Efficient blood cell medium exchange is essential for eliminating plasma interference and providing a stable microenvironment in applications such as drug screening and flow cytometry. The widely used centrifugation method is limited by high sample consumption, discontinuous processing, and poor integration potential. Here, we present a high-frequency acoustofluidic platform that enables continuous, on-chip medium exchange by directing blood cells from the sample stream into a buffer stream by acoustic manipulation. By systematically optimizing platform parameters through numerical simulations and experimental validation, we achieve continuous and stable operation with a cell recovery rate of 92.9%. Notably, the unique helical trajectories of motion induced in cells by high-frequency acoustics, when combined with the well-engineered microchannel geometry and laminar interfaces, enable effective cell washing during transfer, removing up to 96% of the original medium. Additionally, owing to the universality and biocompatibility of acoustic manipulation, the proposed platform shows strong potential for medium exchange in a variety of cells and particles.

Graphene/Ti composites have attracted significant attention from researchers owing to their exceptional strength, ductility, and impact resistance. However, the high chemical reactivity of titanium complicates the interfacial structure and presents challenges in the development of graphene/titanium composites. Consequently, it is crucial to investigate the microscopic mechanisms for modifying the graphene/titanium interface by introducing alloying elements. In this study, the thermodynamic stability, interfacial shear properties, and electronic structure of graphene/titanium interfaces doped with various alloying elements are evaluated using first-principles calculations. The results indicate that the alloyed graphene/Ti interface exhibits good thermodynamic stability in the ground state. Specifically, the graphene/Ti interface shows a greater tendency to form alloyed interfaces when doped with 5d metal elements such as Os, Re, or Ir. Furthermore, the incorporation of alloying elements significantly enhances the shear properties of the graphene/Ti interface. Notably, the Mn-alloyed graphene/Ti interface exhibits superior toughness, while the Ir-alloyed interface reveals a substantial increase in shear strength, primarily due to the strengthening of C–Ti covalent bonds.

We propose a simplified Lithographie, Galvanoformung, Abformung (LIGA)-like method for fabricating silicon-based, high-aspect-ratio x-ray absorption gratings by bonding silicon substrates with different resistivities, creating a pre-positioned electrode structure. This design significantly enhances conductivity contrast between the trench bottoms and sidewalls, enabling stable and uniform bottom-up gold electroplating without relying on specialized electrolytes or complex procedures. COMSOL simulations and nickel electroplating experiments verify the bottom-up growth characteristics. The fabrication of void-free gold absorption gratings (period 6 μm, depth 55 μm) is verified by scanning electron microscopy and x-ray phase-contrast imaging. Our method allows the use of commercially available cyanide-free gold plating solutions, making silicon-based absorption gratings more accessible and greatly benefiting the advancement of x-ray phase-contrast imaging technology. Furthermore, the method offers a practical alternative to conventional LIGA technology for microsystem applications.

This study aims to develop a prosthetic hand grip control system based on machine vision to improve the quality of life and self-care capacity of patients. In medicine and rehabilitation engineering, machine vision technology has been widely used to design intelligent prostheses to help patients restore limb function. Grip strength control is one of the key challenges in developing prosthetic hands; for example, patients need to appropriately control the grip strength of the prosthetic hand depending on the nature and size of the object to be gripped to prevent it from slipping or being damaged. This study combines machine learning and deep learning techniques to determine object grip information by analyzing images of such objects, including their type, texture, and size, so as to select the appropriate grip strength threshold. The electromyographic gesture-control mode is integrated with the visual recognition system to achieve active detection and control of the intelligent prosthetic hand. This research is also transplanted into the K210 main control board for offline recognition to achieve more efficient real-time performance. The experimental results demonstrate that the system achieves an object recognition accuracy rate of 90%, and the real-machine recognition rate is above 85%. The system successfully implements adaptive grasping for eggs (fragile items) and water bottles (rigid objects).

Owing to the complexity of analyzing gases with known and unknown chemical interferences, existing single metal–oxide–semiconductor (MOS) gas sensors fail to generate distinguishable signals for different gases. Besides, previous gas recognition algorithms have only extracted local or global features from sensor signals, with no interaction between local and global features. In this paper, an individual microelectromechanical systems (MEMS)-based MOS sensor is applied to generate multivariable signals under pulsed operating modes of an integrated microheater in the MEMS chip. This sensor is able to generate distinguishable gas signals. We also propose a multitask guided gas recognition algorithm that utilizes interacting local and global features of multivariable signals and is able to perform gas classification and quantitative concentration analysis simultaneously. Specifically, to capture the time series information from sensor response signals, a Gramian angular field module is applied to convert the signal into a two-dimensional image. Then, a multi-scale convolutional neural network and Transformers are combined to extract multiscale local and global features, which strengthens the discriminative ability for different gases with different concentrations. Finally, a multitask module is introduced to perform the classification and regression simultaneously. Extensive experiments demonstrate the effectiveness of the proposed algorithm, which achieves an average recognition accuracy of 96.6% for five types of gases: ammonia, ethanol, formaldehyde, water vapor, and methanol. Compared with many classical recognition algorithms, the proposed algorithm yields lower mean absolute error and root mean square error in concentration estimation, which demonstrates its superiority. The pulsed operating modes combined with the proposed algorithm enable individual MEMS sensor to achieve intelligent for gas recognition, which is crucial for applications to the Internet of Things and artificial intelligence.

Inconel-718 is widely utilized in the aerospace and defense industries owing to its exceptional strength and thermal resistance. However, these properties make grinding difficult, often leading to rapid tool wear and poor surface quality. This study experimentally evaluates the use of an ecofriendly surface-active medium (SAM) with ultrasonic-assisted surface grinding (USG) as part of an advanced manufacturing process. The goal is to improve machining performance while reducing cutting force and material usage. To evaluate the efficacy of the proposed strategy, the key processing parameters considered are the depth of cut ap (15–35 μm), spindle speed ω (8000–16 000 rpm), ultrasonic amplitude A (2–10 μm), and feed rate fr (5–25 mm/min). The results indicate that the integration of an SAM with high-frequency vibrations significantly reduces grinding forces (by up to 39.86%), enhances tool life, and improve surface finish by as much as 56.8%. Additionally, the optimal cutting conditions (ap= 30 μm, A = 10 μm, ω = 16 000 rpm, and fr = 20 mm/min) are found to provide superior cutting performance. The proposed sustainable method demonstrates considerable potential for machining Inconel-718 using better machining processes.

We report on the fabrication of superconducting nanowire arrays through photothermal effects induced by nano laser direct writing (NLDW), with progressively reduced spacing between the laser paths. The superconducting nanowire arrays were fabricated on 50 nm-thick Nb films via sputtering deposition on high-resistivity silicon substrates. Large-scale fabrication of superconducting nanowire arrays using NLDW has advantages such as cost-effectiveness, efficiency, and design flexibility. Furthermore, the thermal effects induced the degradation of Nb films with narrowing spacing, which were analyzed using simulated temperature distribution, electron probe x-ray micro-analysis, and electrical transport measurements. Specifically, the critical point of spacing (6.7 pixels) was confirmed, at which the Nb nanowires exhibited resistive behavior at 4.0 K. Similar to the pattern overlap and multiple exposure techniques in semiconductor fabrication, by designing appropriate spacing, the width of the remaining functional Nb film could be reduced to several tens of nanometers or even down to a few nanometers. Compared with traditional micro–nano fabrication techniques such as electron beam lithography and focused ion beams, the NLDW technique provides a reliable, economical, and reproducible pathway for scaling up superconducting circuits, as well as an avenue to conduct nanoscale thermal engineering on superconducting materials for basic scientific studies.

As advanced nanoactuators, nano flexible scanning platforms can quickly and stably achieve multi-axis scanning positioning at the nanoscale, and they are widely used in advanced fields such as chemical detection, micro–nano measurement, microelectromechanical control, and optical positioning. Such platforms usually include horizontal and vertical scanners, whose mechanical structure and combined multi-axis scanning will directly affect the response speed and displacement performance. The circuit and measurement system and nonlinear control algorithm are also crucial, since small changes to these can affect platform resolution and stability. Therefore, in this paper, a nano scanning platform with flexible hinge structure and a dedicated circuit and measurement system is designed. The platform has a three-axis structure combining series and parallel connections. An improved sliding mode closed-loop controller is proposed for nonlinear errors, which further improves the scanning accuracy of the platform through subdivision calculation and segmented calibration methods. Experiments prove the effectiveness of the nano flexible scanning platform and its control algorithm.

Harmonic mode-locking (HML) in soliton fiber lasers is crucial for generating high-repetition-rate pulse trains beyond the fundamental cavity frequency, enabling advanced applications in, for example, optical communication and precision sensing. However, achieving HML in experiments is challenging, owing to its inherent instability and high sensitivity to laser parameters, resulting in complex and iterative adjustments. In this paper, a novel HML technique utilizing bidirectional adjustment of pump power is proposed, and it is experimentally demonstrated in an all-fiber hybrid mode-locked soliton laser. By first increasing the pump power to generate a soliton bunch with a certain number of pulses and then gradually decreasing it, HML can be achieved at an order corresponding to the number of pulses in the soliton bunch. Experimental results on the evolution of temporal pulse trains during bidirectional adjustment of the pump power enable a relationship to be established between pump power and soliton bunching with increasing pump power, and reveal the collapse of the soliton bunch and subsequent gradual uniform distribution of solitons into an HML state with decreasing pump power. Second- to sixth-order HML is successfully generated using the proposed technique, and an analysis of the results provides a deeper understanding of the observed pulse dynamics.

Droplet-based microfluidics have drawn much attention in recent years and have been successfully applied in biochemical analysis, material synthesis, and biomedical engineering. Precise and flexible manipulations of droplets are the basis of various applications. Numerous techniques have been introduced to achieve on-demand control of droplets, including electric, magnetic, acoustic, optical, and thermal methods. Among these, the combination of acoustics and microfluidics (termed acoustofluidics) has shown great potential and advantages in droplet manipulation as it is non-invasive, high-precision, low-cost, easily integrated, and biocompatible. Here, we summarize recent works on acoustofluidic manipulations of droplet-based microfluidics. This paper is structured into three main sections. First, the commonly used acoustic devices in acoustofluidics and their working principles are introduced. Such acoustic devices include interdigital transducers, Lamb wave resonators, and bulk acoustic resonators, and generate acoustic waves with frequencies ranging from kilohertz to gigahertz. Second, the forces and effects involved in droplet manipulations using acoustofluidics are analyzed. Third, the manipulation processes of droplet microfluidics using various acoustofluidic techniques are summarized and compared with other methods, including droplet generation, mixing, splitting, fusion, sorting, transportation, and internal particle patterning. Finally, current challenges and future prospects for acoustofluidic manipulation techniques for droplet-based microfluidics are discussed.