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This paper introduces a pioneering approach that combines ex situ synthesis with advanced manufacturing to develop ZIF-67-PA12 Nylon composites with mixed-matrix membranes (MMMs), with the goal of enhancing hydrogen storage systems. One method involves producing MOF-PA12 composite powders through an in situ process, which is then commonly used as a base powder for powder bed fusion (PBF) to fabricate various structures. However, developing the in situ MOF-PA12 matrix presents challenges, including limited spreadability and processability at higher MOF contents, as well as reduced porosity due to pore blockage by polymers, ultimately diminishing hydrogen storage capacity. To overcome these issues, PBF is employed to form PA12 powder into films, followed by the ex situ direct synthesis of ZIF-67 onto these substrates at loadings exceeding those typically used in conventional MMM composites. In this study, ZIF-67 mass loadings ranging from 2 to 30 wt.% were synthesized on both PA12 powder and printed film substrates, with loadings on printed PA12 films extended up to 60 wt.%. ZIF-67-PA12-60(f) demonstrated a hydrogen capacity of 0.56 wt.% and achieved 1.53 wt.% for ZIF-67-PA12-30(p); in comparison, PA12 exhibited a capacity of 0.38 wt.%. This was undertaken to explore a range of ZIF-67 Metal–organic frameworks (MOFs) to assess their impact on the properties of the composite, particularly for hydrogen storage applications. Our results demonstrate that ex situ-synthesized ZIF-67-PA12 composite MMMs, which can be used as a final product for direct application and do not require the use of in situ pre-synthesized powder for the PBF process, not only retain significant hydrogen storage capacities, but also offer advantages in terms of repeatability, cost-efficiency, and ease of production. These findings highlight the potential of this innovative composite material as a practical and efficient solution for hydrogen storage, paving the way for advancements in energy storage technologies.

Accurate and prompt determination of fire types is essential for effective firefighting and reducing damage. However, traditional methods such as smoke detection, visual analysis, and wireless signals are not able to identify fire types. This paper introduces FireSonic, an acoustic sensing system that leverages commercial speakers and microphones to actively probe the fire using acoustic signals, effectively identifying fire types. By incorporating beamforming technology, FireSonic first enhances signal clarity and reliability, thus mitigating signal attenuation and distortion. To establish a reliable correlation between fire type and sound propagation, FireSonic quantifies the heat release rate (HRR) of flames by analyzing the relationship between fire-heated areas and sound wave propagation delays. Furthermore, the system extracts spatiotemporal features related to fire from channel measurements. The experimental results demonstrate that FireSonic attains an average fire type classification accuracy of 95.5% and a detection latency of less than 400 ms, satisfying the requirements for real-time monitoring. This system significantly enhances the formulation of targeted firefighting strategies, boosting fire response effectiveness and public safety.

Spatial–temporal variation in soil organic carbon is an important factor for national targets to mitigate climate change and land degradation impacts. In this research, we took Guangdong Province of China as the study area, evaluated the spatial–temporal distributions of soil organic carbon using data from three China Geochemical Baseline projects (conducted in 2009, 2016, and 2023, respectively), and quantified the main driving factors of spatial–temporal variations in soil organic carbon using the random forest algorithm, further predicting the density and inventories of soil organic carbon. The results demonstrate that the mean value of SOC in Guangdong in 2009 was 0.81%; in 2016 it was 1.13%; and in 2023 it was 1.02%. The inventories of soil organic carbon (0–30 cm) in Guangdong Province were 0.61 Pg in 2009, 0.74 Pg in 2016, and 0.62 Pg in 2023. Soil in Guangdong acted as a carbon sink from 2009 to 2023 as a whole, and the most important driving force behind spatial–temporal variations in soil organic carbon was temperature, followed by precipitation and vegetation cover.

Regenerated rice, characterized by single planting and double harvesting, saves labor and costs, significantly contributing to global food security. Hyperspectral imaging technology, which integrates image and spectral data, provides comprehensive, non-destructive, and pollution-free vegetation canopy analysis, making it highly effective for crop nutrient diagnosis. In this study, we selected two varieties of regenerated rice for field trials. Hyperspectral images were captured during key growth stages (flush, grouting, and ripening) of both the first and regenerated seasons. Utilizing a two-dimensional convolutional neural network (2D-CNN) as a deep feature extractor and a fully connected layer for nitrogen content prediction, we developed a robust model suitable for estimating nitrogen content in regenerated rice. The experimental results demonstrate that our method achieves a mean squared error (MSE) of 0.0008, significantly outperforming the back-propagation (BP) network and multiple linear regression by reducing the MSE by 0.0151 and 0.0247, respectively. It also surpasses the one-dimensional convolutional neural network (1D-CNN) by 0.003. This approach ensures accurate nitrogen content prediction throughout the growth cycle of regenerated rice, aiding in yield and economic benefit enhancement.

Bedload sediment transport is critical in the natural river environmental and ecological system. It is quite challenging to measure the bedload sediment transport rate in rivers with any degree of accuracy. In this study, the authors developed the Gravel Pressure and Voice Synchronous observation system (GPVS) to estimate the bedload sediment transport rate in rivers. The core of the GPVS includes an underwater high-fidelity audio recorder and pressure sensor. The audio recorder is intended to monitor the low bedload sediment transport rate, whereas the pressure sensor is utilized to detect relatively substantial bedload sediment transport. The GPVS is tested by running flume experiments with natural gravel to evaluate the system’s reliability and feasibility. Results reveal that the GPVS has a very high sensitivity for detecting bedload transport. When the bedload sediment transport rate is relatively low, the audio recorder can measure it quantitatively, showing that the system is not impacted by ambient noise.

Supercapacitors are regarded as reliable energy storage devices to alleviate the energy crisis and environmental pollution. However, the relatively low capacitance and low energy density limit the practical application of supercapacitors. In this context, boron carbon nitride (BCN) nanomaterials have been extensively studied in the past decade due to their chemical and thermal stability, high mechanical strength, as well as tunable bandgap. The specific capacitance and energy density of supercapacitors can be significantly improved by fabricating nanostructured BCN-based electrode materials. In this review, the recent advances in the application of BCN-based materials in supercapacitors is presented. Strategies such as structure design, porosity/defect engineering, and hybrid nanostructure construction to boost the electrochemical performance of BCN-based materials are provided and, finally, promising research directions for novel energy storage materials are proposed.

Real-time sweat monitoring is vital for athletes in order to reflect their physical conditions, quantify their exercise loads, and evaluate their training results. Therefore, a multi-modal sweat sensing system with a patch-relay-host topology was developed, which consisted of a wireless sensor patch, a wireless data relay, and a host controller. The wireless sensor patch can monitor the lactate, glucose, K+, and Na+ concentrations in real-time. The data is forwarded via a wireless data relay through Near Field Communication (NFC) and Bluetooth Low Energy (BLE) technology and it is finally available on the host controller. Meanwhile, existing enzyme sensors in sweat-based wearable sports monitoring systems have limited sensitivities. To improve their sensitivities, this paper proposes a dual enzyme sensing optimization strategy and demonstrates Laser-Induced Graphene (LIG)-based sweat sensors decorated with Single-Walled Carbon Nanotubes (SWCNT). Manufacturing an entire LIG array takes less than one minute and costs about 0.11 yuan in materials, making it suitable for mass production. The in vitro test result showed sensitivities of 0.53 μA/mM and 3.9 μA/mM for lactate and glucose sensing, and 32.5 mV/decade and 33.2 mV/decade for K+ and Na+ sensing, respectively. To demonstrate the ability to characterize personal physical fitness, an ex vivo sweat analysis test was also performed. Overall, the high-sensitivity lactate enzyme sensor based on SWCNT/LIG can meet the requirements of sweat-based wearable sports monitoring systems.

As we move away from internal combustion engines to tackle climate change, the importance of hydrogen-powered vehicles and polymer electrolyte membrane fuel cell (PEMFC) technology has dramatically increased. In the present study, we aimed to determine the optimal configuration for the power output of a PEMFC system using computational fluid dynamics (CFD) modelling to analyse variations of the primary serpentine design of gas flow channels. This helps improve efficiency and save on valuable materials used, reducing potential carbon emissions from the production of hydrogen vehicles. Different numbers of serpentine gas channels were represented with various spacing between them, within the defined CFD model, to optimise the gas channel geometry. The results show that the optimum configuration was found to have 11 serpentine channels with a spacing of 3.25 mm. In this optimum configuration, the ratio between the channel width, channel spacing, and serpentine channel length was found to be 1:2.6:38 for PEMFCs. Furthermore, the inclusion of fillets to the bends of the serpentine gas channels was found to have a negative effect on the overall power output of the fuel cell. Moreover, the optimisation procedures with respect to the number of gas channels and the spacing revealed an optimal power density exceeding 0.65 W/cm2.

Mild Cognitive Impairment (MCI) in pensioners has become an important concern in the aging population, and there are an increasing number of products, especially virtual reality (VR)-based products, to assist in the identification, intervention, and treatment of MCI older adults. Multiple studies on the efficacy and usability of VR products are also receiving increased attention from designers. However, issues such as the efficacy testing of VR products still face serious challenges. In this study, we evaluated VR products looking at the interactive responsiveness of MCI older adults when using VR products, and analyzed the brain activation status and behavioral conditions of MCI older adults. Multisource data were generated by a functional near-infrared spectroscopy (fNIRS) device with high spatial resolution and a behavioral recording device reflecting motor abilities. Small-wave amplitudes were selected as indicators of brain activation to analyze six brain areas: LPFC, RPFC, LOL, ROL, LMC, and RMC. Eight aspects, such as overall upper-limb speed, upper-limb global acceleration, and median velocity, were selected as indicators for behavioral recording. The differences were observed by comparing the level of completion of interactive responses by MCI older adults between the two groups. The results showed that MCI older adults showed different levels of activation in brain regions when performing VR product-based tasks. The higher the level of cognition, the better the interactive response in the task and the stronger the activation of brain regions. Meanwhile, the level of interaction response had a significant correlation with the motor performance of MCI older adults, with stronger motor functions leading to a more effective interaction response to the product. This study proposes a new method to evaluate the feasibility of monitoring the interaction between the MCI elderly and VR-based products using fNIRS with Kinect, which provides a new way to evaluate the effectiveness of VR-based product-assisted treatment.

The environmental quality of the sediments in karst areas is a common concern, and it is of great significance to analyze the sources of the sediments. This study investigates the sources and its temporal variations of catchment sediments in a typical small karst watershed area. Toxic metal concentrations in the catchment area were monitored via three geochemical baseline projects in China. The sediment identification fingerprint tool (SIFT) was used to establish a geochemical model for tracing the main source contributions and its temporal variations of catchment sediments over the past 28 years (1992–2019). The catchment sediments in the small karst catchment area were mainly sourced from the background lithologies, among which limestone contributed the most, followed by dolomite, sand-shale, and mudstone; however, the anthropogenic lead–zinc tailings contributed the least. The contributions and temporal variations of each source were closely related to the lithology, topography, and landform, as well as the change in land-use and vegetation cover and the degree of rocky desertification. Moreover, the implementation of vegetation restoration and control of rocky desertification decreased the contributions of the upstream geological bodies, and the toxic metal content of the catchment sediment decreased accordingly. This study is of great significance for environmental governance in karst areas.

Given the continuous improvement in the capabilities of road vehicles to detect obstacles, the road friction coefficient is closely related to vehicular braking control, thus the detection of road surface conditions (RSC), and the level is crucial for driving safety. Non-contact technology for RSC sensing is becoming the main technological and research hotspot for RSC detection because of its fast, non-destructive, efficient, and portable characteristics and attributes. This study started with mapping the relationship between friction coefficients and RSC based on the requirement for autonomous driving. We then compared and analysed the main methods and research application status of non-contact detection schemes. In particular, the use of infrared spectroscopy is expected to be the most approachable technology path to practicality in the field of autonomous driving RSC detection owing to its high accuracy and environmental adaptability properties. We systematically analysed the technical challenges in the practical application of infrared spectroscopy road surface detection, studied the causes, and discussed feasible solutions. Finally, the application prospects and development trends of RSC detection in the fields of automatic driving and exploration robotics are presented and discussed.

In pipelines for transporting oil and gas, multiple cracks often exist in weld joints. The interaction among the cracks should be considered as it directly affects the life span of the pipeline structures. In the current investigation, based on the fluid–solid magnetic coupling model, the virtual crack-closure technique (VCCT) is applied to systematically study the multi-crack dynamic interaction effect on pipeline welds during the crack propagation process. The results show that the existence of an auxiliary crack accelerates the main crack’s propagation. When the auxiliary crack is nearer to the main crack tip, the enhancement effect of the auxiliary crack on the main crack increases. Further, when the initial length of the auxiliary crack increases, the main crack becomes easier to propagate. Two important parameters, the distance between the two interacting crack tips and the initial size of the auxiliary crack, are studied in detail. Their interference effect on the main crack has been quantified, which is very user-friendly for engineers to conduct failure assessment and prevention for oil and gas pipes with multiple cracks at weld joints.

The health risks of PM2.5-bound heavy metals have attracted extensive attention recently. In order to evaluate those deleterious effects on human health more accurately, and to propose proper measures to reduce health risks of air pollution, the conduction of a source-specific health risk assessment is necessary. Based on daily collected PM2.5 samples at different functional sites during winter 2019 in a megacity Chongqing, China, combining source apportionment results from PMF and health risk assessment from the U.S. EPA, the source-specific health risks from PM2.5-bound heavy metals were given. Six types of PM2.5 sources have been identified, coal burning (25.5%), motor vehicles (22.8%), industrial emissions (20.5%), biomass burning (15.9%), dust (7.8%), and ship emissions (7.5%). Results showed that the total hazard quotient (HQ) was 0.32 and the total carcinogenic risks (CR) were 2.09 × 10−6 for children and 8.36 × 10−6 for adults, implying certain risks for local residents. Industrial emissions related with Cr posed both the highest carcinogenic risk and noncarcinogenic risk (contributing 25% CR and 36% HQ). Coal combustion (associated with Cr, As, and Mn) contributed 15.46% CR and 20.64% HQ, while biomass burning and motor vehicles shared 19.99% and 19.05% of the total CR, respectively. This work indicated that health risks of air pollution sources were the combined effects of the source contribution and chemical components. In order to control the health risks of PM2.5 to the local residents, the priority of targeted emission sources should be adopted for industrial emissions, biomass burning, vehicle emissions, and coal combustion sources.

In the manufacturing process of lithium-ion batteries, the current organic solvent-based processes will inevitably be replaced with eco-friendly water-based processes. For this purpose, the current organic-soluble binder should be replaced with a water-soluble or water-dispersed binder. In this study, a new polyacrylate latex dispersed in water was successfully applied as a binder of lithium-ion battery cathodes for the first time. One of the biggest advantages of the polyacrylate binder is that it is electrochemically stable at the working voltage of typical cathodes, unlike a conventional water-dispersed styrene-butadiene binder. This implies that the water-dispersed polyacrylate has no limitations for the usage of a cathodic binder. The performance of the polyacrylate binder for lithium iron phosphate cathodes was compared with those of a conventional organic-based polyvinylidene fluoride binder as well as a water-dispersed styrene-butadiene binder. The polyacrylate binder exhibited an electrochemical performance that was comparable to that of an existing styrene-butadiene binder and much better than that of the polyvinylidene fluoride binder. This superior performance of the polyacrylate binder is attributed to the point-to-point bonding mechanism of an emulsified binder, which leads to a strong adhesion strength as well as the low electrical and charge transfer resistances of the cathodes.

Serangium japonicum Chapin (Coleoptera: Coccinellidae) is a predominant predator with a preference for Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae). To date, the orientational behavior of S. japonicum toward B. tabaci-infested plants has seldom been reported. In this study, greenhouse cage experiments and bioassays with wind tunnels, a Y-tube olfactometer and B. tabaci-induced plant volatiles were executed to clarify this behavior. In greenhouse cage experiments, B. tabaci adults significantly preferred eggplant, cucumber and tobacco to cotton and tomato, whereas S. japonicum adults preferred B. tabaci-infested eggplant, cucumber and cotton to tobacco and tomato. In wind tunnel bioassays, B. tabaci showed a clear preference for eggplant, cucumber and tobacco. Compared with B. tabaci-infested eggplant, cucumber or cotton, B. tabaci-infested tobacco was rarely visited by S. japonicum. In Y-tube bioassays, S. japonicum did not distinguish between B. tabaci-infested and uninfested eggplant. Nine common plant volatiles were detected in different plant species, suggesting that these volatiles may play an important role in the process by which S. japonicum looks for prey. In light of the current results, we discuss the implications of our findings and put forward to a new strategy—i.e., an eggplant + B. tabaci + S. japonicum system—to control B. tabaci damage in the integrated management of whitefly.

In the inductive power transfer (IPT) system, it is recommended to drive the resonant inverter in zero-voltage switching (ZVS) or zero-current switching (ZCS) operation to reduce switching losses, especially in dynamic applications with variable couplings. This paper proposes an improved autonomous current-fed push-pull parallel-resonant inverter, which not only realizes the ZVS operation by tracking the zero phase angle (ZPA) frequency, but also improves the output power and overall efficiency in a wide range by reducing gate losses and switching losses. The ZPA frequencies characteristic of the parallel-parallel resonant circuit in both bifurcation and bifurcation-free regions is derived and verified by theory and experiments, and the comparative experimental results demonstrate that the improved inverter can significantly increase the output power from 7.68 W to 8.74 W and has an overall efficiency ranging from 63.5% to 72.5% compared with the traditional inverter at a 2 cm coil distance. Furthermore, with a 2-fold input voltage (24 V), the improved inverter can achieve an approximate 4-fold output power of 38.9 W and overall efficiency of 83.6% at a 2 cm coil distance.