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The state-of-the-art triboelectric nanogenerator (TENG) technology has numerous advantages and creates new prospects for the rapid development of the Internet of Things (IoT) in marine environments. Here, to accelerate the application process of TENG, an elaborately designed multilayered sleeve-structured hybrid nanogenerator (M-HNG) is developed to efficiently and persistently harvest marine energy. The M-HNG integrates an electromagnetic nanogenerator (EMG) with four coils and a multilayered sleeve-structured TENG (MS-TENG) with three freestanding layer units to increase spatial utilization efficiency. Moreover, rabbit fur strips are introduced to enhance the output performance and strengthen the durability of TENG. Therefore, the MS-TENG has high durability due to its soft-contact structure, maintaining its performance even after 240,000 cycles. When a 1000 μF capacitor is charged by M-HNG utilizing a power management circuit (PMC), the stored energy is increased from 2.62 mJ to 140.11 mJ, representing a significant improvement of 52-fold. The M-HNG triggered by water waves has successfully powered various small electronic devices, including 1200 LED lights, nine thermo-hygrometers, a water quality testing pen, and water level alarms. The proposed M-HNG effectively harvests low-frequency water wave energy, introducing an innovative concept for constructing a hybrid TENG with enhanced density and durability.

With the intensification of explosive-based terrorism attack and environmental concerns, the innovation of high-efficiency and portable sensors for facile, rapid, and reliable monitoring of explosives has become one of the major demands in societies. Herein, a reliable and easy-to-use cataluminescence sensor system based on Dy 3+ doping La 2 O 3 nanorod catalysts has been developed for the identification and detection of six types of military explosive vapors, including homologous compounds and even isomers. The efficient discrimination is to make full use of the thermodynamic and kinetic information that can be extracted from the catalytic oxidation process of explosive molecules on various sensing materials, that is, the response signal and response time to generate the fingerprint of each target compound, while the rapid detection of the strategy can be manifested in response toward six military explosive vapors within 2.5 s and recover within 4 s. Meanwhile, the quantitative analysis of the explosives by the sensor system was realized based on 0.8%Dy:La 2 O 3 with optimal catalytic activity, and the detection limits of NB, m-MNT, m-DNB, PNT, DNT, and TNT can reach 0.62, 0.49, 0.63, 0.38, 0.023, and 0.067 μg mL -1 . In this research, we also constructed a novel sensor device and detection platform for explosive monitoring, which is of great significance for providing a new sensing principle for the efficient identification of explosives.

The treatment and detection of ozone have been widely studied in recent decades with respect to toxicity and contamination, while the measurement method of ozone is relatively toneless. Fortunately, a new concept of the cataluminescence (CTL) sensor provides a scheme of real-time ozone sensing in a tiny system. Here, a novel CTL sensor system was specially developed with silica-hydroxyl functional boron nitride as the sensing material for rapid and sensitive ozone detection. Coupled with the construction of a pulse vacuum static sampling system, ozone on the surface of sensing material can be desorbed rapidly and can step into the next detection circulation in a few seconds. Based on the strong emission initiated by the transient of reactive oxygen species (ROS) including singlet oxygen, a trioxide group, and an oxygen radical, the detection limit of ozone could be optimized to be as low as 51.2 ppb. Besides, the sensor system exhibited remarkable anti-interference performance in which humidity changes and common VOCs do not disturb or weakly disturb ozone sensing, and the CTL mechanism of the multistep degradation process was further discussed on the basis of multiple pieces of experimental evidence and a DFT transient calculation. A real-time degradation-sensing module was further attached to the system to realize the functions of ozone decomposition and real-time monitoring.

Cataluminescence as a highly efficient gas transduction principle has attracted wide attention among research in environmental monitoring and clinical diagnosis with increasing awareness of human safety. Nowadays, the development of innovation sensing systems and the construction of the sensing mechanism to improve the analytical performance of compounds remain a major challenge. Herein, we construct an advanced photoinduced thermocatalytic chemiluminescence (PI-TC-CL) gas-sensing system via the introduction of a Z-scheme heterojunction Ag 3 PO 4 /Ag/Bi 4 Ti 3 O 12 to achieve higher efficient detection of H 2 S. The unique electron transport path of the Z-scheme heterojunction and the LSPR effect of Ag nanoparticles fascinate the generation of the photoinduced electron-hole pair on the surface of catalysts when stimulated by LED lamps and slow down the recombination of electron-hole pairs under thermal conditions. Thus, based on the cooperative effect of the Z-scheme heterojunction AgPO/Ag/BTO and PI-TC-CL system, we have successfully established an efficient H 2 S CTL detection system, which has a response three times higher than that on the traditional CTL system and even 45 times higher than that on BTO and ranges among the best of the state-of-the-art CTL performance in H 2 S detection with the linear range of 0.095-8.87 μg mL -1 and a limit of detection of 0.0065 μg mL -1 . Besides, to explore the gas-sensing mechanism, the synergetic effects of photoinduction and thermal catalysis are investigated thoroughly via conductivity and electrochemical experiments. This research provides a new perspective of engineering highly efficient catalysts and ingenious sensor systems through designing the nanostructure of materials and synergism catalytic mechanism.

Two-dimensional (2D) materials have been developed into various catalysts with high performance, but employing them for developing highly stable and active nonprecious hydrogen evolution reaction (HER) catalysts still encounters many challenges. To this end, the machine learning (ML) screening of HER catalysts is accelerated by using genetic programming (GP) of symbolic transformers for various typical 2D MA 2 Z 4 materials. The values of the Gibbs free energy of hydrogen adsorption (Δ G H* ) are accurately and rapidly predicted via extreme gradient boosting regression by using only simple GP-processed elemental features, with a low predictive root-mean-square error of 0.14 eV. With the analysis of ML and density functional theory (DFT) methods, it is found that various electronic structural properties of metal atoms and the p-band center of surface atoms play a crucial role in regulating the HER performance. Based on these findings, NbSi 2 N 4 and VSi 2 N 4 are discovered to be active catalysts with thermodynamical and dynamical stability as Δ G H* approaches to zero (-0.041 and 0.024 eV). In addition, DFT calculations reveal that these catalysts also exhibit good deuterium evolution reaction (DER) performance. Overall, a multistep workflow is developed through ML models combined with DFT calculations for efficiently screening the potential HER and DER catalysts from 2D materials with the same crystal prototype, which is believed to have significant contribution to catalyst design and fabrication.

The freshness of meat has always been the focus of attention from consumers and suppliers for health and economic reasons. Usually, amine vapors, as one of the main components of the gas produced in the process of meat spoilage, can be used to monitor meat spoilage. Here, a new ratiometric cataluminescence (CTL) sensor based on energy transfer was developed to identify amine vapors and monitor meat freshness. After Tb doping, amine vapors exhibit a dual-wavelength (490 and 555 nm) property of CTL signals when reacted on the surface of Tb-doped La 2 O 2 CO 3 , and the ratio of I 555 to I 490 ( R 555/490 ) is a unique value for a given analyte within a wide range of concentrations. To illustrate the new sensor, 15 amine vapors were successfully identified using R 555/490 , including homologues and isomers. Besides, this sensor was used to monitor four meats, and the freshness of meats can be distinguished by cluster analysis successfully. Moreover, further discussion of energy-transfer phenomena and influence factors has facilitating effects on exploring the mechanism of energy transfer at the gas-solid interface.