Highly sensitive triethylamine (TEA) gas sensors have undergone extensive research, yet slow response/recovery speed, poor moisture resistance, and high detection limitation limited their further ...application. Herein, pure SnO2 and Co-doped SnO2 nanofibers have been synthesized by a simple electrostatic spinning technique, and their sensing performance has been systematically analyzed. As a result, the sensors based on the 2 mol% Co-doped SnO2 nanofibers show a good response (Ra/Rg = 50.2) to 100 ppm TEA at 200 °C. In addition, the 2 mol% Co-doped SnO2 based sensors display a rapid response and recovery speed, low limit of detection, superior anti-humidity property, and excellent reproducibility for TEA. The improved sensing performance owing to enhanced chemisorbed oxygen as a consequence of the Fermi level regulation and the abundant oxygen vacancies. All in all, 2 mol% Co-doped SnO2 nanofibers have the potential for efficient detection of low concentrations of TEA.
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•Porous 2 mol% Co-SnO2 nanofibers were synthesized by an electrospinning method.•The regulation of the energy level of SnO2 for the efficient detection of TEA.•Co doping significantly increased the oxygen vacancies of SnO2 nanofibers.•The doping of Co could enhance the sensing performance of SnO2 for TEA.
Spider silk is one of the most robust natural materials, which has extremely high strength in combination with great toughness and good elasticity. Inspired by spider silk but beyond it, a healable ...and recyclable supramolecular elastomer, possessing superhigh true stress at break (1.21 GPa) and ultrahigh toughness (390.2 MJ m−3), which are, respectively, comparable to and ≈2.4 times higher than those of typical spider silk, is developed. The elastomer has the highest tensile strength (ultimate engineering stress, 75.6 MPa) ever recorded for polymeric elastomers, rendering it the strongest and toughest healable elastomer thus far. The hyper‐robust elastomer exhibits superb crack tolerance with unprecedentedly high fracture energy (215.2 kJ m−2) that even exceeds that of metals and alloys, and superhigh elastic restorability allowing dimensional recovery from elongation over 12 times. These extraordinary mechanical performances mainly originate from the meticulously engineered hydrogen‐bonding segments, consisting of multiple acylsemicarbazide and urethane moieties linked with flexible alicyclic hexatomic spacers. Such hydrogen‐bonding segments, incorporated between extensible polymer chains, aggregate to form geometrically confined hydrogen‐bond arrays resembling those in spider silk. The hydrogen‐bond arrays act as firm but reversible crosslinks and sacrificial bonds for enormous energy dissipation, conferring exceptional mechanical robustness, healability, and recyclability on the elastomer.
Healable and recyclable elastomers with superhigh strength (tensile strength ≈ 75.6 MPa, true stress at break ≈ 1.21 GPa) and ultrahigh toughness (≈390.2 MJ m−3) are reported. The elastomer has unprecedented crack tolerance with fracture energy of 215.2 kJ m−2 that even exceeds that of metals and alloys. The elastomer exhibits superhigh elastic restorability allowing dimensional recovery from elongation over 12 times.
Nowadays, soft actuators have received extensive attention in many application fields, among which hydrogels have become an important choice for constructing soft actuators due to their unique ...properties. However, the actuating behaviors of hydrogel‐based actuators are usually monotonous due to their unchangeable shapes and structures. Herein, we report a temperature‐responsive hydrogel actuator with a bilayer structure. Based on the dual network structure (polyvinyl alcohol/poly acrylamide and polyvinyl alcohol/poly (N‐isopropylacrylamide), the actuators can realize the reinforcement compared with the single network. Because of the intrinsic lower critical solution temperature of poly (N‐isopropylacrylamide, both sides of actuators have different swelling rates, enabling them to achieve the thermal‐responsive actuation and shape programming. Therefore, this work is promising to provide a new strategy for designing temperature switches and thermally driven soft robots.
Schematic illustration of temperature‐responsive dual network hydrogels and the hydrogel‐based actuators.
High-performance interlayer materials have garnered considerable interest owing to their low manufacturing costs and applicability in smart windows. In this study, a novel smart-window interlayer ...material capable of selective shielding against both near-infrared (NIR) and ultraviolet (UV) radiation is developed based on the light transmittance control mechanism. An excellent thermoresponsive liquid, denoted as CDs@TRL (viz., carbon quantum dots at thermal-responsive liquid), is synthesized by compositing biomass-based fluorescent carbon quantum dots (CDs) and poly(N-isopropylacrylamide) (pNIPAM) at natural ambient temperature and in an aqueous phase. Due to the characteristics of CDs and synergistic effect of hydrogen bonds, CDs@TRL exhibits a high specific heat capacity (4.41 kJ kg–1 K–1), large thermal storage capacity (264.6 kJ kg–1), and better UV–NIR-blocking properties, compared to pure pNIPAM, as well as improves the sensitivity of thermal response. When injected into a window as a liquid interlayer, CDs@TRL can intelligently adjust the light transmittance according to ambient light intensity to achieve an intelligent response. The shielding rate of a 10 mm-thick CDs@TRL composite liquid against UV radiation (200–400 nm) was more than 95% in an overcast environment with insufficient light and close to 100% in a well-lighted environment. In addition, CDs@TRL is a cost-effective material that can be prepared from a wide range of raw material sources using a simple preparation process and exhibits excellent mobility and recyclability. Because of these features, it is considered to be a promising candidate for developing energy-saving and climate-adapted smart windows.
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•A dual Z-scheme MBSr ternary composite was developed.•The dual Z-scheme heterojunction enhanced visible-light adsorption and the transfer of photoinduced charged carriers.•The ...photocatalytic performance of MBSr is superior to that of single and binary composites.•Possible photodegradation pathway and mechanism of RhB were proposed.
In this study, we synthesized the MBSr (MIL-88A(Fe)/BiOBr/SrFe12O19) dual Z-scheme heterojunction via an accessible hydrothermal method and investigated the photocatalytic performance of MBSr composites for Rhodamine B (RhB) and Methylene blue (MB). The MBSr-1% photocatalyst exhibited excellent photocatalytic performance, resulting the degradation rate of RhB reached approximately 96.2% within 60 min, which was higher than that of M88 (34%), BiOBr (89%) and M88/BiOBr-7% (93.7%) composites. And the MBSr-1% could eliminate 90.1% of MB within 90 min, which displayed the best photodegradation efficiency of prepared photocatalysts. The enhanced photocatalytic performance can be ascribed to the formation of dual Z-scheme heterojunction, which enhanced visible-light absorption and facilitated the transfer of photoinduced carriers. The MBSr-1% was proved to have excellent stability and reusability after six-recycling run. Furthermore, the major reactive species were h+, •O2− and •OH by radical trapping experiments. Finally, a possible photocatalytic pathway and mechanism of MBSr photocatalysts was proposed.
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•The dual Z-scheme UNiMOF/BiVO4/S-C3N4 (NBSCN) photocatalyst with a 2D/3D/2D structure was prepared via a facile one-pot hydrothermal method.•The NBSCN-20% composite exhibits ...impressive photocatalytic activity and stability for TC photodegradation and Cr(VI) photoreduction.•The dual Z-scheme heterojunction presents a more favorable transfer of photoexcited charge carriers than single and binary composites.•The effects of pH and interfering substances on photocatalytic performance were probed.•The feasible photocatalytic mechanism is proposed.
Rapid recombination of the photogenerated carrier, a limited range of photoexcitation, and unsatisfactory photocatalytic activity are the limiting factors in photocatalytic applications. Accelerating photogenerated carrier transfer and constructing surface active sites have become critical tasks. In this study, a dual Z-scheme UNiMOF/BiVO4/S-C3N4 (NBSCN) photocatalyst with a 2D/3D/2D structure was successfully constructed. Under visible-light irradiation, NBSCN outperforms single and binary composites in photocatalytic tetracycline photodegradation and Cr(VI) photoreduction due to the synergistic effect of adsorption and photocatalysis. The maximum photocatalytic efficiency of tetracycline (90.1 %) and Cr(VI) (93.6 %) in 120 min was achieved by NBSCN-20 %. The exceptional photocatalytic activity of NBSCN-20 % can be attributed to the large specific surface area, increased active sites, improved visible-light absorption ranges, and the construction of heterojunctions. The fabricated dual Z-scheme heterojunction at the interface of NBSCN reduces the recombination rate of photogenerated carriers and widens the range of light absorption. NBSCN-20 % exhibits excellent stability in the process of cyclic experiments. On the basis of the results, the feasibility of the dual Z-scheme mechanism is proposed. This work demonstrates that NBSCN-20 % photocatalyst has promising application prospects in removing heavy-metal ions and organic pollutants from aqueous environments.
Accurately predicting traffic flow is a crucial upstream technique in intelligent transportation systems for future travel plans, the efficiency of urban transport, and the regulation of transport ...departments, etc. The mainstream spatiotemporal graph convolutional neural networks are usually based on prior knowledge to predefine adjacency matrix graphs for spatial dependencies of the road network. However, modeling spatial correlation statically limits these models to accurately predict traffic flow, since the spatial correlations of road segments change over time. To address these issues, we propose a spatiotemporal gated transformer network with a graph latent information learning structure, termed GL-STGTN, for spatiotemporal traffic flow forecasting. First, we propose a graph latent information learning structure to dynamically learn the spatial dependencies for road network conditions from global and local learning perspectives. Second, we design a spatiotemporal gated transformer network (STGTN) block, which consists of a localized geographically aware block to extract the local embedding of spatial correlations and a temporal-aware enlarged block to extract local temporal dependencies. The learned spatial and temporal feature embeddings are further aggregated in a spatial multi-head attention module and a temporal multi-head attention module, respectively. In the end, a spatiotemporal fusion layer fuses the spatial and temporal information from the stacked STGTN blocks. Experiments on two public real-world benchmark datasets show that our model outperforms six state-of-the-art models for multi-step traffic flow forecasting.
To better prevent the occurrence of hidden dangers of coal mine accidents and ensure the safety production of coal mine enterprises. This paper mines and analyses the pattern of historical monthly ...hidden danger quantity in the coal mine and constructs three models: the traditional backpropagation (BP) neural network model, the BP neural network based on the adaptive moment estimation optimization algorithm (Adam-BP) model, and the BP neural network prediction model with the introduction of monthly moderators (Month-Adam-BP). The experimental results show that the Adam-BP model can improve the prediction accuracy, in which the mean absolute percentage error (MAPE) improves by 8.93%, the root mean square error (RMSE) improves by 8.15%, the postdifference ratio C improves by 0.04, and the small error probability P improves by 0.12; the Month-Adam-BP model with the introduction of the monthly adjustment factor further improves the prediction accuracy, in which MAPE improves by 2.61%, RMSE improves by 5.41%, the postdifference ratio C improves by 0.06, and the small error probability P improves by 0.03. And the Month-Adam-BP model prediction accuracy reaches the level 2 standard with credible prediction effect; it can also be used to predict coal mines with periodic characteristics of hidden hazard data. Our prediction results show that the predicted number of hidden hazards in this coal mine for the next month is 29, which is an increase compared to the number of hidden dangers in the previous month. Thus, the coal mine safety managers need to strengthen the management of hidden hazards further to prevent accidents, which can better serve the standardization of coal mine safety production and ensure the smooth production of the coal mine.
Bayesian networks (BNs) can be automatically constructed with field data when the data can sufficiently support the objectivity of the model. However, in most risk assessments, field data cannot ...effectively support learning with BNs. In this paper, a new hybrid method is proposed to construct BNs and estimate the corresponding parameters considering the objectivity of field data and the accessibility of expert knowledge. This method is combined with the ISM‐K2 (interpretive structural model) algorithm, copula theory, and the nonparametric method. First, the ISM is used to identify the relationships among the directly and indirectly related variables (i.e., obtain the parent variable set). Second, based on the parent variable set, the K2 algorithm is used to construct BNs with the search volume reduced from an exponential to a quadratic form. Third, copula theory is introduced to consider several marginal distributions of variables, and a copula parameter is used to replace the multivariate joint cumulative distribution. The Gumbel copula function is first introduced to replace the often‐used normal copula function. Fourth, four types of distributions are utilized to fit the characteristics of the variables as the marginal distribution by using a nonparametric method. Finally, the proposed method was used to construct BNs for water inrush and estimate the risk of water inrush for a tunnel.
