Asymmetric supercapacitors based on La-doped MoO3 nanobelts as advanced negative electrode and VOR nanosheets as positive electrode
Source abstract
Abstract
The energy density of asymmetric supercapacitors (ASCs) is limited by the negative electrodes; thus, it is imperative to design negative electrodes to optimize the device and increase the energy density of ASCs. Recently, doping has been shown to be an effective technique to regulate the band gap and increase the excitation of charge carriers to the conduction band and improve the capacitive performance for further energy conversion. Herein, by doping heteroelement metal ions, the La-doping strategy reduced the band gap of MoO3 and improved the electric conductivity, as proof by experiments and DFT calculations. The specific capacitance of the LaMoO3-4 sample exhibits an obvious improvement (from 116.5 to 605.6 F g−1 at a current density of 1 A g−1). Aqueous ASCs with a working voltage of 2 V are assembled based on VOR nanosheets as the positive electrode and LaMoO3-4 as the negative electrode. At a power density of 1000 W kg−1, the energy density of the assembly is 123 Wh kg−1; it also has an excellent cycle stability, and the capacitance retention rate after 6 000 cycles is 95.4%. A promising research route to achieve a high power density and high energy density is demonstrated herein. La is doped into the MoO3 nanobelts and the as-obtained LaMoO3 shows narrower band gap (1.91 eV) than pure MoO3 (2.48 eV) leading to an effective enhancement of electron transport and much better electrochemical performance (605.6 F g-1 at a current density of 1 A g-1). ASCs with a working voltage of 2 V based on the LaMoO3 as negative electrode and VOR as positive electrode exhibit a high energy density of 123 Wh kg-1.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Supercapacitor Materials and Fabrication · Conducting polymers and applications · Electrochemical sensors and biosensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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