A transparent and flexible film heater was fabricated; based on a hybrid structure of poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) and silver nanowires (Ag NWs) using a screen printing; which is a scalable production technology. The resulting film integrates the advantages of the two conductive materials; easy film-forming and strong adhesion to the substrate of the polymer PEDOT:PSS; and high conductivity of the Ag NWs. The fabricated composite films with different NW densities exhibited the transmittance within the range from 82.3% to 74.1% at 550 nm. By applying 40 V potential on the films; a stable temperature from 49 °C to 99 °C was generated within 30 s to 50 s. However; the surface temperature of the pristine PEDOT:PSS film did not increase compared to the room temperature. The composite film with the transmittance of 74.1% could be heated to the temperatures from 41 °C to 99 °C at the driven voltages from 15 V to 40 V; indicating that the film heater exhibited uniform heating and rapid thermal response. Therefore; the PEDOT:PSS/Ag NW composite film is a promising candidate for the application of the transparent and large-scale film heaters.

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The shortage of freshwater resources has become a major obstacle threatening human development, and directly utilizing solar energy by solar evaporators is emerging as a promising method to produce freshwater from the seawater. Compared to many synthetic polymer‐based evaporators, cellulose‐based evaporators are expected to offer more interesting features benefiting from the renewable feature and abundant reserves of cellulose‐contained naturally occurring materials. First, according to the different fabrication methods, cellulose‐based solar evaporators can be divided into two types, i.e., top‐down utilization (wood‐based) and bottom‐up assembled (cellulose composite‐based), respectively. The different fabrication schemes also bring their own unique advantages, such as the bimodal porous structure of wood‐based evaporators and the artificial interconnection microporous network of cellulose composite‐based evaporators. Subsequently, this review further summarizes the most recent advances and highlights of those cellulose‐based solar evaporators, by focusing on their structural regulation strategies (e.g., drilled channel array, asymmetric wettability structure, delignification, 2D waterway, etc.) and evaporation performance improvements (e.g., salt resistance, high evaporation rate, etc.). Finally, the challenges in this field and potential solutions are also discussed, which are anticipated to provide new opportunities toward the future development of cellulose and other kinds of biomass‐based evaporators.

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Hydrogen embrittlement (HE) is a critical issue that hinders the reliability of hydrogenation reactors. Hence, it is of great significance to investigate the effect of hydrogen on fracture toughness of 2.25Cr-1Mo-0.25V steel and weld. In this work, the fracture behavior of 2.25Cr-1Mo-0.25V steel and welds was studied by three-point bending tests under hydrogen-free and hydrogen-charged conditions. The immersion charging method was employed to pre-charge hydrogen inside specimen and the fracture toughness of these joints was evaluated quantitatively. The microstructure and grain size of the specimens were observed by scanning electron microscopy (SEM) and by metallurgical microscopy to investigate the HE mechanisms. It was found that fracture toughness for both the base metal (BM) and the weld zone (WZ) significantly decreased under hydrogen-charged conditions due to the coexistence of the hydrogen-enhanced decohesion (HEDE) and hydrogen-enhanced localized plasticity (HELP) mechanisms. Moreover, the formation and growth of primary voids were observed in the BM, leading to a superior fracture toughness. In addition, the BM compared to the WZ shows superior resistance to HE because the finer grain size in the BM leads to a larger grain boundary area, thus distributing more of the diffusive hydrogen trapped in the grain boundary and reducing the hydrogen content.

When a landslide happens, it is important to recognize the hazard-affected bodies surrounding the landslide for the risk assessment and emergency rescue. In order to realize the recognition, the spatial relationship between landslides and other geographic objects such as residence, roads and schools needs to be defined. Comparing with semantic segmentation and instance segmentation that can only recognize the geographic objects separately, image captioning can provide richer semantic information including the spatial relationship among these objects. However, the traditional image captioning methods based on RNNs have two main shortcomings: the errors in the prediction process are often accumulated and the location of attention is not always accurate which would lead to misjudgment of risk. To handle these problems, a landslide image interpretation network based on a semantic gate and a bi-temporal long-short term memory network (SG-BiTLSTM) is proposed in this paper. In the SG-BiTLSTM architecture, a U-Net is employed as an encoder to extract features of the images and generate the mask maps of the landslides and other geographic objects. The decoder of this structure consists of two interactive long-short term memory networks (LSTMs) to describe the spatial relationship among these geographic objects so that to further determine the role of the classified geographic objects for identifying the hazard-affected bodies. The purpose of this research is to judge the hazard-affected bodies of the landslide (i.e., buildings and roads) through the SG-BiTLSTM network to provide geographic information support for emergency service. The remote sensing data was taken by Worldview satellite after the Wenchuan earthquake happened in 2008. The experimental results demonstrate that SG-BiTLSTM network shows remarkable improvements on the recognition of landslide and hazard-affected bodies, compared with the traditional LSTM (the Baseline Model), the BLEU1 of the SG-BiTLSTM is improved by 5.89%, the matching rate between the mask maps and the focus matrix of the attention is improved by 42.81%. In conclusion, the SG-BiTLSTM network can recognize landslides and the hazard-affected bodies simultaneously to provide basic geographic information service for emergency decision-making.

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