Issue 9, 2023

Formation of inorganic liquid gallium particle–manganese oxide composites

Abstract

Gallium (Ga) is a low melting point post-transition metal that, under mild mechanical agitation, can form micron and submicron-sized particles with combined fluid-like and metallic properties. In this work, an inorganic network of Ga liquid metal particles was synthesised via spontaneous formation of manganese (Mn) oxide species on their liquid metallic surfaces forming an all-inorganic composite. The micron-sized Ga particles formed by sonication were connected together by Mn oxide nanostructures spontaneously established from the reduction of a Mn salt in aqueous solution slightly above the melting point of Ga. The formed Mn oxide nanostructures were found to coalesce from the surface of the Ga particles into a continuous inorganic network. The morphology of the composites could be altered by varying the Mn salt concentration and by performing post-treatment annealing. The composites presented a shell of various Mn oxide nanostructures including wrinkled sheets, rods and nanoneedles, around spherical liquid Ga particles, and a liquid metal core. The photoelectric and optical properties of the composites were thoroughly characterised, which revealed decreasing bandgaps and valence band edge characteristics as a function of increased Mn oxide coverage. The photoluminescence properties of the composites could be also engineered by increasing the Mn oxide coverage. The all-inorganic liquid Ga composite could be formed via a straightforward reduction reaction of a Mn-rich salt at the surface of liquid Ga particles with tunable surface properties for future optoelectronic applications.

Graphical abstract: Formation of inorganic liquid gallium particle–manganese oxide composites

Supplementary files

Article information

Article type
Paper
Submitted
15 Nov 2022
Accepted
24 Jan 2023
First published
25 Jan 2023

Nanoscale, 2023,15, 4291-4300

Formation of inorganic liquid gallium particle–manganese oxide composites

S. Cai, M. B. Ghasemian, Md. A. Rahim, M. Baharfar, J. Yang, J. Tang, K. Kalantar-Zadeh and F. Allioux, Nanoscale, 2023, 15, 4291 DOI: 10.1039/D2NR06384K

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