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Winter extreme cold events (ECEs) have profound impacts on human health, transportation, energy consumption and the economy, particularly associated with high‐humidity conditions. Recent research has indicated a growing interest in extreme temperature events that account for the presence of water vapour. However, the characteristics of humidity‐related ECEs (HECEs) remain unclear. Given the rise in atmospheric moisture due to global warming, understanding the influence of water vapour on HECEs becomes crucial. This study examined variations in HECEs identified using the wet‐bulb globe temperature (WBGT) in China during 1959–2020 and quantified the impacts of water vapour. The results revealed a decrease in the intensity and frequency of HECEs in China during this period, except for in northern China, where the intensity increased, which contrasts with the trends in traditional ECEs. Furthermore, strong HECEs were found to exhibit greater frequency, duration and intensity in northern China than weak HECEs. Additionally, the specific humidity for all categories of HECEs in China exhibited an upward trend, with a more rapid increase for strong HECEs. The findings indicated that the intensity of HECEs is positively correlated with the increase in water vapour. Defining a water vapour amplification factor revealed amplified intensity and duration at most grid points, particularly across northern China. Therefore, while winter warming reduces traditional ECEs, HECEs persist and even intensify as humidity increases, confirming significant amplification by water vapour. Our results emphasized the importance of increasing water vapour, driven by global warming, which may increase the risk of HECEs in the future. [ABSTRACT FROM AUTHOR]

Mechanical metamaterials are often designed with particular properties for specific load‐bearing functions. Alternatively, this study aims to create a class of active lattice metamaterials, dubbed self‐activated solids, that can learn desired stiffness tensors from the elastic deformations they experienced, a crucial feature to improve the performance, efficiency, and functionality of materials. Artificial adaptive matters that combine sensory, control, and actuation elements can offer appealing solutions. However, challenges still remain: The designs will rely on accurate off‐line and global computations, as well as intricate coordination among individual elements. Here, a simple online and local learning strategy is initiated based on contrastive Hebbian learning to gradually guide self‐activated solids to possess sought‐after stiffness tensors autonomously and reversibly. During learning, the bond stiffness of the active lattice varies depending only on its local strain. The numerical tests show that the self‐activated solid can not only achieve the desired bulk, shear, and coupling moduli but also manifest uni‐mode and bi‐mode extremal materials by itself after experiencing the corresponding elastic deformations. Further, the self‐activated solid can also achieve the desired time‐varying moduli when exposed to temporally different loads. The design is applicable to any lattice geometries and is resistant to damage and instabilities. The material design approach and the physical learning strategy suggested can benefit the design of autonomous materials, physical learning machines, and adaptive robots. [ABSTRACT FROM AUTHOR]

Electrothermal carbon nanotube (CNT) yarn muscles can provide large strokes during thermal cycling. However, the slow cooling rate of thermal muscles limits their applications, since large diameter prior‐art thermal muscles cannot be rapidly cycled. Herein, a fast thermally powered sheath‐driven yarn muscle that uses a hybrid CNT sheath and an inexpensive polymer core, is reported. The stroke recovery rate for the hybrid muscle is much lower at all frequencies than for about the same diameter sheath‐driven muscle, which means that the full cycle contractile mechanical power is much higher than for comparable prior‐art hybrid muscle. More specifically, the coiled sheath‐driven muscle contracts 14.3% at 1 Hz and 7.3% at 8 Hz in air when powered by a square‐wave electrical voltage input, which is 2.9‐ and 11.4‐times the stroke of the coiled hybrid muscle at these respective frequencies. An average power density of 12 kW kg−1 is obtained for a sheath‐driven muscle, which is 42‐times that for human skeletal muscle. These high‐performance results since the heating that drives fast actuation cycles are largely restricted to the muscle sheath, and this sheath is in direct contact with ambient temperature air. [ABSTRACT FROM AUTHOR]

The rational selection and integration of materials play important roles in advancing electrochemical sensing. Herein, a highly sensitive electrochemical platform based on composites of graphene oxide (GO) and conductive YbHHTP metal–organic framework (HHTP = 2,3,6,7,10,11‐hexahydroxytriphenylene) for the detection of dopamine (DA) and uric acid (UA) is reported. The composites are prepared by the introduction of GO into the hydrothermal synthesis of YbHHTP. The morphology, structure, and property of the resultant GO/YbHHTP composites are characterized by scanning electron microscopy, transmission electron microscopy, X‐ray diffraction, ultraviolet–visible spectroscopy, X‐ray photoelectron spectroscopy, electrochemical impedance spectroscopy, and cycle voltammetry. The results show that this in situ integration strategy facilitates the homogeneous anchoring of YbHHTP nanorods on the surface of GO sheets to achieve a considerable conductivity in the composites and fast electrochemical kinetics for probe molecules. As a result, the GO(2.0)/YbHHTP‐modified electrodes exhibit ultrahigh sensitivity in detection of DA (3.62 µA µm−1) and UA (1.97 µA µm−1) as well as excellent reproducibility, stability, and anti‐interfere ability. [ABSTRACT FROM AUTHOR]

This article presents integrated experiments and constitutive modeling of cyclic compressive deformation and Poisson behavior of unidirectional (UD) fiber‐reinforced polymer matrix composites (PMCs). Consecutive loading‐unloading tests with a gradually increasing peak stress are performed for five cycles and on UD laminates with different fiber orientations. Nonlinear accumulation of plastic strain with the peak stress is observed both in the axial and lateral directions for all fiber orientations and described by a nonassociative plasticity model. This model enables the collapsing of axial and lateral stress‐plastic strain curves from different fiber orientations into a single master curve in the effective stress‐effective plastic strain plane and allows accurate predictions of compressive plastic Poisson's ratio. Nonlinear unloading behavior appears in the cycles and is attributed to the recovery of nonlinear elastic strain. A linear relationship between plastic strain and nonlinear elastic strain is assumed regardless of the axial and lateral directions. By incorporating this linear dependence into the nonassociative plasticity model, the cyclic evolution of nonlinear elastic strain is simulated. Experimental results of UD laminates with different fiber orientations are used to validate the accuracy of the model in the cyclic compressive nonlinear response and Poisson effect of PMCs. [ABSTRACT FROM AUTHOR]

Two‐dimensional (2D) layered graphitic carbon nitride (gCN) nanosheets offer intriguing electronic and chemical properties. However, the exfoliation and functionalisation of gCN for specific applications remain challenging. We report a scalable one‐pot reductive method to produce solutions of single‐ and few‐layer 2D gCN nanosheets with excellent stability in a high mass yield (35 %) from polytriazine imide. High‐resolution imaging confirmed the intact crystalline structure and identified an AB stacking for gCN layers. The charge allows deliberate organic functionalisation of dissolved gCN, providing a general route to adjust their properties. [ABSTRACT FROM AUTHOR]

Abstract: Materials that can simultaneously achieve excellent electrical conductivity and stretchability are essential components for the next‐generation stretchable electronics. Herein, a highly conductive and stretchable graphene honeycomb (GHC) sandwich consisting of a porous GHC/polydimethylsiloxane (PDMS) composite core and ultrahigh‐density graphene foam/PDMS composite face sheets is rationally assembled. The GHCs prepared by a 3D printing technique possess a long‐range ordered hexagonal porous structure with an ultralow density of 3.25 mg cm−3 and deliver an excellent electrical conductivity of 72 S m−1. To the best of authors' knowledge, they are the lightest honeycomb structure reported in open literature. The highly porous GHC core endows the sandwich with an ultralow resistance change over large external strains of 60% with excellent structural durability. A stretchable light‐emitting display is demonstrated using the sandwich as the electric circuit and light‐emitting diodes as the pixels, which exhibits reliable lighting performance under different loading conditions. [ABSTRACT FROM AUTHOR]

The drug-serum albumin interaction plays a dominant role in drug efficacy and disposition. The glycation of serum albumin that occurs during diabetes may affect its drug-binding properties in vivo. In order to evaluate the interactivity characteristics of cyanidin-3- O-glucoside (C3G) with human serum albumin (HSA) and glycated human serum albumin (gHSA), this study was undertaken using multiple spectroscopic techniques and molecular modeling analysis. Time-resolved fluorescence and the thermodynamic parameters indicated that the quenching mechanism was static quenching, and hydrogen bonding and Van der Waals force were the main forces. The protein fluorescence could be quenched by C3G, whereas the polarity of the fluorophore was not obviously changed. C3G significantly altered the secondary structure of the proteins. Furthermore, the interaction force that existed in the HSA-C3G system was greater than that in the gHSA-C3G system. Fluorescence excitation emission matrix spectra, red edge excitation shift, Fourier transform infrared spectroscopy and circular dichroism spectra provided further evidence that glycation could inhibit the binding between C3G and proteins. In addition, molecular modeling analysis supported the experimental results. The results provided more details for the application of C3G in the treatment of diabetes. [ABSTRACT FROM AUTHOR]