Memristor, based on the principle of biological synapse, is recognized as one of the key devices in confronting the bottleneck of classical von Neumann computers. However, conventional memristors are difficult to continuously adjust the conduction and dutifully mimic the biosynapse function. Here, TiO 2 films with self-assembled Ag nanoclusters implemented by gradient Ag dopant are employed to achieve enhanced memristor performance. The memristors exhibit gradual both potentiating and depressing conduction under positive and negative pulse trains, which can fully emulate excitation and inhibition of biosynapse. Moreover, comprehensive biosynaptic functions and plasticity, including the transition from short-term memory to long-term memory, long-term potentiation and depression, spike-timingdependent plasticity, and paired-pulse facilitation, are implemented with the fabricated memristors in this work. The applied pulses with a width of hundreds of nanoseconds timescale are beneficial to realize fast learning and computing. High-resolution transmission electron microscopy observations clearly demonstrate that Ag clusters redistribute to form Ag conductive filaments between Ag and Pt electrode under electrical field at ON-state device. The experimental data confirm that the oxides doped with Ag clusters have the potential for mimicking biosynaptic behavior, which is essential for the further creation of artificial neural systems.

From Deep Blue to AlphaGo, artificial intelligence and machine learning are booming, and neural networks have become the hot research direction. However, due to the size limit of complementary metal–oxide–semiconductor (CMOS) transistors, von Neumann‐based computing systems are facing multiple challenges (such as memory walls). As the number of transistors required by the neural network increases, the development of neural networks based on the von Neumann computer is limited by volume and energy consumption. As the fourth basic circuit element, memristor shines in the field of neuromorphic computing. The new computer architecture based on memristor is widely considered as a substitute for the von Neumann architecture and has great potential to deal with the neural network and big data era challenge. This article reviews existing materials and structures of memristors, neurophysiological simulations based on memristors, and applications of memristor‐based neural networks. The feasibility and advancement of implementing neural networks using memristors are discussed, the difficulties that need to be overcome at this stage are put forward, and their development prospects and challenges faced are also discussed.

Doped‐HfO2 thin films with ferroelectricity have attracted great attention due to their potential application in semiconductor industry as negative capacitance and resistance switching memory. Despite Hf0.5Zr0.5O2 (HZO) thin films having the most robust ferroelectric properties among all doped‐HfO2 thin films, the realization of single orthorhombic phase HZO thin films is not achieved, while the direct evidence between the structural–properties relationship of orthorhombic phase HZO and ferroelectricity is not confirmed. In this work, the growth of single orthorhombic phase HZO thin films with decent ferroelectricity and resistive switching behavior is reported. With the aid of advanced structural characterization techniques, the HZO thin film is confirmed to be in the single orthorhombic phase. Next, using scanning probe microscopy techniques and macroscopic ferroelectric measurements, the single phase HZO thin films exhibit ferroelectric properties with a remanent polarization of about 20 µC cm−2. Interestingly, the HZO thin film shows ferroelectric resistive switching with an ROFF/RON ratio of about 16 100% with excellent device performance. Furthermore, brain‐like learning behavior is also observed in the HZO thin film. These results may serve to stimulate the study of ferroelectric properties of HZO thin films and their application in the electronic industry.

Reported is a novel and simple method for the preparation of polymer spheres bearing hemispherical surface bumps where one type of polymer chains concentrates. The method is used to produce spheres with a diameter between approximately 30 and approximately 500 nm. Spheres with chain-segregated bumpy surfaces may find applications in drug delivery and other areas.