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Advancing flexible pressure sensors with high sensitivity and a wide measurement range presents a major challenge and development focus in the field. Although current sensing mechanisms can achieve high sensitivity, their structural integrity and load-bearing capacity often suffer under significant pressure. Here, we report a new type of piezoresistive sensor utilizing a PVP/SnO2 nanofiber membrane as the sensing layer and carbon cloth as the electrode. The sensor is engineered to maintain extreme sensitivity and stability under conditions beyond those of traditional laboratory environments. Percolation theory is used to interpret the initial resistance decrease, and the quantum tunneling effect explains the rapid resistance drop at moderate pressures. At high pressure magnitudes, where the resistance variation is linear, the classical resistive formula is applied. Remarkably, it demonstrates a remarkable transition in resistance, similar to a semiconductor-to-conductor transformation under pressure, achieving a high sensitivity of up to 1.43 × 106 kPa−1 across a measurement range of 0–190 kPa. Additionally, the sensor exhibits a rapid response time of 80 ms and a relaxation time of 120 ms while retaining full textile flexibility, superior air permeability, excellent washability, enhanced reliability, and outstanding ultraviolet (UV) resistance. These exceptional characteristics highlight the potential of the sensor for wearable technology and pressure monitoring applications. [ABSTRACT FROM AUTHOR]

This study proposes a generalised value network (VN) model for sharing economy platforms (SEP) and analyzes the internal structure and functional mechanisms by utilising sharing economy theories and corporate value creation. Platform business strategy and the development of the VN system are further discussed through the case study of a ride-hailing platform. This paper proposes that the SEP realises its own value creation and growth by creating and extending the user-centered VN. The user base is a core element of the sustainable development of an SEP, which should thus constantly strengthen its customer-centricity, information-sharing, and resource integration strategies to enhance overall efficiency and core competitiveness. In addition, sustainable growth could be achieved by exploiting the value of information data deeply and expanding as well as enriching the business ecosystem. [ABSTRACT FROM AUTHOR]

Resonant magnetic x-ray scattering from dense self-assemblies of 9-nm diameter epsilon-Co and hcp-Co particles is reported. For lower anisotropy epsilon-Co we find remanent magnetic scattering that is significantly enhanced, indicating preferred inter-particle moment orientations of both antiferromagnetic and ferromagnetic character. This interaction-mediated collective behavior is consistent with dipolar fields and exists well above the isolated particles blocking temperature where thermal activation is operative, suggesting that magnetostatic super-spin waves exist in such systems.

Nanostructured metal-nitrides have attracted tremendous interest as a new generation of catalysts for electroreduction of CO2, but these structures have limited activity and stability in the reduction condition. Herein, we report a method of fabricating FeN/Fe3N nanoparticles with FeN/Fe3N interface exposed on the NP surface for efficient electrochemical CO2 reduction reaction (CO2RR). The FeN/Fe3N interface is populated with Fe−N4 and Fe−N2 coordination sites respectively that show the desired catalysis synergy to enhance the reduction of CO2 to CO. The CO Faraday efficiency reaches 98% at −0.4 V vs. reversible hydrogen electrode, and the FE stays stable from −0.4 to −0.9 V during the 100 h electrolysis time period. This FeN/Fe3N synergy arises from electron transfer from Fe3N to FeN and the preferred CO2 adsorption and reduction to *COOH on FeN. Our study demonstrates a reliable interface control strategy to improve catalytic efficiency of the Fe–N structure for CO2RR. Understanding and controlling chemical environment of metal-N-catalysts is of great importance. In this work, the authors reveal FeN/Fe3N interface with Fe-N4 and Fe-N2 coordination sites for enhanced electrochemical CO2 reduction to CO. [ABSTRACT FROM AUTHOR]

Support vector machine (SVM) is a new machine learning method developed from statistical learning theory. Since the objective function of the unconstrained SVM model is a non-smooth function, a lot of fast optimization algorithms can't be used to find the solution. Firstly, to overcome the non-smooth property of this model, a new padé33 approximation smooth function is constructed by rational approximation method, and a new smooth support vector machine model (SSVM) is established based on the smooth function. Then, by analyzing the performance of the smooth function, we find that the smooth precision is significantly higher than existing smooth functions. Moreover, theoretical and rigorous mathematical analyses are given to prove the convergence of the new model. Finally, it is applied to the heart disease diagnosis. The results show that the Padé33-SSVM model has better classification capability than existing SSVMs. [ABSTRACT FROM AUTHOR]

Due to the wide application of wearable electronic devices in daily life, research into flexible electronics has become very attractive. Recently, various polymer-based sensors have emerged with great sensing performance and excellent extensibility. It is well known that different structural designs each confer their own unique, great impacts on the properties of materials. For polymer-based pressure/strain sensors, different structural designs determine different response-sensing mechanisms, thus showing their unique advantages and characteristics. This paper mainly focuses on polymer-based pressure-sensing materials applied in different microstructures and reviews their respective advantages. At the same time, polymer-based pressure sensors with different microstructures, including with respect to their working mechanisms, key parameters, and relevant operating ranges, are discussed in detail. According to the summary of its performance and mechanisms, different morphologies of microstructures can be designed for a sensor according to its performance characteristics and application scenario requirements, and the optimal structure can be adjusted by weighing and comparing sensor performances for the future. Finally, a conclusion and future perspectives are described. [ABSTRACT FROM AUTHOR]

This study quantitively estimates the energy and environmental impacts of China's promotion of battery electric vehicles (BEVs) in the context of banning the sale of gasoline vehicles (GVs). Combining the population ecological growth model and the life cycle assessment method, the potential of BEVs promotion in reducing fossil energy (FE) consumption and greenhouse gas (GHG) emissions under different timings of banning GV sales was dynamically simulated and analyzed. The results show that the current life cycle FE consumption and GHG emissions of BEVs are approximately 40.1% and 26.6% lower than those of GVs, respectively. Based on the development of automobile technology and the national energy plan, replacing GVs with BEVs can reduce GHG emissions and FE consumption by up to 43.61–55.81% and 46.33–55.45%, respectively. Compared with the scenario without BEV promotion, if sales of GVs in China are banned between 2040 and 2060, the point at which the carbon peak of the automobile market will be reached will be advanced by approximately two years, and the corresponding carbon peak value will be reduced by approximately 13.58–28.79 million tons of CO2-eq (MtCO2e). In addition, the annual FE savings and GHG emission reductions will reach approximately 2.99–6.35 million TJ and 276.54–488.77 MtCO2e by 2050. This research work will not only help authorities, managers, and the public to better understand the environmental and energy impacts of promoting new energy vehicles, but also provide a forward-looking reference for formulating comprehensive, systematic, and reasonable industrial planning to better promote a green and sustainable transformation of the automotive sector and solve the relevant energy and environmental problems. [ABSTRACT FROM AUTHOR]

Reconstructing the process of plate subduction is challenging, but clues can be found in sedimentary basins and the nature of deformation of the overriding plate. Here we analyse a seismic‐reflection dataset that indicates tectonic inversion in the southwestern Songliao basin, NE China, to construct the geodynamics of Palaeo‐Pacific plate. The study area consists of Lower Cretaceous rift sediments that were cut by normal faults, folded, and subsequently overlain by undeformed Upper Cretaceous strata, revealing a process of basin inversion. The timing of inversion is constrained to the interval between deposition of the Lower and Upper Cretaceous sediments (i.e. 87–71 Ma). Mud volcanoes and similar structures associated with inversion are observed in basins throughout the region. The change from tectonic extension to shortening in the overriding plate is recorded by sedimentation and inversion of the basins, and was triggered by an increase in the rate of motion of the subducting Palaeo‐Pacific plate. [ABSTRACT FROM AUTHOR]