Prof. XU Teng | Publications & Academic Profile | SinoGreenTech

Research Publications & English Decoded Briefs

Showing 2 publications

Chinese Journal of Environmental Engineering•2026•DOI: 10.12030/j.cjee.202510089

Removal Mechanisms of Fe3O4@MIL-100(Fe) for Microplastics in Water

Microplastics (MPs) are frequently detected in various water bodies, posing increasing environmental risks. This study synthesized magnetic Fe3O4@MIL-100(Fe) microspheres via an in-situ one-step hydrothermal method and investigated their adsorption removal mechanisms for polystyrene (PS) and polylactic acid (PLA) microplastics. The composite exhibited a core-shell structure with a high specific surface area of 848.6 m2·g−1. Adsorption kinetics showed that PLA followed a pseudo-second-order model, while PS fitted both pseudo-first-order and pseudo-second-order models. Equilibrium data for both MPs were well described by the Freundlich isotherm. Removal efficiencies for PLA and PS increased from 58.18% and 49.66% to 98.90% and 98.58%, respectively, as pH decreased, and from 64.24% and 21.58% to 97.05% and 94.63% with increasing ionic strength. The removal mechanism involved synergistic physical-chemical interactions: hydrogen bonding dominated for PLA, with some complexation, while π–π interactions and hydrogen bonding were primary for PS. The material demonstrated excellent reusability over multiple cycles. These findings highlight the potential of Fe3O4@MIL-100(Fe) for efficient removal of MPs from water, offering a novel approach for controlling emerging contaminants.

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SCIENCE CHINA Materials•2025•DOI: 10.1007/s40843-025-3535-8

Efficient Orbit-Torque Driven Spiking Neuromorphic Device Mimicking the Selective Attention Mechanism for Self-Adaptive Recognition

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.

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