Rational Engineering of Multilayered Co3O4/ZnO Nanocatalysts through Chemical Transformations from Matryoshka‐Type ZIFs

Hybrid metal oxides with multilayered structures exhibit unique physical and chemical properties, particularly important to heterogeneous catalysis. However, regulations of morphology, spatial location, and shell numbers of the hybrid metal oxides still remain a challenge. Herein, binary Co₃O₄/ZnO nanocages with multilayered structures (up to eight layers) are prepared via chemical transformation from diverse Matryoshka‐type zeolitic imidazolate frameworks (ZIFs) via a straightforward and scalable calcination method. More importantly, the obtained ZIF‐derived metal oxides (ZDMOs) with versatile layer numbers exhibit remarkable catalytic activity for both gas‐phase CO oxidation and CO₂ hydrogenation reactions, which are directly related to the sophisticated shell numbers (i.e., Co₃O₄‐terminated layers or ZnO‐terminated layers). Particularly, in situ reflectance infrared Fourier transform spectroscopy (DRIFTS) results indicate that the promotional effects of the multilayered structures indeed exist in CO₂ hydrogenation, wherein the key reaction intermediates are quite different for five‐layer and six‐layer ZDMOs. For instance, *HCOO is the predominant intermediate over the six‐layer ZDMO; on the contrary, *H₃CO is the crucial species over the five‐layer ZDMO. The ZnO/Co₃O₄ interface should be the active sites for CO₂ hydrogenation to *HCOO and *H₃CO species, which are ultimately converted to the products (CH₄ or methanol). Accordingly, the work here provides a convenient way to facilely engineer multilayered Co₃O₄/ZnO nanocomposites with precisely controlled shell numbers for heterogeneous catalysis applications.     

3D Macroscopic Architectures from Self‐Assembled MXene Hydrogels

Assembly of 2D MXene sheets into a 3D macroscopic architecture is highly desirable to overcome the severe restacking problem of 2D MXene sheets and develop MXene‐based functional materials. However, unlike graphene, 3D MXene macroassembly directly from the individual 2D sheets is hard to achieve for the intrinsic property of MXene. Here a new gelation method is reported to prepare a 3D structured hydrogel from 2D MXene sheets that is assisted by graphene oxide and a suitable reductant. As a supercapacitor electrode, the hydrogel delivers a superb capacitance up to 370 F g^?1 at 5 A g^?1, and more promisingly, demonstrates an exceptionally high rate performance with the capacitance of 165 F g^?1 even at 1000 A g^?1. Moreover, using controllable drying processes, MXene hydrogels are transformed into different monoliths with structures ranging from a loosely organized porous aerogel to a dense solid. As a result, a 3D porous MXene aerogel shows excellent adsorption capacity to simultaneously remove various classes of organic liquids and heavy metal ions while the dense solid has excellent mechanical performance with a high Young's modulus and hardness.     

Engineering a Nanoscale Al‐MOF‐Armored Antigen Carried by a “Trojan Horse”‐Like Platform for Oral Vaccination to Induce Potent and Long‐Lasting Immunity

Vaccination via the oral administration of an antigen faces many challenges, including gastrointestinal (GI) proteolysis and mucosal barriers. To limit GI proteolysis, a biomimetically mineralized aluminum‐based metal–organic framework (Al‐MOF) system that is resistant to ambient temperature and pH and can act synergistically as a delivery vehicle and an adjuvant is synthesized over a model antigen ovalbumin (OVA) to act as armor. To overcome mucosal barriers, a yeast‐derived capsule is used to carry the Al‐MOF‐armored OVA as a “Trojan Horse”‐like transport platform. In vitro experiments reveal that the mineralization of Al‐MOFs forms an armor on OVA that protects against highly acidic and degradative GI conditions. However, the mineralized Al‐MOFs can gradually disintegrate in a phosphate ion‐containing simulated intracellular fluid, slowly releasing their encapsulated OVA. In vivo studies reveal that the “Trojan Horse”‐like transport platform specifically targets intestinal M cells, favoring the transepithelial transport of the Al‐MOF‐armored OVA, followed by subsequent endocytosis in local macrophages, ultimately accumulating in mesenteric lymph nodes, yielding long‐lasting, high‐levels of mucosal S‐IgA and serum IgG antibodies. Such an engineered delivery platform may represent a promising strategy for the oral administration of prophylactic or therapeutic antigens for vaccination.     

Rear‐Passivated Ultrathin Cu(In,Ga)Se2 Films by Al2O3 Nanostructures Using Glancing Angle Deposition Toward Photovoltaic Devices with Enhanced Efficiency

In this work, for the first time, the addition of aluminum oxide nanostructures (Al₂O₃ NSs) grown by glancing angle deposition (GLAD) is investigated on an ultrathin Cu(In,Ga)Se₂ device (400 nm) fabricated using a sequential process, i.e., post‐selenization of the metallic precursor layer. The most striking observation to emerge from this study is the alleviation of phase separation after adding the Al₂O₃ NSs with improved Se diffusion into the non‐uniformed metallic precursor due to the surface roughness resulting from the Al₂O₃ NSs. In addition, the raised Na concentration at the rear surface can be attributed to the increased diffusion of Na ion facilitated by Al₂O₃ NSs. The coverage and thickness of the Al₂O₃ NSs significantly affects the cell performance because of an increase in shunt resistance associated with the formation of Na₂Se_X and phase separation. The passivation effect attributed to the Al₂O₃ NSs is well studied using the bias‐EQE measurement and J–V characteristics under dark and illuminated conditions. With the optimization of the Al₂O₃ NSs, the remarkable enhancement in the cell performance occurs, exhibiting a power conversion efficiency increase from 2.83% to 5.33%, demonstrating a promising method for improving ultrathin Cu(In,Ga)Se₂ devices, and providing significant opportunities for further applications.     

User identification via neural network based language models

Identifying compromised accounts on online social networks that are used for phishing attacks or sending spam messages is still one of the most challenging problems of cyber security. In this research, the authors explore an artificial neural network‐based language model to differentiate the writing styles of different users on short text messages. In doing so, the aim is to be able to identify compromised user accounts. The results obtained indicate that one can learn the language model on one dataset and can generalize it to different datasets to identify users with high accuracy and low false alarm rates without any modification to the language model.     

Modeling and analysis for multilayered complex communication network of satellite navigation system

This study is extended to construct the network model, the node model, and the link model of complex communication network for satellite navigation system (CCN‐SNS) based on the hierarchical architecture. Firstly, a method called snapshots was proposed to describe the dynamic topology for CCN‐SNS; secondly, another method was put forward to model the different nodes of the CCN‐SNS; thirdly, the different links between every two different nodes were modeled. Therefore, based on the OPNET tools, a simulation for the CCN‐SNS, which contains the models that proposed earlier used to analyze the navigation accuracy and network transmission performance, was performed.     

Novel method for transferring access control list rules to synchronize security protection in a locator/identifier separation protocol environment with cross‐segment host mobility

Extended access control lists (ACLs) are used to filter packets for network security. However, in current network frameworks, ACL rules are not transferred simultaneously with devices that move across network segments. The Internet Engineering Task Force proposed the Locator/Identifier Separation Protocol (LISP), which enables routers (xTRs) to configure ACL rules for blocking immobile endpoint identifiers (EIDs). However, when an EID moves from the original xTR to a new xTR, the ACL rules at the original xTR cannot be transferred with the EID. Thus, the new xTR lacks the corresponding ACL rules to effectively block the EID, resulting in security risks. The highlights of this study are as follows. First, a method is proposed for dynamically transferring ACL rules in LISP environments and frameworks. Second, the map‐register and map‐notify protocols were combined to encapsulate and transfer the ACL rules and thus obviate an additional process required to transfer these rules. Third, the experimental results verified that the proposed method can be used to achieve synchronized security protection in an LISP environment involving cross‐segment EID movements.     

Interoperability in semantic Web of Things: Design issues and solutions

The significant improvement in processing power, communication, energy consumption, and the size of computational devices has led to the emergence of the Internet of Things (IoT). IoT projects raise many challenges, such as the interoperability between IoT applications because of the high number of sensors, actuators, services, protocols, and data associated with these systems. Semantics solves this problem by using annotations that define the role of each IoT element and reduces the ambiguity of information exchanged between the devices. This work presents SWoTPAD, a semantic framework that helps in the development of IoT projects. The framework is designer oriented and provides a semantic language that is more user‐friendly than OWL‐S and WSML and allows the IoT designer to specify devices, services, environment, and requests. Following this, it makes use of these specifications and maps them for RESTful services. Additionally, it generates an automatic service composition engine that is able to combine services needed to handle complex user requests. We validated this approach with two case studies. The former concerns a residential security system and the latter, the cloud application deployment. The average time required for service discovery and automatic service composition corresponds to 72.9% of the service execution time in the case study 1 and 64.4% in the case study 2.     

Comparison of self‐adaptive dynamic differential evolution and particle swarm optimization for smart antennas in wireless communication

In this paper, ultrawide band (UWB) communication systems with eight transmitting and receiving ring antenna arrays are implemented to test the bit error rate and capacity performance. By using the ray‐tracing technique to compute any given indoor wireless environment, the impulse response of the system can be calculated. The synthesized beamforming problem can be reformulated into a multiobjective optimization problem. Self‐adaptive dynamic differential evolution (SADDE) and particle swarm optimization (PSO) are used to find the excitation current and the feed line length of each antenna to form the appropriate beam pattern. This pattern can then reduce the bit error rate and increase the channel capacity and receiving energy. Numerical results show that the fitness value and the convergence speed by the SADDE are better than those by the PSO. Moreover, the SADDE had better results for both line‐of‐sight and nonline‐of‐sight cases. In other words, compared with PSO, SADDE has improved more effectively the main beam radiation energy and reduced the multipath interference.