Electrically Engineering Synthetic Magnetic Fields for Polarized Photons

Research Report: Electrically Controlled Engineering of Synthetic Magnetic Fields in Polarized Photons Academic Background and Research Purpose In recent years, synthetic gauge theory has shown its potential in controlling the propagation of light and its state evolution in non-magnetic photonic systems. However, the synthetic magnetic fields gener...

Thresholds and Mechanisms of Human Magnetophosphene Perception Induced by Low Frequency Sinusoidal Magnetic Fields

Threshold and Mechanisms of Magnetophosphene Perception Background The effect of Magnetic Fields (MF) on the human body has long been a hot topic in scientific research. Extremely Low-Frequency Magnetic Fields (ELF-MF) are widespread in daily life, primarily originating from power lines (50⁄60 Hz) and household appliances. These magnetic fields can...

Regulation of Metal Bond Strength Enables Large-Scale Synthesis of Intermetallic Nanocrystals for Practical Fuel Cells

In recent years, fuel cells, as a clean and renewable energy technology, have garnered widespread attention. However, the extensive application of fuel cells faces the challenge of the stability of oxygen reduction reaction (ORR) electrocatalysts. L10-structured intermetallic nanocrystals (INCs) with chemically ordered structures, due to their lowe...

Sliding Mode Control for Uncertain Fractional-Order Reaction-Diffusion Memristor Neural Networks with Time Delays

Application of Sliding Mode Control in Uncertain Fractional-Order Reaction-Diffusion Memristor Neural Networks In recent years, as neural networks have been widely applied in various fields, the research on their control and stability has gained increasing attention. Fractional-order (FO) memristor neural networks (MNNs), due to their ability to si...

Dynamics of Heterogeneous Hopfield Neural Network with Adaptive Activation Function Based on Memristor

Study of Heterogeneous Hopfield Neural Networks: Dynamic Behavior Analysis Combining Adaptive Activation Functions and Memristors This study investigates the impact of nonlinear factors on the dynamic behavior of neural networks. Specifically, activation functions and memristors are commonly used as nonlinear factors to construct chaotic systems an...