Yongqian Du

A compact differential microwave sensor, based on an “eye-like” complementary split-ring resonator (CSRR), for complex permittivity detection to address the dual challenges of mitigating interresonator coupling and achieving a high sensitivity, is proposed in this work. The “eye-like” CSRR is split into two separate differential half-CSRRs by a slot gap with a “ocular pupil” (OP) at the center; thus, a differential sensing mode against environmental common mode interference is realized. By optimizing the slot gap space and the radii of the “OP,” the interresonator coupling is minimized. Moreover, by integrating two symmetric interdigital structures on both upper and lower “eyelids,” the electrical field distribution is intensified substantially, thereby enhancing sensitivity. The geometry and dimensions of the sensor are optimized based on a mathematical analysis of an equivalent lumped RCL circuit model of CSRR, which also provides the design principle of the sensor. The developed sensor is fabricated and tested with a compact geometric size of 19×14×0.76 mm. The device prototype is measured and characterized using water–ethanol solutions. Compared with the previous similar works, the sensor is small in size and has a high frequency detection resolution (FDR) of 20.1 MHz/ $\Delta \varepsilon ^{\prime }$ , with a sample volume as small as $0.41~\mu $ L.

In compact power electronic devices, magnetic-ring-free current sensors are increasingly preferred due to their compact size and lightweight nature. However, in high-precision small current measurements, the geomagnetic field can introduce substantial errors. To address this issue, a sensor chip using a bridge structure composed of four highly sensitive tunnel magnetoresistance (TMR) elements was employed, and a novel magnetic-ring-free current sensor was designed that eliminates geomagnetic field interference, thereby achieving precise small current measurements. This sensor operates in a zero-magnetic-flux state for the geomagnetic field, where the geomagnetic signal is fed back through a feedback coil, effectively canceling the geomagnetic field with the magnetic field generated in the feedback coil. This design enables the current sensor to achieve high-precision measurements. Experimental results showed that the current sensor achieved a sensitivity of 3.808 V/A and a measurement accuracy of ±1.854% within a sensing range of ±1.8 A. These findings offer a novel design strategy for future current sensors.

A high‐sensitivity and low start‐up voltage cold‐start circuit for wireless power harvesting is presented in this work. To improve conversion efficiency and reduce charge pump stages, a pipeline power supply uplifting clocking (PPSUC) driving scheme is proposed, which improves the conversion efficiency more than 45%. By adopting a two‐stage PPSUC driving Pelliconi charge pump, the proposed cold‐start circuit is designed and verified in a commercial 65‐nm MCOS process. Benefiting from the proposed PPSUC driving scheme, the cold‐start circuit demonstrates a low start‐up voltage of 170 mV and a high cold stat sensitivity of −32 dBm.

We have explored an approach to constructing reliable magnetic field sensors based on cobalt-based Schottky contacts, which has the potential to find practical applications when an applied magnetic field modifies the current–voltage (I–V) characteristics of heterostructures. For this aim, heterostructures based on a ferromagnetic film Co were deposited on a Si(100) substrate by means of an ultrathin Pt film. The electrical properties of Co/Pt/Si heterojunctions were investigated using temperature-dependent I–V characteristics. The magnetic transport properties of Co/Pt/Si heterojunctions have been investigated, and the results show that the experimental ratio of current, I(B)/I(0), measured in magnetic field B and zero field, is linearly related to magnetic field B and almost independent of the applied voltage. Detailed measurements of the sensitivity and linearity of a heterojunction-based self-referencing magnetic field sensor were performed. The results show that the linearity and sensitivity of the sensor increase with an increase in the applied voltage frequency, and the sensitivity of the sensor reaches up to 72.09 μA/T at a voltage frequency of 2000 Hz. The sensor is easy to integrate with existing semiconductor processes, has a simple structure, and can be used for geological applications such as energy exploration.

Full-duplex (FD) enables high spectrum efficiency and dynamic spectrum accessing, although its application is restricted by significant self-interference. In this work, we present an integrated, single antenna, wideband FD self-interference suppression front-end solution, targeting for short-range wireless communication. Based on the characteristic of bi-directional signal transparency of N-phase passive mixer, a mixer-first active electrical balance self-interference suppression architecture is proposed. As no costly and space-consuming out-of-chip circulator is needed, compared with traditional single antenna suppression solutions, it is attractive for cost and area saving In addition, to alleviate the multi-path effect, a two-tap baseband self-interference suppression is adopted, which also helps broaden the self-interference suppression bandwidth. The fabricated FD front-end chip, employing 180nm CMOS process, has a noise figure (NF) of 8.6dB, and at the maximum TX power, the NF is degrade by 4.9dB. Test results show the achieved self-interference suppression depth is up to 52dB over 30MHz, with a much smaller antenna interface and chip size which is 0.75 mm $^{2}$ , compared with other dual and signal antenna solutions. The wireless communication function of the propose FD front-end has been verified and the operation carrier frequency range is 0.4-1.2GHz.

Facing the problems of ohmic loss and short propagation length, the application of plasmonic waveguides is limited. Here, a triangle hybrid plasmonic waveguide is introduced, where a cylinder silicon waveguide is separated from the triangle prism silver waveguide by a nanoscale silica gap. The process of constant optimization of waveguide structure is completed and simulation results indicate that the propagation length could reach a length of 510 μm, and the normalized mode area could reach 0.03 along with a high figure of merit 3150. This implies that longer propagation length could be simultaneously achieved along with relatively ultra-deep subwavelength mode confinement due to the hybridization between metallic plasmon polarization mode and silicon waveguide mode, compared with previous study. By an analysis of fabrication errors, it is confirmed that this waveguide is fairly stable over a wide error range. Additionally, the excellent performance of this is further proved by the comparison with other hybrid plasmonic waveguides. Our work is significant to manipulate light waves at sub-wavelength dimensions and enlarge the application fields, such as light detection and photoelectric sensors, which also benefit the improvement of the integration of optical devices.

忆阻网络是一种基于忆阻器单元的大规模非线性电路, 在下一代人工智能、生物电子、高性能存储器等新兴研究领域发挥着重要作用. 描述忆阻器单元物理和电学特性的模型对忆阻网络的性能仿真具有显著影响. 然而, 现有模型主要为非解析模型, 应用于忆阻网络分析时可能存在收敛性问题. 因此, 提出了一种基于同伦分析法(homotopy analysis method, HAM)的忆阻器单元解析建模策略, 该策略具有解析性和收敛性优化的特点, 可提高忆阻器单元和相应忆阻网络的收敛性. 此外, 还提出了一种面向忆阻器单元模型的验证准则, 以验证模型在大规模忆阻网络中的适用性. 通过忆阻器单元和忆阻矩阵网络的长时演化实验以及与传统非解析(数值)方法的比较, 验证了所提策略的解析性和收敛性优势; 利用不同类型忆阻器单元和输入的实验, 验证了该策略的扩展性. 进一步地, 基于上述实验, 揭示了忆阻网络仿真出现收敛性问题的潜在原因. 该策略具有潜力应用于基于忆阻网络的新兴研究.

At present, studies on macrophage proteins mainly focus on biological stimuli, with less attention paid to the responses of macrophage proteins to physical stimuli, such as electric fields. Here, we exploited the electric field-sensitive hub proteins of macrophages. RAW 264.7 macrophages were treated with a direct current electric field (dcEF) (200 mV/mm) for four hours, followed by RNA-Seq analysis. Differentially expressed genes (DEGs) were obtained, followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) and protein–protein interaction (PPI) analysis. Eight qPCR-verified DEGs were selected. Subsequently, three-dimensional protein models of DEGs were modeled by Modeller and Rosetta, followed by molecular dynamics simulation for 200 ns with GROMACS. Finally, dcEFs (10, 50, and 500 mV/mm) were used to simulate the molecular dynamics of DEG proteins for 200 ns, followed by trajectory analysis. The dcEF has no obvious effect on RAW 264.7 morphology. A total of 689 DEGs were obtained, and enrichment analysis showed that the steroid biosynthesis pathway was most affected by the dcEF. Moreover, the three-dimensional protein structures of hub proteins were constructed, and trajectory analysis suggested that the dcEF caused an increase in the atomic motion of the protein in a dcEF-intensity-dependent manner. Overall, we provide new clues and a basis for investigating the hub proteins of macrophages in response to electric field stimulation.

Resistive random access memory device (RRAM) has been widely used in various novel circuit systems, such as memory, artificial intelligence, and neural networks, due to its unique memory characteristics. However, there are very few studies focusing on analytic modeling of RRAM. In this work, modeling for solving analytic approximate solution to the state variable of RRAM, based on the proposed Multistage Homotopy Analysis Method (MuHAM), is proposed. Different from traditional HAM, the time span under consideration is divided into many subintervals, then the convergence control parameter in each subinterval is optimized to achieve high approximation accuracy. By simulating and comparing the obtained analytic solutions with solutions solved by other traditional homotopy-based modeling methodologies and by numerical analyses, we verified that MuHAM has higher Quality Factor (introduced to evaluate the model accuracy and computational cost comprehensively), hence improving the simulation efficiency. Besides the classical Hewlett-Packard (HP) RRAM, some current RRAMs are also verified. MuHAM also has the advantages of enabling both qualitative and quantitative analyses, and immunity to convergence issues. It is particularly suitable for the analytic modeling of the other novel memory devices having strong nonlinearity.

Recently, nanosecond pulsed electric field (nsPEF) has been considered as a new tool for tumor therapy, but its molecular mechanism of function remains to be fully elucidated. Here, we explored the cellular processes of Jurkat cells exposed to nanosecond pulsed electric field. Differentially expressed genes (DEGs) were acquired from the GEO2R, followed by analysis with a series of bioinformatics tools. Subsequently, 3D protein models of hub genes were modeled by Modeller 9.21 and Rosetta 3.9. Then, a 100 ns molecular dynamics simulation for each hub protein was performed with GROMACS 2018.2. Finally, three kinds of nsPEF voltages (0.01, 0.05, and 0.5 mV/mm) were used to simulate the molecular dynamics of hub proteins for 100 ns. A total of 1769 DEGs and eight hub genes were obtained. Molecular dynamic analysis, including root mean square deviation (RMSD), root mean square fluctuation (RMSF), and the Rg, demonstrated that the 3D structure of hub proteins was built, and the structural characteristics of hub proteins under different nsPEFs were acquired. In conclusion, we explored the effect of nsPEF on Jurkat cell signaling pathway from the perspective of molecular informatics, which will be helpful in understanding the complex effects of nsPEF on acute T-cell leukemia Jurkat cells.