As an emerging memory device, memristor shows great potential in neuromorphic computing applications due to its advantage of low power consumption. This review paper focuses on the application of low-power-based memristors in various aspects. The concept and structure of memristor devices are introduced. The selection of functional materials for low-power memristors is discussed, including ion transport materials, phase change materials, magnetoresistive materials, and ferroelectric materials. Two common types of memristor arrays, 1T1R and 1S1R crossbar arrays are introduced, and physical diagrams of edge computing memristor chips are discussed in detail. Potential applications of low-power memristors in advanced multi-value storage, digital logic gates, and analogue neuromorphic computing are summarized. Furthermore, the future challenges and outlook of neuromorphic computing based on memristor are deeply discussed.

The origin of near-infrared (NIR) emission by Mn²⁺ has sparked intense academic debates for decades. However, to date, none of the proposed hypotheses have garnered widespread consensus. This study validates that Mn²⁺ positioned within a 6-coordinate octahedral lattice, exhibiting a strong crystal field akin to the AlO₆ site, possesses the capability to produce NIR emission. The results of this study offer a novel perspective for the progress of efficient Mn²⁺-doped NIR phosphors.

The NEAL team at the University of South China has successfully developed HARMONY2.0, an upgraded version of their higher-order modes diffusion code HARMONY1.0. By adopting a hybrid two-step methodology combining MC(Monte Carlo) homogenization and deterministic higher-order modes calculation, this advancement addresses the limitations of deterministic methods in handling complex geometries and energy spectrum adaptation, while avoiding the computational inefficiency inherent to MC approaches. The integration of OpenMP-based parallel computing further accelerates the process, significantly enhancing the capability for reactor higher-order modes analysis. This progress provides critical technical support for key applications such as reactor reactivity measurements and online monitoring.

A research team at the University of Seville, Spain, developed a novel extension of virus machines, an emerging computing model that draws inspiration from how viruses propagate among hosts. These super virus machines, as the team calls them, address time efficiency limits in basic virus machines. This work was published under the title "Super Virus Machines: Faster Virus Transmission, More Efficiency Using Superchannels" on March 21 in Intelligent Computing, a Science Partner Journal.

Here, researchers from Laval University, Harbin Institute of Technology, University of Toronto, University of L’ Aquila, and University of Rome proposed a frequency multiplexed photothermal correlation tomographic (FM-PCT) technique. This approach overcomes the limitations of 2D imaging modes in infrared thermography, as well as the challenges of low imaging speed, narrow field of view, and low resolution in photothermal imaging.

The leading researcher, Dr Andreas Mandelis, commented: “It is these conditions that, for the first time, make FM-PCT a leading candidate for implementation in fast-turn-around quality control situations, such as industrial manufacturing environments.”

A research article published by the University of Macau presented a robotic US scanning system based on a hybrid active–passive force control method, which can be helpful in modern medical treatment via US imaging.

 

The new research paper, published on May. 2 in the journal Cyborg and Bionic Systems, summarized a robotic ultrasound scanning system with a constant-force end-effector. Its uniqueness is the introduction of a hybrid active–passive force control approach to maintaining a constant contact force between the ultrasound probe and the continually changing surface.

On June 3, Elsevier released the 2024 CiteScore rankings, featuring 33 Tsinghua University Press (TUP) journals--a 17.2% increase in indexed titles compared to 2023.