journal article·2024-06Open access

Synergy of inside doped metals‒Outside coated graphene to enhance hydrogen storage in magnesium-based alloys

Kun Zhang, Yu Chang, Jingjing Lei, Jing Chen, Tingzhi Si, Xiaoli Ding, Ping Cui, Hai-Wen Li, Qingan Zhang, Yongtao Li

Journal of Magnesium and Alloys· Volume 12· Issue 6

Abstract

Grain growth of magnesium (Mg) and its hydride is one of the main reasons for kinetic and capacity degradation during the hydrogen absorption and desorption cycles. To solve this problem, herein we propose a novel method involving synergistic effect of inside embedded metals and outside coated graphene to limit the growth of Mg and its hydride grains. The graphene coated Mg‒Y‒Al alloys were selected as a model system for demonstrating this positive effect where the Mg91Y3Al6 alloy was first prepared by rapidly solidified method and then high-pressure milled with 5 wt% graphene upon 5 MPa hydrogen gas for obtaining in-situ formed YAl2 and YH3 embedded in the MgH2 matrix with graphene shell (denoted as MgH2[email protected]). In comparison to pure MgH2, the obtained MgH2[email protected] composites deliver much better kinetics and more stable cyclic performance. For instance, the MgH2[email protected] can release about 6.1 wt% H2 within 30 min at 300°C but pure MgH2 only desorbs ∼1.5 wt% H2. The activation energy for desorption of MgH2[email protected] samples is calculated to be 75.3±9.1 kJ/mol that is much lower than approximately 160 kJ/mol for pure MgH2. Moreover, its capacity retention is promoted from ∼57% of pure MgH2 to ∼84% after 50th cycles without obvious particle agglomeration and grain growth. The synergistic effect of outside graphene coating with inside embedded metals which could provide a huge number of active sites for catalysis as well as inhibit the grain growth of Mg and its hydride is believed to be responsible for these.
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Research context

OpenAlex topics: Hydrogen Storage and Materials · Ammonia Synthesis and Nitrogen Reduction · Magnesium Alloys: Properties and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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