Mineral phase analysis of deep-sea hydrothermal particulates by a Raman spectroscopy expert algorithm: Toward autonomous in situ experimentation and exploration

This paper demonstrates that a Raman spectroscopy, point-counting technique can be used for phase analysis of minerals commonly found in deep-sea hydrothermal plumes, even for minerals with similar chemical compositions. It also presents our robust autonomous identification algorithm and spectral database, both of which were developed specifically for deep-sea hydrothermal studies. The Raman spectroscopy expert algorithm was developed and tested against multicomponent mixtures of minerals relevant to the deep-sea hydrothermal environment. It is intended for autonomous classification where many spectra must be examined with little or no human involvement to increase analytic precision, accuracy, and data volume or to enable in situ measurements and experimentation.