Nano-Micro Letters最新文献

The stable periodic porous shielding materials were prepared by combining the strategies of 3D printing and metamaterial design.

The relationship between porous material structure and electromagnetic interference shielding efficiency (EMI SE) effectiveness was deeply explored, revealing the important structural parameters for realizing tunable EMI SE property.

The optimized design of the periodic porous shielding box achieves effective EMI shielding in a wide wavelength range (over 2.4 GHz).

Exploiting single-atom catalytic activation and targeted adsorption properties, Ni single-atom active sites based on N, C coordination are constructed on the surface of two-dimensional MXene nanosheets (Ni–N–C/Ti₃C₂T_x), enabling highly sensitive and selective NH₃ gas detection.

The catalytic activation effect of Ni–N–C/Ti₃C₂T_x effectively reduces the Gibbs free energy of the sensing elemental reaction, while its electronic structure promotes the spill-over effect of reactive oxygen species at the gas–solid interface.

An end-sealing passivation strategy utilizing a conjugated hydrogen bond network of the conductive polymer was employed on MXene-based flexible electrodes, effectively mitigating the oxidative degradation of MXene-based gas sensors.

This review paper provides a comprehensive analysis of light–material interaction (LMI) parameters, offering insights into their significance in material processing.

It examines a wide array of photothermal and photochemical processes, showcasing their versatility in creating advanced materials for energy conversion and storage applications.

The review presents a multidisciplinary approach to advancing LMI technologies and highlights their potential contribution to the commercialization of future energy conversion and storage systems.

A novel cascade strategy is proposed to construct Pd-NiCo₂O₄ electrocatalyst.

First time discovery that Ni incorporation together with Pd loading is able to balance the competitive adsorption of OH^– and 5-hydroxymethylfurfural.

Pd–NiCo₂O₄ promotes both the indirect and direct synergistic oxidation process.

Pd–NiCo₂O₄ catalyst exhibits extraordinary current density and excellent Faradaic Efficiency at a low potential.

Photoresponsive black phosphorus (BP)/Ti₃C₂T_x composites were synthesized by a self-assembly strategy.

Enhanced gas sensitive property was achieved by visible light modulation.

Light activated virtual sensor array was fabricated based on BP/Ti₃C₂T_x composite.

Diagnosis of coronary heart disease was achieved with the help of machine learning.

Oxygen-vacancy-rich SiC@MoO₃ nanocomposite with strong reflection loss (− 50.49 dB at 1.27 mm thickness) and broadband absorption band (8.72 GHz at 2.68 mm thickness) were constructed via in situ etching strategy.

The presence of oxygen vacancy leads to an increased conductive loss and defect-induced dipole polarization, which plays significant role in attenuating the incident electromagnetic wave.

Challenges and future directions for 3D-printed metal-organic frameworks (MOFs) monoliths in environmental applications are discussed.

Various strategies for fabrication of 3D-printed MOF monoliths are summarized.

Advancements in 3D printing enable customizable and high-performance MOF monoliths.

3D orienting of MOFs opens avenues for applications in water treatment and gas adsorption.

Negative charged acidic polarity (NCAP) has been unveiled as the guideline for selecting additives to regulate electric double layer (EDL) for Zn-ion batteries.

NCAP glutamate has been verified to regulate EDL structure with synergetic effects, including preferential adsorption on Zn anode and reconstruction of hydrated Zn-ion clusters.

Adding NCAP additives, Zn|Cu half-cell achieves a high Coulombic efficiency of 99.83% for 2000 cycles, and NH₄V₄O₁₀|Zn full cell realizes a high-capacity retention of 82.1% for 3000 cycles.

The types, working principles, advantages and limitations of pattern recognition methods based on chemiresistive gas sensor array are reviewed and discussed comprehensively.

Outstanding and novel advancements in the application of machine learning methods for gas recognition in different important areas are compared, summarized and evaluated.

The current challenges and future prospects of machine learning methods in artificial olfactory systems are discussed and justified.