自适应融合层级特征的混合退化图像复原算法

多种退化类型混合的图像比单一类型的退化图像降质更严重,很难建立精确模型对其复原,研究端到端的神经网络算法是复原的关键.现有的基于操作选择注意力网络的算法(operation-wiseattentionnetwork,OWAN)虽然有一定的性能提升,但是其网络过于复杂,运行较慢,复原图像缺乏高频细节,整体效果也有提升的空间.针对这些问题,提出一种基于层级特征融合的自适应复原算法.该算法直接融合不同感受野分支的特征,增强复原图像的结构;用注意力机制对不同层级的特征进行动态融合,增加模型的自适应性,降低了模型冗余;另外,结合L1损失和感知损失,增强了复原图像的视觉感知效果.在DIV2K,BSD500等数据集上的实验结果表明,该算法无论是在峰值信噪比和结构相似性上的定量分析,还是在主观视觉质量方面,均优于OWAN算法,充分证明了该算法的有效性.     

Approaching Ultrastable High‐Rate Li–S Batteries through Hierarchically Porous Titanium Nitride Synthesized by Multiscale Phase Separation

Porous architectures are important in determining the performance of lithium–sulfur batteries (LSBs). Among them, multiscale porous architecutures are highly desired to tackle the limitations of single‐sized porous architectures, and to combine the advantages of different pore scales. Although a few carbonaceous materials with multiscale porosity are employed in LSBs, their nonpolar surface properties cause the severe dissolution of lithium polysulfides (LiPSs). In this context, multiscale porous structure design of noncarbonaceous materials is highly required, but has not been exploited in LSBs yet because of the absence of a facile method to control the multiscale porous inorganic materials. Here, a hierarchically porous titanium nitride (h‐TiN) is reported as a multifunctional sulfur host, integrating the advantages of multiscale porous architectures with intrinsic surface properties of TiN to achieve high‐rate and long‐life LSBs. The macropores accommodate the high amount of sulfur, facilitate the electrolyte penetration and transportation of Li⁺ ions, while the mesopores effectively prevent the LiPS dissolution. TiN strongly adsorbs LiPS, mitigates the shuttle effect, and promotes the redox kinetics. Therefore, h‐TiN/S shows a reversible capacity of 557 mA h g^?1 even after 1000 cycles at 5 C rate with only 0.016% of capacity decay per cycle.     

多级孔ZSM-5分子筛的加氢脱硫性能

以四头聚季铵盐为模板合成的多级孔ZSM-5分子筛为载体、Pd为金属组分制备新型介孔分子筛基Pd催化剂,考察其对4,6-二甲基二苯并噻吩的加氢脱硫活性,并与其他催化剂进行对比。结果表明,与常规ZSM-5分子筛基Pd催化剂和γ-Al_2O_3基Pd催化剂相比,以多级孔ZSM-5分子筛为载体制备的Pd催化剂表现出更高的加氢脱硫活性。该催化剂同时具有介孔和B酸中心,为4,6-二甲基二苯并噻吩的异构化和脱硫反应提供了更多的活性中心,使其能够发生甲基异构化反应,生成3,6-二甲基二苯并噻吩后进行氢解脱硫。     

When Does Communication Learning Need Hierarchical Multi-Agent Deep Reinforcement Learning

Abstract

Multi-agent systems need to communicate to coordinate a shared task. We show that a recurrent neural network (RNN) can learn a communication protocol for coordination, even if the actions to coordinate are performed steps after the communication phase. We show that a separation of tasks with different temporal scale is necessary for successful learning. We contribute a hierarchical deep reinforcement learning model for multi-agent systems that separates the communication and coordination task from the action picking through a hierarchical policy. We further on show, that a separation of concerns in communication is beneficial but not necessary. As a testbed, we propose the Dungeon Lever Game and we extend the Differentiable Inter-Agent Learning (DIAL) framework. We present and compare results from different model variations on the Dungeon Lever Game.     

Hierarchical Coherent Phonons in a Superatomic Semiconductor

The coupling of phonons to electrons and other phonons plays a defining role in material properties, such as charge and energy transport, light emission, and superconductivity. In atomic solids, phonons are delocalized over the 3D lattice, in contrast to molecular solids where localized vibrations dominate. Here, a hierarchical semiconductor that expands the phonon space by combining localized 0D modes with delocalized 2D and 3D modes is described. This material consists of superatomic building blocks (Re₆Se₈) covalently linked into 2D sheets that are stacked into a layered van der Waals lattice. Using transient reflectance spectroscopy, three types of coherent phonons are identified: localized 0D breathing modes of isolated superatom, 2D synchronized twisting of superatoms in layers, and 3D acoustic interlayer deformation. These phonons are coupled to the electronic degrees of freedom to varying extents. The presence of local phonon modes in an extended crystal opens the door to controlling material properties from hierarchical phonon engineering.     

Fe/ZSM-5催化剂的酸性与孔隙特性对合成气直接制备芳烃的影响

以多级孔ZSM-5分子筛为载体，通过等体积浸渍法制备了一种双功能铁基催化剂，用于合成气直接制备芳烃。采用硅烷法合成不同硅铝比和介孔孔隙率的多级孔ZSM-5分子筛载体。催化剂的理化性质通过XRD、XRF、BET和HN₃-TPD进行表征。结果表明：具有较高酸性的分子筛有利于提高油相中芳烃的选择性，当载体的硅铝比为40时，在油相中芳烃选择性可达66.9%；通过调节硅烷剂3-氨丙基三甲氧基硅烷（3-APTMS）的加入量来控制分子筛的介孔孔隙率，可使碳氢产物中芳烃的收率大幅度提高。     

含磷模板和不同硅源对多级孔ZSM-5分子筛结构和催化性能的影响

通过采用不同比例的四丁基氢氧化磷（TBPOH）和四丙基氢氧化铵（TPAOH）混合作为模板剂合成多级孔ZSM-5分子筛，采用XRD，BET，SEM，TEM，NH3-TPD，MAS NMR等方法对分子筛进行物化表征，考察TPAOH和TBPOH的协同作用，期望得到较高结晶度的含P的多级孔ZSM-5。结果表明：以正硅酸乙酯（TEOS）为硅源，在TBPOH和TPAOH物质的量比为1∶1时，合成的多级孔ZSM-5形貌较为规整，由ZSM-5小晶粒堆积而成并呈现出丰富的介孔结构，具有较大的比表面积和孔体积，平均孔径分布于4～10 nm和50～70 nm。相比常规ZSM-5分子筛，合成的多级孔ZSM-5分子筛表现出更强的弱酸性和更多的总酸量。在1，3，5-三异丙苯的裂解反应中，相同转化率下，微孔ZSM-5分子筛表现出较好的苯和二异丙苯的选择性，而多级孔ZSM-5表现出更加优异的丙烯和异丙苯的选择性。     

Synthesis of Hierarchical 4H/fcc Ru Nanotubes for Highly Efficient Hydrogen Evolution in Alkaline Media

Hierarchical metal nanostructures containing 1D nanobuilding blocks have stimulated great interest due to their abundant active sites for catalysis. Herein, hierarchical 4H/face‐centered cubic (fcc) Ru nanotubes (NTs) are synthesized by a hard template‐mediated method, in which 4H/fcc Au nanowires (NWs) serve as sacrificial templates which are then etched by copper ions (Cu²⁺) in dimethylformamide. The obtained hierarchical 4H/fcc Ru NTs contain ultrathin Ru shells (5–9 atomic layers) and tiny Ru nanorods with length of 4.2 ± 1.1 nm and diameter of 2.2 ± 0.5 nm vertically decorated on the surface of Ru shells. As an electrocatalyst for the hydrogen evolution reaction in alkaline media, the hierarchical 4H/fcc Ru NTs exhibit excellent electrocatalytic performance, which is better than 4H/fcc Au‐Ru NWs, commercial Pt/C, Ru/C, and most of the reported electrocatalysts.     

Progress in the design of zeolite catalysts for biomass conversion into biofuels and bio-based chemicals

This article reviews the recent advances in the development of zeolite catalysts for biomass valorization processes to produce both biofuels and/or bio-based chemicals, which is an emerging and fast expanding field. The work deals with different types of feedstocks, including vegetable oils, lignocellulose and sugars, as well as with a number of relevant intermediates and platform molecules. Transformation of biomass into valuable products is hindered by a number of factors, mainly related to its complex composition, as biomass typically consists of bulky molecules with high oxygen content. Accordingly, biomass processing usually requires the combination of multiple steps and severe conditions, hence concepts like atom efficiency, product selectivity, and catalyst deactivation become of special relevance. A great progress has been achieved in the past years engineering the properties of zeolites for being adapted to the challenges associated to biomass valorization. The possibility of tailoring the main physicochemical properties of zeolites has become now a reality, being the major reason that explains the success achieved by this class of materials in a growing variety of biomass conversion pathways, as those described in this work: catalytic cracking and pyrolysis, hydrotreatments, with special relevance for hydrodeoxygenation processes, as well as in a high number of condensation, isomerization, and dehydration reactions. Thus, the development of hierarchical zeolites, exhibiting enhanced accessibility, and the possibility of introducing and combining in a controlled way different types of active sites (Brønsted and Lewis acid centers, basic sites, and metal phases) are the main basis of the excellent performance of zeolites in numerous biomass conversion routes.