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Despite the potential of deep learning (DL)-based methods in substituting CT-based PET attenuation and scatter correction for CT-free PET imaging, a critical bottleneck is their limited capability in handling large heterogeneity of tracers and scanners of PET imaging. This study employs a simple way to integrate domain knowledge in DL for CT-free PET imaging. In contrast to conventional direct DL methods, we simplify the complex problem by a domain decomposition so that the learning of anatomy-dependent attenuation correction can be achieved robustly in a low-frequency domain while the original anatomy-independent high-frequency texture can be preserved during the processing. Even with the training from one tracer on one scanner, the effectiveness and robustness of our proposed approach are confirmed in tests of various external imaging tracers on different scanners. The robust, generalizable, and transparent DL development may enhance the potential of clinical translation.

● Gasification of cow dung was evaluated using Aspen Plus software.● Optimum reaction conditions were utilized to maximize hydrogen production.● Steam gasification can effectively increase hydrogen production.● Optimum hydrogen production was achieved at 800 °C and steam/biomass of 1.5 and 0.1 MPa. In this study, a biomass gasification model was developed and simulated based on Gibbs free energy minimization by using software Aspen Plus. Two reactors, RYIELD and RGIBBS, were moslty used. The biomass feedstock used was cow dung. The model was validated. The composition, H2/CO ratio and low heating value (LHV) of the resulting synthetic gas (also known as syngas) was estimated by changing the operating parameters of gasification temperatures, steam and biomass ratios and pressures. Simulation results showed that increased gasification temperature helped to elevate H2 and CO content and H2 peaked at 900 °C. When steam increased as the gasification agent, H2 production increased. However, the steam/biomass (S/B) ratio negatively affected CO and CH4, resulting in lower LHV. The optimal S/B ratio was 1.5. An increase in pressure lead to a decrease in H2 and CO content, so the optimal pressure for gasification was 0.1 MPa.

Marine DC power grid typically sustains high current when shorted and its electric characteristics are extremely susceptible to influence by the stray parameters. Given the limitations of cabin space, it is necessary for the bus-tie switch of the DC grid to be miniaturized and in a symmetrical topology while the same level of fault shutdown protection performance is maintained. To this end, this paper presents the rule that how support capacitors and busbar's stray parameters impact short-circuit current, which was analyzed through a combination of simulation and testing at multiple operating points of a typical DC power grid. Specifically, to ensure the safety of devices, breaking time of the solid-state circuit breaker should not exceed 200 μs, and addressing the transient overvoltage suppression in case of bus- tie switch breaking is identified as a key technical issue. Based on the analysis results, it proposes a solid-state circuit breaker with a mirror-symmetrical bus-tie switch topology suitable for marine application scenarios and with the optimized performance based on simulation, to integrate the bus-tie switch and chopper multiplexing as a solution for voltage oscillation upon the bus-tie switch breaking-off. Based on the practical short-circuit tests, it is verified that the designed bus-tie switch is capable of meeting continuous DC power supply conditions on the normal side DC power grid when the busbar and branch are short-circuited. The onboard test results show that the solid-state circuit breaker can achieve a breaking-off capacity in the order of 100 μs, the optimized design of bus-tie switch topology meets the short-circuit protection requirements of marine DC power grid, and the delay for the bus-tie switch to break-off in case of short-circuit fault can mitigate breaking overvoltage fluctuation, thus better guaranteeing system safety.

Due to the strictly restricted free area, vehicles have difficulties to pass through mine narrow corridors. To solve this problem, this paper presents a trajectory planning method based on optimal control. Narrow corridor model and vehicle single-track kinematics model are adopted to construct the trajectory planning model based on optimal control with an approximate space-discretization strategy considering factors like vehicle passage time, vehicle-boundary collision and vehicle actuator range. By vehicle kinematics integral, the control variable sequence solved by the above trajectory planning model leads to an initial optimal trajectory. Taking the discretization impact on trajectory continuity into account, the final target trajectory is formed after smooth the initial optimal trajectory by quadratic programming. Simulation results show that the trajectory generated by the proposed method is effective in narrow corridor scene, and the generated trajectory is continuous and smooth. Compared with the baseline method, the average maximum curvature reduces from 0.094 m-1 to 0.040 m-1 and the average passing time reduces from 6.18 s to 4.80 s in evaluate scenarios.

To achieve large-scale development of triboelectric nanogenerators (TENGs) for water wave energy harvesting and powering the colossal sensors widely distributed in the ocean, facile and scalable TENGs with high output are urgently required. Here, an elastic self-recovering hybrid nanogenerator (ES-HNG) is proposed for water wave energy harvesting and marine environmental monitoring. The elastic skeletal support of the ES-HNG is manufactured using three-dimensional (3D) printing technology, which is more conducive to the large-scale integration of the ES-HNG. Moreover, the combination of a TENG and an electromagnetic generator (EMG) optimizes the utilization of device space, leading to enhanced energy harvesting efficiency. Experimental results demonstrate that the TENG achieves a peak power output of 42.68 mW, and the EMG reaches a peak power output of 4.40 mW. Furthermore, various marine environment monitoring sensors, such as a self-powered wireless meteorological monitoring system, a wireless alarm system, and a water quality monitoring pen, have been successfully powered by the sophisticated ES-HNG. This work introduces an ES-HNG for water wave energy harvesting, which demonstrates potential in marine environment monitoring and offers a new solution for the sustainable development of the marine internet of things. [ABSTRACT FROM AUTHOR]

Escalating global climate change and the intensification of urban heatwaves have led to an increase in summer air conditioning cooling energy consumption. This phenomenon is particularly critical in tropical regions, as it may trigger an energy crisis. The rational setting of indoor thermal design parameters can help conserve energy to the maximum extent while ensuring thermal comfort for occupants. This study selected Haikou City, a unique tropical city in China, as the research location. Indoor environment measurements and a questionnaire survey were conducted with participants, and the outdoor thermal environment sensitivity, population attributes and differences in thermal sensation, thermal neutral temperature, and comfort range were calculated and analyzed. The following results were obtained. Based on the overall population, long-term residence, and temporary residence classification, the indoor thermal comfort needs of residents in tropical cities in Haikou were effectively identified. The actual thermal neutral temperature of the overall population is 25.7 °C, and 90% of the acceptable thermal comfort temperature range is 23.2 °C–28.0 °C. The actual thermal neutral temperature of the regular residents is 27.3 °C, and 90% of the acceptable thermal comfort temperature range is 23.3 °C–31.4 °C. The actual thermal neutral temperature of the temporary population is 25.5 °C, and 90% of the acceptable thermal comfort temperature range is 23.0 °C–28.0 °C. These research results have an important reference value for improving the setting of the temperature of air conditioning in tropical areas in summer and further reducing energy consumption, which is conducive to sustainable development. [ABSTRACT FROM AUTHOR]

As natural medicines in complementary and alternative medicine, edible and medicinal resources are being gradually recognized throughout the world. According to statistics from the World Health Organization, about 80% of the worldwide population has used edible and medicinal resource products to prevent and treat diseases. Polysaccharides, one of the main effective components in edible and medicinal resources, are considered ideal regulators of various biological responses due to their high effectiveness and low toxicity, and they have a wide range of possible applications for the development of functional foods for the regulation of common, frequently occurring, chronic and severe diseases. Such applications include the development of polysaccharide products for the prevention and treatment of neurodegenerative diseases that are difficult to control by a single treatment, which is of great value to the aging population. Therefore, we evaluated the potential of polysaccharides to prevent neurodegeneration by their regulation of behavioral and major pathologies, including abnormal protein aggregation and neuronal damage caused by neuronal apoptosis, autophagy, oxidative damage, neuroinflammation, unbalanced neurotransmitters, and poor synaptic plasticity. This includes multi-target and multi-pathway regulation involving the mitochondrial pathway, MAPK pathway, NF-κB pathway, Nrf2 pathway, mTOR pathway, PI3K/AKT pathway, P53/P21 pathway, and BDNF/TrkB/CREB pathway. In this paper, research into edible and medicinal resource polysaccharides for neurodegenerative diseases was reviewed in order to provide a basis for the development and application of polysaccharide health products and promote the recognition of functional products of edible and medicinal resources. [ABSTRACT FROM AUTHOR]

Accurate tracking of all components (including core, anvil, and cirrus) of deep convective systems (DCSs) throughout their lifecycle is key to quantifying their impacts on radiative forcing, especially of the anvil and cirrus. Here, a new Full‐tracking Algorithm for Convective Thunderstorm System is developed based on geostationary satellite. It successfully tracks DCSs starting from the initial core to complete dissipation of cirrus detrained from them, and integrates all the related components that split from the initial convective core into a whole DCS. Results show that more than half of the tracked DCSs experience splitting evolutions, with an average of eight sub‐cores during their lifetime. With tracking cirrus generated by DCSs, the lifetime of DCSs is lengthened by up to 10 hr, and their area is enlarged by 16% on average. Generally, long‐lived DCSs have lower cloud top temperature, greater rainfall, and larger area, with more frequent splitting evolutions than short‐lived DCSs. Additionally, DCSs always reach their peaks within 6 hr after initiation regardless of their lifetime. This paper provides a basis for further quantifying the evolution of DCS properties, their impacts on the global radiation budget, and the water cycle in the climate system. Key Points: A novel method is developed to track full components of deep convective systems (DCSs) from their initiation to total cirrus dissipationLifetime of DCSs is extended by up to 10 hr, and their area is enlarged by 16% averagely after continuously tracking their detrained cirrusIntegrated total rainfall amounts are comparably contributed between frequent but small and rare but large DCSs [ABSTRACT FROM AUTHOR]

This study evaluates ice particle size distribution and aspect ratio φ Multi-Radar Multi-Sensor (MRMS) dual-polarization radar retrievals through a direct comparison with two legs of observational aircraft data obtained during a winter storm case from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. In situ cloud probes, satellite, and MRMS observations illustrate that the often-observed Kdp and ZDR enhancement regions in the dendritic growth layer can either indicate a local number concentration increase of dry ice particles or the presence of ice particles mixed with a significant number of supercooled liquid droplets. Relative to in situ measurements, MRMS retrievals on average underestimated mean volume diameters by 50% and overestimated number concentrations by over 100%. IWC retrievals using ZDR and Kdp within the dendritic growth layer were minimally biased relative to in situ calculations where retrievals yielded −2% median relative error for the entire aircraft leg. Incorporating φ retrievals decreased both the magnitude and spread of polarimetric retrievals below the dendritic growth layer. While φ radar retrievals suggest that observed dendritic growth layer particles were nonspherical (0.1 ≤ φ ≤ 0.2), in situ projected aspect ratios, idealized numerical simulations, and habit classifications from cloud probe images suggest that the population mean φ was generally much higher. Coordinated aircraft radar reflectivity with in situ observations suggests that the MRMS systematically underestimated reflectivity and could not resolve local peaks in mean volume diameter sizes. These results highlight the need to consider particle assumptions and radar limitations when performing retrievals. significance statement: Developing snow is often detectable using weather radars. Meteorologists combine these radar measurements with mathematical equations to study how snow forms in order to determine how much snow will fall. This study evaluates current methods for estimating the total number and mass, sizes, and shapes of snowflakes from radar using images of individual snowflakes taken during two aircraft legs. Radar estimates of snowflake properties were most consistent with aircraft data inside regions with prominent radar signatures. However, radar estimates of snowflake shapes were not consistent with observed shapes estimated from the snowflake images. Although additional research is needed, these results bolster understanding of snow-growth physics and uncertainties between radar measurements and snow production that can improve future snowfall forecasting. [ABSTRACT FROM AUTHOR]

Severe regional haze events, which are characterized by exceedingly high levels of fine particulate matter (PM), occur frequently in many developing countries (such as China and India), with profound implications for human health, weather, and climate. The occurrence of the haze extremes involves a complex interplay between primary emissions, secondary formation, and conducive meteorological conditions, and the relative contributions of the various processes remain unclear. Here we investigated severe regional haze episodes in 2013 over the Northern China Plain (NCP), by evaluating the PM production and the interactions between elevated PM and the planetary boundary layer (PBL). Analysis of the ground-based measurements and satellite observations of PM properties shows nearly synchronized temporal PM variations among the three megacities (Beijing, Baoding, and Shijiazhuang) in this region and a coincidence of the aerosol optical depth (AOD) hotspots with the three megacities during the polluted period. During the clean-to-hazy transition, the measured oxygenated organic aerosol concentration ([OOA]) well correlates with the odd-oxygen concentration ([Ox]=[O3]+[NO2]), and the mean [OOA] / [ Ox ] ratio in Beijing is much larger than those in other megacities (such as Mexico City and Houston), indicating highly efficient photochemical activity. Simulations using the Weather Research and Forecasting (WRF) model coupled with an explicit aerosol radiative module reveal that strong aerosol–PBL interaction during the polluted period results in a suppressed and stabilized PBL and elevated humidity, triggering a positive feedback to amplify the haze severity at the ground level. Model sensitivity study illustrates the importance of black carbon (BC) in the haze–PBL interaction and the aerosol regional climatic effect, contributing to more than 30 % of the PBL collapse and about half of the positive radiative forcing on the top of the atmosphere. Overall, severe regional haze exhibits strong negative radiative forcing (cooling) of - 63 to - 88 Wm-2 at the surface and strong positive radiative forcing (warming) of 57 to 82 Wm-2 in the atmosphere, with a slightly negative net radiative forcing of about - 6 Wm-2 on the top of the atmosphere. Our work establishes a synthetic view for the dominant regional features during severe haze events, unraveling rapid in situ PM production and inefficient transport, both of which are amplified by atmospheric stagnation. On the other hand, regional transport sufficiently disperses gaseous aerosol precursors (e.g., sulfur dioxide, nitrogen oxides, volatile organic compounds, and ammonia) during the clean period, which subsequently result in rapid in situ PM production via photochemistry during the transition period and via multiphase chemistry during the polluted period. Our findings highlight the co-benefits for reduction in BC emissions, which not only improve local and regional air quality by minimizing air stagnation but also mitigate the global warming by alleviating the positive direct radiative forcing. [ABSTRACT FROM AUTHOR]

Most existing cloud models tend to overestimate the size of cloud ice particles and underestimate their concentration. This emphasizes the need to provide a reliable observational reference to optimize cloud model performance, particularly in areas of high concentration of ice at high altitudes. The dual‐polarization radars give the community a unique opportunity to quantify cloud ice with a good accuracy using polarimetric radar retrievals. In this study, we utilize the network of operational WSR‐88D radars to build a climatology of the vertical profiles of radar variables, such as radar reflectivity Z, differential reflectivity ZDR, and specific differential phase KDP as well as the radar‐retrieved vertical profiles of ice water content (IWC) above the melting layer and liquid water content below it, mean volume diameter Dm, and total number concentration Nt of ice and liquid particles. Such climatology was created for continental/marine mesoscale convective systems (MCSs) and tropical cyclones including hurricanes. The dataset includes 13 continental MCSs, 10 marine MCSs, and 11 tropical cyclones. Separate statistics of the "background" vertical profiles and the ones associated with high IWC aloft have been obtained in the course of this study. It is shown that continental MCSs exhibit larger size of ice in lower concentration aloft compared to the marine MCSs and especially tropical cyclones/hurricanes. A combination of high KDP and low Z aloft signifies lower Dm, higher Nt, and often substantial IWC. Key Points: Climatology of the vertical profiles of polarimetric radar variables and microphysical parameters is documented for different storm typesAreas of high ice water content (IWC) in clouds are characterized by high values of specific differential phase combined with low reflectivityTropical clouds have smaller size ice in higher concentration compared to their continental counterparts with comparable IWC [ABSTRACT FROM AUTHOR]

Severe regional haze events, which are characterized by exceedingly high levels of fine particulate matter (PM), occur frequently in many developing countries (such as China and India), with profound implications for human health, weather, and climate. The occurrence of the haze extremes involves a complex interplay between primary emissions, secondary formation, and conducive meteorological conditions, and the relative contributions of the various processes remains unclear. Here we investigated severe regional haze episodes in 2013 over the Northern China Plain (NCP), by evaluating the PM production and the interactions between elevated PM and the planetary boundary layer (PBL). Analysis of the ground-based measurements and satellite observations of PM properties shows nearly synchronized temporal PM variations among the three megacities (Beijing, Baoding, and Shijiazhuang) in this region and a coincidence of the aerosol optical depth (AOD) hotspots with the three megacities during the polluted period. During the clean-to-hazy transition, the measured oxygenated organic aerosol concentration ([OOA]) well correlates with the odd-oxygen concentration ([Ox] = [O3] + [NO2]), and the mean [OOA]/[Ox] ratio in Beijing is much larger than those in other megacities (such as Mexico City and Houston), indicating highly efficient photochemical activity. Simulations using the Weather Research and Forecasting (WRF) model coupled with an explicit aerosol radiative module reveal that strong aerosol-PBL interaction during the polluted period results in a suppressed and stabilized PBL and elevated humidity, triggering a positive feedback to amplify the haze severity at the ground level. Model sensitivity study illustrates the importance of black carbon (BC) in the haze-PBL interaction and the aerosol regional climatic effect, contributing to more than 30% of the PBL collapse and about half of the positive radiative forcing on the top of the atmosphere. Overall, severe regional haze exhibits strong negative radiative forcing (cooling) of -63 to -88 W m-2 at the surface and strong positive radiative forcing (warming) of 57 to 82 W m-2 in the atmosphere, with a slightly negative net radiative forcing of about -6 W m-2 on the top of the atmosphere. Our work establishes a synthetic view for the dominant regional features during severe haze events, unraveling rapid in-situ PM production and inefficient transport, both of which are amplified by atmospheric stagnation. On the other hand, regional transport sufficiently disperses gaseous aerosol precursors (e.g., sulfur dioxide, nitrogen oxides, volatile organic compounds, and ammonia) during the clean period, which subsequently result in rapid in-situ PM production via photochemistry during the transition period and via multiphase chemistry during the polluted period. Our findings highlight the co-benefits for reduction in BC emissions, which not only improve local and regional air quality by minimizing air stagnation but also mitigate the global warming by alleviating the positive direct radiative forcing. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the significance of collagen in predicting the aggressiveness of rectal tumors in patients, examined in vivo based on tomoelastography quantified stiffness and ex vivo by histologically measured collagen volume fraction (CVF). Experimental Design: 170 patients with suspected rectal cancer were prospectively enrolled and underwent preoperative magnetic resonance imaging (MRI) and rectal tomoelastography, a technique based on multifrequency magnetic resonance elastography. Histopathologic analysis identified eighty patients with rectal cancer who were divided into subgroups by tumor-node (TN) stage, prognostic stage, and risk level. Rectal tumor stiffness was correlated with histopathologic CVF. Area-under-the-curve (AUC) and contingency analysis were used to evaluate the performance of rectal stiffness in distinguishing tumor stages which was compared to standard clinical MRI Results: In vivo tomoelastography revealed that rectal tumor stiffened significantly with increased TN stage (p<0.05). Tumors with poorly differentiated status, perineural and lymphovascular invasion also displayed higher stiffness than well-to-moderately differentiated, noninvasive tumors (all p<0.05). Similar to in vivo stiffness, CVF indicated an abnormally high collagen content in tumors with perineural invasion and poor differentiation status. CVF was also positively correlated with stiffness (p<0.05). Most importantly, both stiffness (AUROC: 0.82) and CVF (AUROC: 0.89) demonstrated very good diagnostic accuracy in detecting rectal tumors that have high risk for progressing to an aggressive state with poorer prognosis. Conclusion: In human rectal carcinomas, overexpression of collagen is correlated with increased tissue stiffness and high risk for tumor advancing more aggressively. In vivo tomoelastography quantifies rectal tumor stiffness which improves the diagnostic performance of standard MRI in the assessment of lymph nodes metastasis. Therefore, in vivo stiffness mapping by tomoelastography can predict rectal tumor aggressiveness and add diagnostic value to MRI. [ABSTRACT FROM AUTHOR]

During development, melanopsin-expressing intrinsically photosensitive retinal ganglion cells (ipRGCs) become light sensitive much earlier than rods and cones. IpRGCs project to many subcortical areas, whereas physiological functions of these projections are yet to be fully elucidated. Here, we found that ipRGC-mediated light sensation promotes synaptogenesis of pyramidal neurons in various cortices and the hippocampus. This phenomenon depends on activation of ipRGCs and is mediated by the release of oxytocin from the supraoptic nucleus (SON) and the paraventricular nucleus (PVN) into cerebral-spinal fluid. We further characterized a direct connection between ipRGCs and oxytocin neurons in the SON and mutual projections between oxytocin neurons in the SON and PVN. Moreover, we showed that the lack of ipRGC-mediated, light-promoted early cortical synaptogenesis compromised learning ability in adult mice. Our results highlight the importance of light sensation early in life on the development of learning ability and therefore call attention to suitable light environment for infant care. [Display omitted] • Light sensation through ipRGCs early in life promotes cortical synaptogenesis • Light enhances CSF oxytocin level via an ipRGCs-SON-PVN oxytocin neuron circuit • Oxytocin is essential for light-promoted ipRGC-mediated synaptogenesis • Lack of light sensation in early development impairs learning ability in adult mice Light sensation by intrinsically photosensitive retinal ganglion cells early in life ensures proper learning ability in adult mice by activating oxytocin-releasing neurons, which in turn promotes cortical synaptogenesis. [ABSTRACT FROM AUTHOR]

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.

Hybrid nanogenerators (HNGs) represent a promising avenue for water energy harvesting, yet their commercial viability faces hurdles such as limited power output, poor coupling, and constrained operational lifespans. Here, a highly coupled triboelectric-electromagnetic magnetic-levitation hybrid nanogenerator (ML-HNG) is introduced that shows great potential for water energy harvesting. The ML-HNG fulfills the challenges of high power output, strong coupling, and long operational lifespans. During the contact-separation process of the triboelectric nanogenerator (TENG), the changing magnetic flux in the electromagnetic generator's coils generates a potential difference between the coils and Cu electrodes. The unique design of the ML-HNG employs a shared coil electrode configuration, which enhances the coupling without adding extra volume. This integration allows the ML-HNG to achieve multi-frequency vibrations and multiple output cycles per external longitudinal movement, a phenomenon known as the frequency multiplication effect. With an average power density of 1.69 W m -3 in water, the ML-HNG provides continuous power for a thermo-hygrometer and can quickly drive a wireless water level alarm system within a minute. This groundbreaking hybrid nanogenerator design holds significant promise for the efficient and consistent harvesting of low-frequency ocean wave energy, marking a substantial advancement in blue energy technology., (© 2024 Wiley‐VCH GmbH.)

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.