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As they mimic the synapses in biological neurons, memristors became the key component for designing novel types of computing and information systems based on artificial neural networks, the so-called neuromorphic electronics (Zidan, 2018; Wang and Zhuge, 2019; Zhang et al., 2019b). Electronic artificial neurons with synaptic memristors are capable of emulating the associative memory, an important function of the brain (Pershin and Di Ventra, 2010). In addition, the technological simplicity of thin-film memristors based on transition metal oxides such as TiO2 allows their integration into electronic circuits with extremely high packing density. Memristor crossbars are technologically compatible with traditional integrated circuits, whose integration can be implemented within the complementary metal–oxide–semiconductor platform using nanoimprint lithography (Xia et al., 2009). Nowadays, the size of a Pt-TiOx-HfO2-Pt memristor crossbar can be as small as 2 nm (Pi et al., 2019). Thus, the inherent properties of memristors such as non-volatile resistive memory and synaptic plasticity, along with feasibly high integration density, are at the forefront of the new-type hardware performance of cognitive tasks, such as image recognition (Yao et al., 2017). The current state of the art, prospects, and challenges in the new brain-inspired computing concepts with memristive implementation have been comprehensively reviewed in topical papers (Jeong et al., 2016; Xia and Yang, 2019; Zhang et al., 2020). These reviews postulate that the newly emerging computing paradigm is still in its infancy, while the rapid development and current challenges in this field are related to the technological and materials aspects. The major concerns are the lack of understanding of the microscopic picture and the mechanisms of switching, as well as the unproven reliability of memristor materials. The choice of memristive materials as well as the methods of synthesis and fabrication affect the properties of memristive devices, including the amplitude of resistive switching, endurance, stochasticity, and data retention time.

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•  At present, Lide powder is mainly produced in China. Most of the domestic Lide powder production is still using traditional methods. The main raw materials are zinc oxide, sulfuric acid and barium sulfide (barite and coal are produced by high temperature reduction). Zinc 45% ~ 70%. The traditional method for producing the Liede powder process is to use zinc bakelite containing more than 45% zinc as a raw material to be leached with sulfuric acid to obtain a crude zinc sulfate solution, and then to remove iron by potassium permanganate, and then replace the heavy metal with zinc powder and filter to obtain zinc sulfate. The refined liquid is further subjected to metathesis reaction, pressure filtration, calcination, rinsing, drying, and pulverization with strontium sulfide to obtain a series of different types of lindose powder containing zinc sulfide of 30% or more. The whole process is carried out in an acidic (ra<7) environment, which consumes a large amount of sulfuric acid. The sulfuric acid has strong corrosiveness and requires high production equipment. The final discharged slag is acidic slag, which brings new pollution to the environment. High requirements, high production costs, and poor quality of the products obtained.