SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3887-6
The proliferation of 5G/6G communications and radar systems has intensified electromagnetic wave (EMW) leakage, interference, and thermal management challenges. This study presents a 3D MXene sponge/NiFe@NC heterostructure with tunable pore architecture, fabricated by pyrolyzing a polyurethane (PU) foam template uniformly coated with NiFe-decorated Ti3C2Tx MXene nanosheets. The resulting porous dielectric-magnetic network integrates interconnected MXene pathways with uniformly dispersed NiFe@NC nanoparticles, enabling synergistic dielectric-magnetic loss via conduction loss, dipole/interface polarization, and magnetic loss. Precise pore structure design enhances impedance matching and promotes multi-scattering and internal reflection of EMWs. An 'EMW-pore matching' mechanism is proposed, where pore size governs impedance matching at specific frequencies, enabling tunable absorption performance. The optimized absorber achieves a reflection loss (RL) of -67.84 dB, while radar cross-section (RCS) simulations confirm exceptional attenuation and stealth potential. Additionally, the 3D skeleton derived from PU foam confers remarkable thermal resistance and flame retardancy. This pore-regulation strategy provides a scalable route to designing lightweight, broadband, and thermally stable EMW absorbers for next-generation communication and stealth applications.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202605011
Phytoplankton are highly sensitive to environmental changes and respond rapidly, making their community dynamics crucial early warning indicators of lake ecosystem health. Previous studies have qualitatively analyzed the combined effects of multiple physicochemical water quality factors on phytoplankton communities, but few have quantitatively distinguished direct from indirect effects. This study employed correlation analysis, redundancy analysis, and structural equation modeling to investigate the spatiotemporal distribution of phytoplankton communities in Baiyangdian Lake and their driving factors. A total of 113 species belonging to 57 genera and 7 phyla were recorded. Phytoplankton density exhibited significant seasonal and spatial variability, peaking in summer. Diatoms and green algae dominated in spring, transitioning to cyanobacterial dominance in summer and autumn, and reverting to green algae in winter. Structural equation modeling revealed that water temperature had a total positive effect on phytoplankton biomass (β = 0.96), comprising a direct positive effect (β = 0.94, P < 0.05) and an indirect positive effect via increased abundance (β = 0.02). Total nitrogen (TN) had a negative total effect on biomass (β = -0.98), with a direct negative effect (β = -0.97, P < 0.05) and an indirect negative effect via reduced abundance (β = -0.01). TN also negatively affected abundance (β = -0.15, P < 0.05). These findings provide a scientific basis for ecosystem health assessment, eutrophication control, and biodiversity protection in Baiyangdian Lake.
SCIENCE CHINA Materials•2025•DOI: 10.1007/s40843-025-3535-8
The brain's selective visual attention mechanism (SVAM) enables robust visual recognition in noisy environments through diverse neural action potential peaks acting as filters. Spiking neural networks (SNNs) mimic this paradigm but limited noise immunity and high write current density hinder brain-like efficiency. Hardware implementing SVAM necessitates spiking spintronic devices with noise-resistant and low operation current densities; such devices remain unreported. Here, we report an orbit-torque (OT) actuated ferromagnetic spiking synapse and neuron featuring a tunable peak action potential. These are more akin to biological neurons with varying sensitivities to external sensory stimuli, thereby augmenting the perception aptitude of the system in complex surroundings. Capitalizing on the high-efficiency OT, the ferromagnetic device demands a write current density of 5 × 10^6 A/cm^2, which is an order of magnitude lower than other spiking devices actuated by spin-orbit torque. Leveraging these neuromorphic devices, an all-spin SNN with low current density and tunable action potential peak has been fabricated, successfully mimicking the SVAM. In complex noise environment, the SNN achieves 92% on Cifar-10 and 95% on MNIST dataset, surpassing state-of-the-art spin-based SNNs by 5%. Our work provides a promising avenue for exploring the SVAM-inspired spiking neuromorphic devices, enhancing the bionic performance of the SNNs.