhance the H₂-generating potential of serpentinization reactions. These findings highlight the mineralogical complexity of the studied ultramafic rock and the value of integrating compositional and spatial data when considering the potential of particular materials for hydrogen generation. The integrated analytical approach proposed in this study provides new insights and practical tools for evaluating the hydrogen generation potential associated with subsurface serpentinization in ultramafic rock.

Keywords

Natural hydrogen / Serpentinization / Deep Learning / X-ray micro-computed tomography / X-ray fluorescence spectroscopy / X-ray diffraction / SEM-EDS

Acknowledgements

The authors acknowledge the facilities and scientific and tech-nical assistance provided by Microscopy Australia at the Electron Microscope Unit (EMU), the X-ray fluorescence laboratory, and the X-ray diffraction laboratory within the Mark Wainwright Ana-lytical Centre (MWAC) at UNSW Sydney. The authors also acknowl-edge the facilities and scientific and technical assistance provided by the Water Research Laboratory at the School of Civil & Environ-mental Engineering at UNSW Sydney. Financial support through Australian Research Council Linkage project LP220200912 and partners Geoscience Australia, Geological Survey of Western Australia, Geological Survey of New South Wales, South Australian Department for Energy and Mining and the Tasmanian Department of State Growth is gratefully acknowledged. Emma Black thanks Geoscience Australia for the award of a PhD doctoral scholarship.

CRediT authorship contribution statement

Jiejie Li: Writing - original draft, Visualization, Validation, Methodology, Investigation, Formal analysis, Data curation. Emma Black: Writing - review & editing, Resources, Investigation. Christopher Miller: Writing - review & editing, Resources. Kunning Tang: Writing - review & editing, Resources. Peyman Mostaghimi: Writing - review & editing, Resources. Andrew Feitz: Writing - review & editing, Resources. T.David Waite:. Ryan T. Armstrong: Writing - review & editing, Supervision, Resources, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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