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We propose the AI painting model based on the generative adversarial network and analyze the color, pattern, and visual hierarchy of the AI painting’s visual expressiveness. Starting from the painting sketch, the corresponding generator and discriminator are integrated to construct the AI painting model based on a generative adversarial network, and the training strategy, optimization objective, and loss function calculation formula of the model are given. The visual analysis of the AI painting based on deep learning technology is combined with research analysis. In terms of simplifying sketches and generating pictures, the model presented in this paper performs more prominently than the control models (CNN and SVM), which is reflected in the loss value and F1 value, respectively. In addition, there are significant differences between AI paintings and traditional paintings in the use of color (P = 0.035, T = 1.478), pattern cultural allegory (P = 0.011, T = 0.347), and visual hierarchy (P = 0.008, T = 2.993), and AI paintings are more visually expressive than traditional paintings, and at the same time, the regression equation of the AI paintings’ visual expressiveness is 0.125+0.179*Color Use+0.188*Pattern Cultural Allegory+0.234 Visual Hierarchy. This study provides a clearer perception of the modern art creation trend and its visual expressiveness, which is of enormous significance in boosting the development of the art field.

As a fundamental industrial catalytic process, the semihydrogenation of alkynes presents a challenge in striking a balance between activity and selectivity due to the issue of over‐hydrogenation. Herein, we develop an efficient catalytic system based on single‐atom Pd catalysts supported on boron‐containing amorphous zeolites (Pd/AZ−B), achieving the tradeoff breaking between the activity and selectivity for the selective hydrogenation of alkynes. Advanced characterizations and theoretical density functional theory calculations confirm that the incorporated B atoms in the Pd/AZ−B can not only alter the geometric and electronic properties of Pd atoms by controlling the electron migration from Pd but also mitigate the interaction between alkene and the catalyst supports. This boosts the exceptional catalytic efficacy in the semihydrogenation of phenylacetylene to styrene under mild conditions (298 K, 2 bar H2), achieving a recorded turnover frequency (TOF) value of 24198 h−1 and demonstrating 95 % selectivity to styrene at full conversion of phenylacetylene. By comparison, the heteroatom‐free amorphous zeolite‐anchored Pd nanoparticles and the commercial Lindlar catalyst have styrene selectivities of 73 % and 15 %, respectively, under identical reaction conditions. This work establishes a solid foundation for developing highly active and selective hydrogenation catalysts by controllably optimizing their electronic and steric properties. [ABSTRACT FROM AUTHOR]

The traditional passive heat dissipation method has low heat dissipation efficiency, which is not suitable for the heat dissipation of the concentrated heat source inside the long-focal aerial camera, resulting in temperature level changes and temperature gradients in the optical system near the heat source, which seriously affect the imaging performance of the aerial camera. To solve this problem, an active heat dissipation method of liquid cooling cycle is proposed in this paper. To improve the solving efficiency and ensure simulation accuracy, a dynamic boundary information transfer method based on grid area weighting is proposed. The thermal simulation results show that the liquid cooling method reduces the heat source temperature by 70.12%, and the boundary temperature transfer error is 0.015%. The accuracy of thermal simulation is verified by thermal test, and the simulation error is less than 6.44%. In addition, the performance of the optical system is further analyzed, and the results show that the MTF of the optical system is increased from 0.077 to 0.194 under the proposed active liquid cooling cycle heat dissipation method. [ABSTRACT FROM AUTHOR]

2D conjugated metal–organic frameworks (2D c‐MOFs) are emerging as unique electroactive materials for electronics and spintronics. The structural design and discovery of Kagome‐type 2D c‐MOFs exhibiting a metallic state are of paramount significance, yet remain rarely explored. Here, the solution synthesis of benzenehexol‐based 2D c‐MOFs based is presented on the tetrahydroxy‐1,4‐quinone (THQ) ligand. This study shows that controlling the pH of the reaction system to ≈7.5 yields an energetically favorable nonporous Cu3(C6O6) with a Kagome lattice, while at a pH of ≈10, the known porous Cu3(C6O6)2 with a honeycomb lattice is obtained. The crystal structures of both Cu3(C6O6)2 and Cu3(C6O6) are resolved with near‐atomic precision (resolution, 1.8 Å) using an imaging technique. Unlike the p‐type semiconducting behavior of Cu3(C6O6)2, theoretical studies identify Cu3(C6O6) as a metal due to its unique structural topology. The metallic state of Cu3(C6O6) is experimentally validated by terahertz time‐domain spectroscopy (THz‐TDS), which shows an increase in conductivity upon cooling. Scattering‐type scanning near‐field optical microscopy (s‐SNOM) measurements further support these findings by revealing an increase in normalized reflectivity with decreasing temperature. This work provides a new avenue for tailoring the structural topology of 2D c‐MOFs to attain the Kagome lattice and metallic state. [ABSTRACT FROM AUTHOR]

Formic acid (FA) dehydrogenation and CO2 hydrogenation to FA/formate represent promising methodologies for the efficient and clean storage and release of hydrogen, forming a CO2‐neutral energy cycle. Here, we report the synthesis of highly dispersed and stable bimetallic Pd‐based nanoparticles, immobilized on self‐pillared silicalite‐1 (SP‐S‐1) zeolite nanosheets using an incipient wetness co‐impregnation technique. Owing to the highly accessible active sites, effective mass transfer, exceptional hydrophilicity, and the synergistic effect of the bimetallic species, the optimized PdCe0.2/SP‐S‐1 catalyst demonstrated unparalleled catalytic performance in both FA dehydrogenation and CO2 hydrogenation to formate. Remarkably, it achieved a hydrogen generation rate of 5974 molH2 molPd−1 h−1 and a formate production rate of 536 molformate molPd−1 h−1 at 50 °C, surpassing most previously reported heterogeneous catalysts under similar conditions. Density functional theory calculations reveal that the interfacial effect between Pd and cerium oxide clusters substantially reduces the activation barriers for both reactions, thereby increasing the catalytic performance. Our research not only showcases a compelling application of zeolite nanosheet‐supported bimetallic nanocatalysts in CO2‐mediated hydrogen storage and release but also contributes valuable insights towards the development of safe, efficient, and sustainable hydrogen technologies. [ABSTRACT FROM AUTHOR]

Two‐dimensional polymers (2DPs) and their layer‐stacked 2D covalent organic frameworks have recently emerged as nonlinear optical (NLO) materials for potential applications in optics. However, the chemistry for designing third‐order NLO 2DP films with large nonlinear absorption coefficient (β) has remained a mystery. Herein, three highly crystalline porphyrin‐integrated 2D polyimines (named as 2DPI‐Zn‐Azo, 2DPI‐2H‐Azo, and 2DPI‐Zn), which are homogeneous films showing large lateral areas over cm2, uniform transparency, and thickness of tens of nanometers are reported. Particularly, the 2DPI‐Zn‐Azo film comprising zinc porphyrin and –NN– displays a large saturable absorption under 532 nm and the highest β (−1.88 × 105 cm GW−1) among the three 2D polyimines, that is also 2–5 orders of magnitude higher than the state‐of‐art performance of photoactive small molecules, porphyrin‐integrated 2DPs, and inorganic 2D materials. Control experiments in combination with theoretical calculation discover that the embedding of metal centers and –NN– results in highly delocalized π‐electrons and narrow bandgap in 2DPI‐Zn‐Azo, which enables fast transfer of the photogenerated electrons after the light‐excited charge separation, thus boosting the NLO performance. This work opens up a new path for the construction of highly efficient third‐order NLO film materials, and pushes the development of 2DPs for optics and optoelectronics. [ABSTRACT FROM AUTHOR]

Reconstruction‐engineered electrocatalysts with enriched high active Ni species for urea oxidation reaction (UOR) have recently become promising candidates for energy conversion. However, to inhibit the over‐oxidation of urea brought by the high valence state of Ni, tremendous efforts are devoted to obtaining low‐value products of nitrogen gas to avoid toxic nitrite formation, undesirably causing inefficient utilization of the nitrogen cycle. Herein, we proposed a mediation engineering strategy to significantly boost high‐value nitrite formation to help close a loop for the employment of a nitrogen economy. Specifically, platinum‐loaded nickel phosphides (Pt‐Ni2P) catalysts exhibit a promising nitrite production rate (0.82 mol kWh−1 cm−2), high stability over 66 h of Zn‐urea‐air battery operation, and 135 h of co‐production of nitrite and hydrogen under 200 mA cm−2 in a zero‐gap membrane electrode assembly (MEA) system. The in situ spectroscopic characterizations and computational calculations demonstrated that the urea oxidation kinetics is facilitated by enriched dynamic Ni3+ active sites, thus augmenting the "cyanate" UOR pathway. The C−N cleavage was further verified as the rate‐determining step for nitrite generation. [ABSTRACT FROM AUTHOR]

As an important parameter of forest biomass, forest height is of great significance for the calculation of forest carbon stock and the study of the carbon cycle in large-scale regions. The main idea of the current forest height inversion methods using multi-baseline P-band polarimetric interferometric synthetic aperture radar (PolInSAR) data is to select the best baseline for forest height inversion. However, the approach of selecting the optimal baseline for forest height inversion results in the process of forest height inversion being unable to fully utilize the abundant observation data. In this paper, to solve the problem, we propose a multi-baseline forest height inversion method combining analytic and geometric expression of the random volume over ground (RVoG) model, which takes into account the advantages of the selection of the optimal observation baseline and the utilization of multi-baseline information. In this approach, for any related pixel, an optimal baseline is selected according to the geometric structure of the coherence region shape and the functional model for forest height inversion is established by the RVoG model's analytic expression. In this way, the other baseline observations are transformed into a constraint condition according to the RVoG model's geometric expression and are also involved in the forest height inversion. PolInSAR data were used to validate the proposed multi-baseline forest height inversion method. The results show that the accuracy of the forest height inversion with the algorithm proposed in this paper in a coniferous forest area and tropical rainforest area was improved by 17% and 39%, respectively. The method proposed in this paper provides a multi-baseline PolInSAR forest height inversion scheme for exploring regional high-precision forest height distribution. The scheme is an applicable method for large-scale, high-precision forest height inversion tasks. [ABSTRACT FROM AUTHOR]