Related Experiment Video
Updated: Jun 2, 2025

Preparation of Graphene Liquid Cells for the Observation of Lithium-ion Battery Material
Published on: February 5, 2019
Pt (n = 1, 3, and 4) Cluster-Modified MoSe2 Nanosheets: A Potential Sensing and Scavenging Candidate for Lithium-Ion
Zhixian Zhang1, Tian-Yi Sang2, Chutian Yu3
1School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China.
Abstract:
Realizing reliable online detection of characteristic gases (H2, C2H4, CO, and CO2) in lithium-ion batteries is crucial to maintain the safe and stable operation of power equipment and new energy storage power plants. In this study, transition metal Pt (n = 1, 3, and 4) clusters are attached to MoSe2 nanosheets for the first time based on density functional theory using the perfect crystalline facet modification method, and the adsorption characteristics and electronic behaviors of H2, C2H4, CO, and CO2 are investigated and enhanced. The results show that Pt (n = 1, 3, and 4) is reliably chemically connected to the substrate without any significant deformation of the geometry. The adsorption properties as well as the band gap, DOS, and LUMO-HOMO are optimized for the modified Gas/Pt (n = 1, 3, and 4)-MoSe2 system. The large electronic states near the Fermi level are further activated by the modification process, and Pt-MoSe2 and Pt4-MoSe2 can serve as battery state characteristic gas sensors suitably according to the detection needs of specific target gases, whereas Pt3-MoSe2 can be used as a good adsorbent for effective and reliable scavenging of battery state characteristic gases and is further applied to energy and power equipment and new energy storage power plants.
More Related Videos
07:55Elemental-sensitive Detection of the Chemistry in Batteries through Soft X-ray Absorption Spectroscopy and Resonant Inelastic X-ray Scattering
Published on: April 17, 2018
11:25Identification and Quantification of Decomposition Mechanisms in Lithium-Ion Batteries; Input to Heat Flow Simulation for Modeling Thermal Runaway
Published on: March 7, 2022