High-temperature superconductivity in cuprates arises from an electronic state that remains poorly understood. We report the observation of a related electronic state in a noncuprate material, strontium iridate (Sr2IrO4), in which the distinct cuprate fermiology is largely reproduced. Upon surface electron doping through in situ deposition of alkali-metal atoms, angle-resolved photoemission spectra of Sr2IrO4 display disconnected segments of zero-energy states, known as Fermi arcs, and a gap as large as 80 millielectron volts. Its evolution toward a normal metal phase with a closed Fermi surface as a function of doping and temperature parallels that in the cuprates. Our result suggests that Sr2IrO4 is a useful model system for comparison to the cuprates.

Memristors with history‐dependent resistance are considered as artificial synapses and have potential in mimicking the massive parallelism and low‐power operation existing in the human brain. However, the state‐of‐the‐art memristors still suffer from excessive write noise, abrupt resistance variation, inherent stochasticity, poor endurance behavior, and costly energy consumption, which impedes massive neural architecture. A robust and low‐energy consumption organic three‐terminal memristor based on ferroelectric polymer gate insulator is demonstrated here. The conductance of this memristor can be precisely manipulated to vary between more than 1000 intermediate states with the highest OFF/ON ratio of ≈104. The quasicontinuous resistive switching in the MoS2 channel results from the ferroelectric domain dynamics as confirmed unambiguously by the in situ real‐time correlation between dynamic resistive switching and polarization change. Typical synaptic plasticity such as long‐term potentiation and depression (LTP/D) and spike‐timing dependent plasticity (STDP) are successfully simulated. In addition, the device is expected to experience 1 × 109 synaptic spikes with an ultralow energy consumption for each synaptic operation (less than 1 fJ, compatible with a bio‐synaptic event), which highlights its immense potential for the massive neural architecture in bioinspired networks.

Novel hierarchical nanostructures of nickel, which were assembled by well-aligned hexagonal nanoplatelets, were fabricated through a simple solution method. The process involved the reduction of nickel dimethylglyoximate with hydrazine under controlled conditions. Based on a series of contrast experiments, the formation mechanism of the flowers was proposed, which could be ascribed to the cooperative effect of the complexant of dimethylglyoxime, a proper reaction rate, and inherent magnetic interactions. The present work provided an example for the synthesis of magnetic assembly nanostructures through properly selection of the reaction conditions, which were independent of any surfactants or external magnetic field.

Due to the lack of a general descriptor to predict the activity of nanomaterials, the current exploration of nanozymes mainly depended on trial-and-error strategies, which hindered the effective design of nanozymes. Here, with the help of a large number of Ni−O−Co bonds at the interface of heterostructures, a prediction descriptor was successfully determined to reveal the double enzyme-like activity mechanisms for Ni/CoMoO 4 . Additionally, DFT calculations revealed that interface engineering could accelerate the catalytic kinetics of the enzyme-like activity. Ni−O−Co bonds were the main active sites for enzyme-like activity. Finally, the colorimetric signal and intelligent biosensor of Ni/CoMoO 4 based on deep learning were used to detect organophosphorus and ziram sensitively. Meanwhile, the in situ FTIR results uncovered the detection mechanism: the target molecules could block Ni−O− Co active sites at the heterostructure interface leading to the signal peak decreasing. This study not only provided a well design strategy for the further development of nanozymes or other advanced catalysts, but it also designed a multifunctional intelligent biosensor platform. Furthermore, it also provided preferable ideas regarding the catalytic mechanism and detection mechanism of heterostructure nanozymes.

The ability to synthesize new complex oxide materials that belong to any of the large number of known oxide structural families relies typically on a general understanding of the relationship between the specific structure type and the chemical composition of its members. However, before one can create such a structure-composition relationship that enables the synthesis of new members, one needs structural information about a sizable number of existing compositions belonging to this structural family, somewhat of a ''chicken or the egg'' problem. In this Highlight we will use one family of oxides, specifically oxides related to the hexagonal perovskite structure, to illustrate how exploratory crystal growth methods have been used successfully to synthesize enough diverse compositions to enable the formulation of a general structural description. Furthermore, by now it appears that enough members with different compositions have been synthesized so that one can attempt to create a structurecomposition relationship that has predictive powers.