The high-speed development of the Internet of Things
and artificial
intelligence is revolutionizing the world in terms of industrial production,
environmental protection, medical treatment, education, daily life,
and so on. The powerful and fast computing methods are crucial for
the advanced computing technology toward the next generation artificial
intelligence. Traditional computing systems have separated logical
and storage units, which cause computation time delays and increase
power consumption. Spintronic memristors combine the nonvolatile characteristics
of memristors with the scalability of a spin-transfer torque device,
which can meet the high-speed, low-power, and scalability requirements
of quantum computing (QC) for quantitative information processing.
This paper reviews the research progress of spintronic memristors
based on magnetic tunnel junction (MTJ), domain wall (DW) motion,
and spin wave (SW), respectively, focusing on the development and
challenges of spintronic memristors for QC. Finally, some problems
that need to be solved urgently in the current research are summarized,
and the potential applications of spintronic memristors are discussed.
In polycrystalline MgB 2 samples, the crystal grains are randomly oriented, and the anisotropy of the upper critical field leads to different supercurrent carrying capacities in different grains, so the overall supercurrent becomes percolation in applied magnetic field. In this paper, we studied the doping effect of citric acid on the critical current density and the percolation behavior in polycrystalline MgB 2 samples. By fitting the experimental data with the percolation model, it is found that the anisotropy of the upper critical field is gradually decreased by doping citric acid, which alters the percolation behavior of the supercurrent of the polycrystalline MgB 2 samples. In addition, it is observed that deviation of the experimental data from the typical grain boundary pinning theory reduces with increasing doping level or as the temperature approaching T c . The phenomenon is well explained according to the systematical decrease of anisotropy parameter = (B ∥ c2 ∕B ⟂ c2 ) with doping level and temperature.
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