Loughborough University
LTO-ILG-Supplemental.pdf (2.71 MB)

Supplementary information files for Two superconductor-insulator phase transitions in the spinel oxide Li1±xTi2 O4-δ induced by ionic liquid gating

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posted on 2021-06-23, 13:20 authored by Zhongxu Wei, Qian Li, Ben-Chao Gong, Xinjian Wei, Wei Hu, Zhuang Ni, Ge He, Mingyang Qin, Anna KusmartsevaAnna Kusmartseva, Feodor Kusmartsev, Jie Yuan, Beiyi Zhu, Qihong Chen, Jian-Hao Chen, Kai Liu, Kui Jin
Supplementary files for article Two superconductor-insulator phase transitions in the spinel oxide Li1±xTi2 O4-δ induced by ionic liquid gating. The associations between emergent physical phenomena (e.g., superconductivity) and orbital, charge, and spin degrees of freedom of 3d electrons are intriguing in transition metal compounds. Here, we successfully manipulate the superconductivity of spinel oxide Li1±xTi2O4-δ (LTO) by ionic liquid gating. A dome-shaped superconducting phase diagram is established, where two insulating phases are disclosed both in heavily electron-doping and hole-doping regions. The superconductor-insulator transition (SIT) in the hole-doping region can be attributed to the loss of Ti valence electrons. In the electron-doping region, LTO exhibits an unexpected SIT instead of a metallic behavior despite an increase in carrier density. Furthermore, a thermal hysteresis is observed in the normal state resistance curve, suggesting a first-order phase transition. We speculate that the SIT and the thermal hysteresis stem from the enhanced 3d electron correlations and the formation of orbital ordering by comparing the transport and structural results of LTO with the other spinel oxide superconductor MgTi2O4 (MTO), as well as analyzing the electronic structure by first-principles calculations. Further comprehension of the detailed interplay between superconductivity and orbital ordering would contribute to the revealing of unconventional superconducting pairing mechanism.


This work was supported by the National Key R&D Program of China (Grants No. 2016YFA0300301, No. 2017YFA0302900, No. 2017YFA0303003, No. 2018YFB0704102, No. 2018YFA0305604, and No. 2019YFA0308402), the National Natural Science Foundation of China (Grants No. 11674374, No. 11774424, No. 11834016, No. 11804378, No. 11961141008, and No. 11927808), the Strategic Priority Research Program (B) of Chinese Academy of Sciences (No. XDB25000000), the Key Research Program of Frontier Sciences, CAS (Grants No. QYZDB-SSW-SLH008, No. QYZDY-SSW-SLH001, and No. QYZDB-SSW-JSC035), CAS Interdisciplinary Innovation Team, Beijing Natural Science Foundation (Grants No. Z190008 and No. Z200005), the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China (No. 19XNLG13). Computational resources are provided by the Physical Laboratory of High Performance Computing at Renmin University of China. G.H. thanks the Alexander von Humboldt Foundation for support from a research fellowship.



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