The unique properties of MoS₂ nanosheets make them a promising candidate for high-performance room temperature gas detection. Herein, few-layer MoS₂ nanosheets (FLMN) prepared via mechanical exfoliation are coated on a substrate with interdigital electrodes for room-temperature NO₂ detection. Interestingly, compared with other NO₂ gas sensors based on MoS₂, FLMN gas sensors exhibit high responsivity for room-temperature NO₂ detection, and NO₂ is easily desorbed from the sensor surface with an ultrafast recovery behavior, with recovery times around 2 s. The high responsivity is related to the fact that the adsorbed NO₂ can affect the electron states within the entire material, which is attributed to the very small thickness of the MoS₂ nanosheets. First-principles calculations were carried out based on the density functional theory (DFT) to verify that the ultrafast recovery behavior arises from the weak van der Waals binding between NO₂ and the MoS₂ surface. Our work suggests that FLMN prepared via mechanical exfoliation have a great potential for fabricating high-performance NO₂ gas sensors.

Based on density functional theory, we investigated the magnetic properties of 5d transition metal (TM) atoms at the porous sites of graphene-like carbon nitride (g-C₃N₄).

Oxygen vacancies (V_O) and their migration and redistribution are believed to be the dominant factors resulting in the degradation of ferroelectrics. Thus, suppressing the formation and mobility of V_O is quite crucial for the physical properties of ferroelectric materials. In this paper, the ab-biaxial strain effects on V_O and their migration process in prototype perovskite ferroelectric BaTiO₃ were studied by first principles total energy calculation. It is found that the formation energies for the two symmetrically inequivalent V_O are enhanced under compressive strain. V_O migration path between V_c (V_O is located along the c-axis) and V_ab (V_O is located in the ab-plane) shows an “S” shape. The V_O migration barrier between V_c and V_ab is enhanced by the compressive strain while lowered by the tensile strain. These results suggest that the ferroelectricity degradation induced by V_O and their migration can be effectively mitigated by applying compressive strain.

Recently, Long-term gas detection has attracted much attention due to its being a key factor for electronic nose (E-Nose) applications. However, the sensor drift effect can significantly reduce the performance of the sensor. Therefore, in this work, we proposed a new drift compensation method by optimizing feature selection, model construction, and training methods to study drift-resistant gas detection based on convolutional neural network methods. Firstly, the attention mechanism is used to screen the specific features of the gas data and remove the low-weight features. Moreover, a multi-scale feature extraction network is designed so that the features fused by the three-layer convolution are used as the final classification feature input to extract the depth features keeping the drift unchanged. Simultaneously, the segmented training method and the targeted cyclic training model are adopted to reduce the required experimental data. Importantly, based on the largest gas drift dataset currently, the proposed method maintains the average gas detection accuracy beyond 80% in three years, and the long-term stability of gas detection is effectively improved. Therefore, our findings provide an effective way to solve the sensor drift effect.

Flexible lithium-ion batteries (FLIBs) have rapidly developed as promising energy storage devices for flexible and wearable electronics, owning to the advantages of high energy density, fast charge–discharge, no memory effect and stable cycle performance. Research on flexible electrodes has attracted widespread attention to maintain stable electrochemical function under deformation. Carbon materials are some of the most popular lithium-ion battery (LIB) anode materials owing to their low cost, high conductivity and excellent stability. However, the scaled-up fabrication of flexible electrodes based on carbon-based materials for high-performance FLIBs is still challenging. Herein, the fabrication strategies for FLIBs based on carbon materials such as carbon nanofibers (CNFs), carbon nanotubes (CNTs), graphene, graphdiyne (GDY) and carbon aerogels (CAs) are reviewed in terms of macroscopic electrode material preparation, property optimization and structure design. Furthermore, fabrication strategies and structure design methods for electrodes are proposed to improve energy capacity, cycle stability, conductivity and flexibility of FLIBs. This minireview can offer potential directions for the novel design of flexible carbon-based anodes employed in FLIBs.

Comprehensive first-principle calculations indicate that the oxygen vacancy (V_O) configuration of a prototypical perovskite oxide PbTiO₃ (PTO) can be tuned by strain engineering. Remarkably, we found that V_O located along the c axis (V_c), normally resulting in a polarization-harming tail-to-tail domain configuration in strain-free PTO ($V_c^{\mathit{u}\mathit{d}}$ ), can be readily tuned to a polarization-harmless head-to-tail domain configuration ($V_c^{\mathit{s}\mathit{w}}$ ) by applying an ab-biaxial compressive strain of 3%. Also, V_O located in the ab-plane (V_ab), another type of polarization-harmless vacancy, can be stabilized by applying a compressive strain of 2%.