Layered Framework Research Articles

Layered 3D Covalent Organic Framework Films Based on Carbon-Carbon Bonds.

The development of covalent organic frameworks (COFs) during the past decades has led to a variety of promising applications within gas storage, catalysis, drug delivery, and sensing. Even though most described synthesis methods result in powdery COFs with uncontrolled grain size, several approaches to grow COF films have recently been explored. However, in all COFs so far presented, the isolated materials are chemically homogeneous, with all functionalities homogeneously distributed throughout the entire material. Strategies to synthetically manipulate the spatial distribution of functionalities in a single film would be game changing. Specifically, this would allow for the introduction of local functionalities and even consecutive functions in single frameworks, thus broadening their synthetic versatility and application potential. Here, we synthesize two 3D crystalline COF films. The frameworks, the ionic B-based and neutral C-based COFs, have similar unit cell parameters, which enables their epitaxial stacking in a layered 3D COF film. The film growth was monitored in real time using a quartz crystal microbalance, showing linear growth with respect to reaction time. The high degree of polymerization was confirmed by chemical analysis and vibrational spectroscopy. Their polycrystalline and anisotropic natures were confirmed with grazing incidence X-ray diffraction. We further expand the scope of the concept by making layered films from COF-300 and its iodinated derivative. Finally, the work presented here will pave the path for multifunctional COF films where concurrent functionalities are embedded in the same crystalline material.

Layered and subregional control strategy based on model-free adaptive iterative learning for laser additive manufacturing process

Improving stability in process and the quality of manufactured parts is critical to laser additive manufacturing (LAM). Developing appropriate control methods is essential for this purpose. Layered control approaches are commonly utilized in current research on LAM process control, with a primary focus on the pattern of layer-by-layer deposition. However, these strategies might neglect the dynamic and evolving characteristics of the process along the scanning direction. Due to the complex nature of the LAM process, such layered control approaches could be inadequate in addressing intra-layer instability, potentially resulting in metallurgical defects. To overcome these limitations, we propose a layered-and-subregional model-free adaptive iterative learning control (LS-MFAILC) method. Considering the cyclic and the layer-by-layer processing principle of LAM, we develop a subregional control strategy and integrate it with a layered control framework. In addition, the model-free adaptive iterative learning control (MFAILC) algorithm is utilized as the controller due to its ability to control complex and time-varying systems with repetitive running characteristics. In the proposed method, each target layer to be printed in process is divided into multiple non-overlapping regions along the scanning direction, and the process parameters for each region are adaptively controlled based on historical information acquired from previous layers during the process. The temperature information of the melt pool is captured and extracted using a thermal imager integrated with the printing system. Experimental results and comparison with the layered control approach demonstrate the effectiveness and superiority of our method.

A fuzzy-based cascade ensemble model for improving extreme wind speeds prediction

A novel fuzzy-based cascade ensemble of regression models is proposed to address a problem of extreme wind speed events forecasting, using data from atmospheric reanalysis models. Although this problem has been mostly explored in the context of classification tasks, the innovation of this paper arises from tackling a continuous predictive domain, aiming at providing an accurate estimation of the extreme wind speed values. The proposed layered framework involves a successive partition of the training data into fuzzy-soft clusters according to the target variable value, and further training a specific regression model within each designated cluster, so that each model can analyze a particular part of the target domain. Finally, predictions made by individual models are integrated into a fuzzy-based ensemble, where a pertinence value is designated to each model based on the previous layer’s prediction, and on the defined membership functions for each cluster. A Differential Evolution (DE) optimization algorithm is adopted to find the optimal way to perform data partitioning. Fast training randomized neural networks methods are used as final regression schemes. The performance of the proposed methodology has been assessed by comparison against state-of-the-art methods in real data from three wind farms in Spain.

Identity frame at metaphor layer as the driving force for nuclear strategy: The US nuclear strategy during the cold war

The formation of a nation’s nuclear strategy is understood from a typical structuralist perspective of security strategy studies and international politics. This makes it difficult to not only derive new strategic alternatives but also anticipate what nuclear strategy patterns can be developed in the future. This study aims to deepen our understanding of nuclear strategy formation through causal layered analysis and to present new strategic alternatives to existing discourse. Therefore, this study examines the driving force that influences nuclear strategy formation and changes in implicit cognitive layers. The cognitive variables of identity are derived, and the causal layered analysis framework is used to explain how identity factors give meaning to concepts regarding national security and how the concepts are linked to strategic initiatives. Furthermore, this study assumes that nuclear strategy arises from interactions among the key frame variables in the cognitive layers. The US nuclear strategy cases are examined using this theoretical framework to understand how their interactions have shaped security concepts and been reflected in the nuclear strategy discourse. This study derives propositions that the ingroup definition of identity frames affects nuclear strategy as a driving force and that interpreting the explicit layers’ realities by the implicit frames affects the formation of security concepts and the direction of nuclear strategy.

Selective Layered Blockchain Framework for Privacy-preserving Data Management in Low-latency Mobile Networks

<p>With the gradual development of Fourth Industrial Revolution technologies, such as artificial intelligence, the Internet of Things, and big data, and the considerable amount of data in mobile networks, low-latency communication and security management are becoming crucial. Blockchain is a data-distributed processing technology that tracks data records to support secure electronic money transactions and data security management in a peer-to-peer environment without the need of a central trusted authority. The data uploaded to the blockchain-shared ledger are immutable, making tracking integrity preservation facile. However, blockchain technology is limited because it is challenging to utilize in the industry owing to its inability to correct data, even when inaccurate data are uploaded. Accordingly, research on blockchain mechanisms that consider privacy-preserving data management is required to commercialize blockchain technology. Previously, off-chain, blacklist, and hard-fork methods have been proposed; however, their application is challenging or impractical. Therefore, to protect privacy, we propose a layered blockchain mechanism that can correct data by adding a buffer blockchain. We evaluated the latency, security, and space complexity of layered blockchains. The security and security-to-latency ratio for data management of the selective layered blockchain is 2.2 and 11.3 times higher than the conventional blockchains, respectively. The proposed selective layered blockchain is expected to promote the commercialization of blockchain technologies in various industries by protecting user privacy.</p> <p> </p>

Eu(III) and Am(III) adsorption on aluminum (hydr)oxide minerals: surface complexation modeling

Americium is a highly radioactive actinide element found in used nuclear fuel. Its adsorption on aluminum (hydr)oxide minerals is important to study for at least two reasons: (i) aluminum (hydr)oxide minerals are ubiquitous in the subsurface environment and (ii) bentonite clays, which are proposed engineered barriers for the geologic disposal of used nuclear fuel, have the same ≡AlOH sites as aluminum (hydr)oxide minerals. Surface complexation modeling is widely used to interpret the adsorption behavior of heavy metals on mineral surfaces. While americium sorption is understudied, multiple adsorption studies for europium, a chemical analog, are available. In this study we compiled data describing Eu(III) adsorption on three aluminum (hydr)oxide minerals—corundum (α-Al2O3), γ-alumina (γ-Al2O3) and gibbsite (γ-Al(OH)3)—and developed surface complexation models for Eu(III) adsorption on these minerals by employing diffuse double layer (DDL) and charge distribution multisite complexation (CD-MUSIC) electrostatic frameworks. We also developed surface complexation models for Am(III) adsorption on corundum (α-Al2O3) and γ-alumina (γ-Al2O3) by employing a limited number of Am(III) adsorption data sourced from literature. For corundum and γ-alumina, two different adsorbed Eu(III) species, one each for strong and weak sites, were found to be important regardless of which electrostatic framework was used. The formation constant of the weak site species was almost 10,000 times weaker than the formation constant for the corresponding strong site species. For gibbsite, two different adsorbed Eu(III) species formed on the single available site type and were important for the DDL model, whereas the best-fit CD-MUSIC model for Eu(III)-gibbsite system required only one Eu(III) surface species. The Am(III)-corundum model based on the CD-MUSIC framework had the same set of surface species as the Eu(III)-corundum model. However, the log K values of the surface reactions were different. The best-fit Am(III)-corundum model based on the DDL framework had only one site type. Both the CD-MUSIC and the DDL model developed for Am(III)-γ-alumina system only comprised of one site type and the formation constant of the corresponding surface species was ~ 500 times stronger and ~ 700 times weaker than the corresponding Eu(III) species on the weak and the strong sites, respectively. The CD-MUSIC model for corundum and both the DDL and the CD-MUSIC models for γ-alumina predicted the Am(III) adsorption data very well, whereas the DDL model for corundum overpredicted the Am(III) adsorption data. The root mean square of errors of the DDL and CD-MUSIC models developed in this study were smaller than those of two previously-published models describing Am(III)-γ-alumina system, indicating the better predictive capacity of our models. Overall, our results suggest that using Eu(III) as an analog for Am(III) is practical approach for predicting Am(III) adsorption onto well-characterized minerals.Graphical

Correction: Facile synthesis of interconnected layered porous carbon framework for high-performance supercapacitors

Correction: Facile synthesis of interconnected layered porous carbon framework for high-performance supercapacitors

Coordination Assembly of Tetrahedral Ti4(embonate)6 Cages with Alkaline-Earth Metal Ions

Recently, the tetrahedral Ti4L6 cage (L = embonate) has been applied as the starting material to realize coordination assembly with transition and rare-earth ornoble metal ions through a two-step reaction. In this work, by employing the Ti4L6 cages to assemble with alkaline-earth metal ions (such as Mg2+, Ca2+ and Ba2+) under different solvothermal conditions, a series of Ti4L6-based structures from simple cages to 1D chain, 2D layer and 3D framework have been synthesized and structurally characterized. In addition, thermal stability, phase purity, UV-vis absorption spectrum, the fluorescent and third-order nonlinear-optical properties are also investigated.

ViTaLS—A Novel Link-Layer Scheduling Framework for Tactile Internet Over Wi-Fi

The pioneering field of Tactile Internet (TI) will enable the transfer of human skills over long distances through haptic feedback. Realizing this demands a roundtrip latency of sub-5 ms. In this work, we investigate the capability of Wi-Fi 6 and existing TI scheduling/multiplexing schemes in meeting this stringent latency constraint. Taking the concrete example of the state-of-the-art Video-Haptic multiplexer (VH-multiplexer), we highlight the pitfalls of relying on the existing Wi-Fi 6 systems for TI communication. To circumvent this, we propose Video-Tactile Latency Scheduler (ViTaLS) -a novel link layer framework for tuning the video-tactile frame transmissions to suit their heterogeneous QoS requirements. We present a mathematical model to characterize the packet transmission duration of Vi-TaLS. Using a custom simulator, we validate our model and measure the objective performance improvement of ViTaLS over VH-multiplexer. We also present ViTaLS-optimal -a variant of ViTaLS, for further reducing the tactile latency. Objectively, we show that ViTaLS-optimal yields a latency improvement of up to 82%. Based on experiments conducted on a real TI testbed, we subjectively demonstrate that ViTaLS-optimal outperforms the VH-multiplexer.

Fluorescence Emission Is Highly Structure-Dependent in Hybrid Lead Halides.

Hybrid lead halide perovskites have received extensive scientific attention owing to their great potential in the field of fluorescent displays and light-emitting diodes. Currently, most luminescent materials contain functional molecular and rare-earth metal ion parts. However, the mechanism of photoluminescence property in two-dimensional hybrid lead halide perovskites with different layered inorganic skeletons has been reported rarely. To better understand the effect of an inorganic skeleton on the fluorescence property, here, we report three organic-inorganic hybrid materials with different layered inorganic frameworks: (MACH)2·PbBr4 (Prv-1, MACH = cyclohexylmethylammonium), (2-MPQ)·PbBr4 (Prv-2, 2-MPQ = 2-methylpiperazinium), and (TMBA)4·Pb3Br10 (Prv-3, TMBA = N'N'N'-trimethylbenzylammonium). Among them, Prv-1 is a (100)-oriented perovskite, Prv-2 belongs to the (110)-oriented perovskite, and the inorganic framework of Prv-3 possesses [Pb3Br10] units. Interestingly, Prv-1 has a strong blue-violet fluorescence emission, while the luminescence effect of Prv-2 is very weak; notably, Prv-3 emits a charming bright-orange light. Meanwhile, results of theoretical computational studies also reveal that the electronic structure of all three compounds is highly dependent on structurally distorted [PbBr6] octahedra, and the frontier molecular orbital (FMO) analysis further suggests that HOMO and LUMO of Prv-3 are contributed by inorganic and organic components, respectively. In addition, all three materials belong to direct band gap semiconductors, and the band gaps are 2.79, 2.97, and 2.76 eV, respectively. Significantly, there are obvious differences in conduction bands. Based on the above analysis, the photoluminescence mechanism of three hybrid materials is explained from the electronic levels. Consequentially, this work might provide practical strategies and perspectives for exploring novel structure-related properties.

A scoping review of the use of lab streaming layer framework in virtual and augmented reality research

A scoping review of the use of lab streaming layer framework in virtual and augmented reality research

Engineering Natural Layered Framework for Low and Anisotropic Thermal Conductivity

AbstractThe development of nano–manufacture technology in the twenty‐first century has paved the way for artificial nanostructure constructions like man–made superlattices, providing historical breakthroughs in thermal physics and thermoelectrics by the modulation of phonons. Still, high–performance thermal insulators haven't come into operation due to the arduousness, costing and unscalability of artificiality. Herein, intentional engineering on a so–called ‘natural superlattice’ with alternating PbSe– and Bi2Se3–layer crystal structure is brought forth to recreate the mechanism of artificial superlattices and boost phonon localization. The thermal conductivity notably shows a direction–specific reduction, leading to minimum approaching and enhanced anisotropy. The modification of the natural framework and its effects have been supported by various transport and structure studies. This work sets a generalizable example for natural layered material engineering that bridges between the inflexible, changeless but self–assembled natural layered compounds, and the highly efficient, delicately tailored but unscalable artificial superlattice complexes. The methodology promises new horizons for practicable thermal management.

An Adaptive Layered Clustering Framework with Improved Genetic Algorithm for Solving Large-Scale Traveling Salesman Problems

Traveling salesman problems (TSPs) are well-known combinatorial optimization problems, and most existing algorithms are challenging for solving TSPs when their scale is large. To improve the efficiency of solving large-scale TSPs, this work presents a novel adaptive layered clustering framework with improved genetic algorithm (ALC_IGA). The primary idea behind ALC_IGA is to break down a large-scale problem into a series of small-scale problems. First, the k-means and improved genetic algorithm are used to segment the large-scale TSPs layer by layer and generate the initial solution. Then, the developed two phases simplified 2-opt algorithm is applied to further improve the quality of the initial solution. The analysis reveals that the computational complexity of the ALC_IGA is between O(nlogn) and O(n2). The results of numerical experiments on various TSP instances indicate that, in most situations, the ALC_IGA surpasses the compared two-layered and three-layered algorithms in convergence speed, stability, and solution quality. Specifically, with parallelization, the ALC_IGA can solve instances with 2×105 nodes within 0.15 h, 1.4×106 nodes within 1 h, and 2×106 nodes in three dimensions within 1.5 h.

Layered 2D MOF nanosheets grown on CNTs substrates for efficient nitrite sensing

In this work, we report a ligand-deficient layered cerium-based metal-organic framework (MOF) nanosheets grown on carbon nanotube (CNT) substrates and its application in electrochemical sensors. The construction of layered MOF nanosheet materials is based on CNTs as the backbone and relies on the low ligand-metal ratios which is controlled by the loaded organic ligands on the surface of CNTs, providing a new approach for the application of 2D MOFs in the field of electrochemical sensing. The obtained 2D MOFs possess unique layered structure and hierarchical connectivity channels, providing highly efficient and stable pathways for electron, ion, and mass transport. The synthesized layered 2D CNTs@Ce-MOF nanosheet hybrid material uses Ce as the center ion and electrocatalytic active material for nitrite sensing. This material exhibits excellent nitrite detection performance within two wider linear ranges of 0.65–3.25 μM and 3.25–7000 μM with the sensitivity of 87.65 ± 0.6 μA·μM−1·cm2 and 0.35 ± 0.03 μA·μM−1·cm−2, respectively. The detection limit is estimated to be 0.12 μM according to signal to noise ratio (S/N) = 3. As the result, the prepared sensors possess advantages in aspects of reproducibility, stability, selectivity and responsiveness in comparison to the reported ones.

Exploring Spin-Phonon Coupling in Magnetic 2D Metal-Organic Frameworks

Layered magnetic metal-organic frameworks (MOFs) are an emerging class of materials that can combine the advantages of both MOFs and 2D magnetic crystals. The recent discovery of large coercivity and long-range magnetic ordering up to 515 K in a layered MOF of general formula MCl2(pyz)2 (M = transition metal, pyz = pyrazine) offers an exciting versatile platform to achieve high-TC magnetism at the 2D limit. In this work, we investigate the exfoliation feasibility down to the monolayer of VCl2(pyz)2 and CrCl2(pyz)2 by means of first-principles calculations. We explore their structural, electronic, magnetic and vibrational properties, as well as the effect of halide substitution. Then, we provide a full analysis of the spin-phonon coupling (SPC) in both 2D derivatives. Our calculations reveal a low SPC and thermal evolution of the magnetic exchange interactions and single-ion anisotropy mainly governed by low-frequency phonon modes. Finally, we provide chemical insights to improve the performance of these magnetic 2D MOFs based on the effective manipulation of the phonon modes that can present a major impact on their magnetic properties.

Rapid elimination of antibiotic gemifloxacin mesylate and methylene blue over Pt nanoparticles dispersed chitosan/g-C3N4 ternary visible light photocatalyst.

Appropriate material selection and proper understanding of bandgap modification are key factors for the development of efficient photocatalysts. Herein, we developed an efficient, well-organized visible light oriented photocatalyst based on g-C3N4 in association with polymeric network of chitosan (CTSN) and platinum (Pt) nanoparticles utilizing a straightforward chemical approach. Modern techniques like XRD, XPS, TEM, FESEM, UV-Vis, and FTIR spectroscopy were exploited for characterization of synthesized materials. XRD results confirmed the involvement of α-polymorphic form of CTSN in graphitic carbon nitride. XPS investigation confirmed the establishment of trio photocatalytic structure among Pt, CTSN, and g-C3N4. TEM examination showed that the synthesized g-C3N4 possesses fine fluffy sheets like structure (100 to 500nm in size) intermingled with a dense layered framework of CTSN with good dispersion of Pt nanoparticles on g-C3N4 and CTSN composite structure. The bandgap energies for g-C3N4, CTSN/g-C3N4, and Pt@ CTSN/g-C3N4 photocatalysts were found to be 2.94, 2.73, and 2.72eV, respectively. The photodegradation skills of each created structure have been examined on antibiotic gemifloxacin mesylate and methylene blue (MB) dye. The newly developed Pt@CTSN/g-C3N4 ternary photocatalyst was found to be efficacious for the elimination of gemifloxacin mesylate (93.3%) in 25min and MB (95.2%) just in 18min under visible light. Designed Pt@CTSN/g-C3N4 ternary photocatalytic framework exhibited ⁓ 2.20 times more effective than bare g-C3N4 for the destruction of antibiotic drug. This study provides a simple route towards the designing of rapid, effective visible light oriented photocatalyts for the existing environmental issues.

Progress and Prospect of Zn Anode Modification in Aqueous Zinc-Ion Batteries: Experimental and Theoretical Aspects.

Aqueous zinc-ion batteries (AZIBs), the favorite of next-generation energy storage devices, are popular among researchers owing to their environmental friendliness, low cost, and safety. However, AZIBs still face problems of low cathode capacity, fast attenuation, slow ion migration rate, and irregular dendrite growth on anodes. In recent years, many researchers have focused on Zn anode modification to restrain dendrite growth. This review introduces the energy storage mechanism and current challenges of AZIBs, and then some modifying strategies for zinc anodes are elucidated from the perspectives of experiments and theoretical calculations. From the experimental point of view, the modification strategy is mainly to construct a dense artificial interface layer or porous framework on the anode surface, with some research teams directly using zinc alloys as anodes. On the other hand, theoretical research is mainly based on adsorption energy, differential charge density, and molecular dynamics. Finally, this paper summarizes the research progress on AZIBs and puts forward some prospects.

A developed distributed ledger technology architectural layer framework for decentralized governance implementation in virtual enterprise

Distributed Ledger technology (DLT) has recently emerged as a disruptive system with a wide range of applicability, with prospect to improve societal interactions at large. In virtual enterprise (VE) context researchers and practitioners have started to investigate the deployment of DLT to automate the processing of data and implementation of decisions to support the provision of digital services. Although academic interest in this domain is growing, a practical analysis of DLT from a governance perspective is still lacking to date. Accordingly, this study aims to fill this gap and provide implications related to decentralized governance of DLT. This article develops an architectural governance-by-design framework that defines the governance of DLT as a combination of architectural layers and governance of DLT dimensions. Design science is employed, and IOTA tangle an open-source DLT which employs a decentralized asynchronous network is deployed to evaluate the applicability of the developed architectural governance-by-design framework through qualitative interviews and literature inquiry. The findings confirm the developed architectural governance-by-design framework and offer a shared discussion and insight surrounding the topic of governance of DLT. The findings also identify limitations associated with governance of DLT solutions and proposes policy recommendations to be used as guidelines for practitioners to improve the adoption of DLT to accelerate VE digitalization.

A Novel Blockchain and Internet of Things-Based Food Traceability System for Smart Cities.

Rapid urbanization has recently caused serious problems for cities all around the world. Smart cities have drawn much interest from researchers in the present research paradigm to manage the expanding urban population. Frameworks for smart cities are planned and implemented using platforms based on blockchain and the Internet of Things (BIOT). Smart cities may use the BIoT platform to provide improved transportation, food traceability, and healthcare services. Food safety is one of the sectors where less research has been done than the others. The importance of food safety is now more widely recognized, making it essential to improve the traceability and transparency of the food supply chain. In this paper, a novel BIOT-based layered framework using EOSIO has been proposed for effective food traceability. The proposed system first identifies the suitable traceability units to provide better transparency and traceability and then defines and implements a layered architecture using Ethereum and EOSIO blockchain platforms. The performance of the proposed EOSIO-based model is evaluated using the practicality of the consensus algorithm, block production rate, throughput, and block confirmation time. The proposed traceability system attains a block production rate of 0.5s and a block confirmation time of 1s, which is much lower than the Ethereum-based traceability system. Hence, from the experimental evidence, the superiority of the proposed EOSIO-based food traceability can be observed.

Microaffirmations: Small Gestures Toward Equity and Advocacy

The practice of using microaffirmations enables positive outcomes through small acts of active listening that encourage feelings of inclusion and shared cultural intimacy. Microaffirmations can be intersectional and are beneficial to a wide range of populations, including people of color, LGBTQIA + individuals, and people with disabilities. School counselors are trained and positioned to have knowledge of practical, evidence-based interventions to help school communities process the negative impacts of microaggressions and daily racism. This article describes the benefits of implementing microaffirmations in school settings and proposes a layered framework for implementation within school communities. We discuss recommendations for training faculty and staff on using microaffirmations and implications for school counselor practice. We also address the importance of using evidence-based school counseling practices as part of framework implementation.