Lattice Framework Research Articles

Hexagonal-phase NaREF4 upconversion nanocrystals: the matter of crystal structure.

The hexagonal-phase (β) of NaREF4 upconversion nanocrystals (RE = rare earth elements) has been widely employed because of the outstanding luminescence performance, yet less is known about the essence of this superior property. The current understanding of this issue is raised from the advantage of weak electron-vibration interactions in fluoride systems, while the interpretability of this statement is controversial and contradictory results are commonly reported. One feasible way to solve this puzzle is from the aspect of "structure-property" relationship, yet even after decades of investigation, the structural details of β-NaREF4 are still under debate. Herein, the reported results relevant to this topic are reviewed, and the conflicting viewpoints are summarized. The similarities and differences between different lattice templates are assessed, and the reasons underlying the divergence are analysed. Based on these discussions, it is realized that the crystal structure of β-NaREF4 should be more reliably depicted as one flexible lattice framework with complex characteristics, and the structural disorder induced by atom displacements in the lattice is probably the key to supporting the superior luminescence properties of β-NaREF4 nanocrystals.

A critical review: Effect of the concentration of carbon nanotubes (CNT) on mechanical characteristics of aluminium metal matrix composites: Part 2

Carbon Nanotubes (CNT) have novel attributes that make them an appropriate strengthening operator in Aluminum (Al) Metal Matrix framework. Strengthening with CNT prompts increment in quality without significant increment in weight. The mechanical and thermal property upgrades accomplished by expansion of CNT in Aluminum metal lattice frameworks. Hence this paper reviews the effect of concentration of CNT on stress strain curve behavior, elastic modulus, hardness, co-efficient of thermal expansion (CTE), creep & damping characteristics of Al – CNT composites.

Al-doping enables high stability of single-crystalline LiNi0.7Co0.1Mn0.2O2 lithium-ion cathodes at high voltage.

LiNi0.7Co0.1Mn0.2O2 (NCM) is a kind of promising cathode material for lithium ion batteries because of its high capacities. However, the further commercialization of this material has been seriously hindered by the unstable structure at a deep de-lithiation state. Herein, it is identified that this drawback can be diminished by Al-doping, which is inherently stable in the lattice framework to restrain the structural collapse of LiNi0.7Co0.1Mn0.2O2 at a high cut-off voltage (4.4 V). As expected, the Al-doped NCM (NCM–0.2Al) material obtains the highest reversible capacity and capacity retention (144.69 mA h g−1, 80.26%) after 90 cycles at 1C. The excellent performance demonstrates that Al-doping can effectively enhance the Li+-ion diffusion kinetic and structural stability of NCM, providing a feasible strategy for the further industrialization of Ni-rich materials.

Deep Proton Insertion Assisted by Oxygen Vacancies for Long‐Term Memory in VO2 Synaptic Transistor

AbstractReversible phase transformation of correlated oxides by field‐driven ionic process present opportunity to efficiently transduce between ionic transfer and electrical currents in insertion‐based reconfigurable transistors. However, the switching rate of insertion transistors is fundamentally limited by the slow rate of ionic insertion into the lattices of correlated oxides. Here, it is demonstrated that preformed oxygen vacancies in VO2−δ lattices strongly accelerate proton insertion by low gate voltage in synaptic transistors. As the degree of oxygen deficiency δ increases in VO2−δ transistors, the steepness of phase transformation and transconductance increase during the voltage sweep at the expense of the channel current modulation. Theoretical and experimental analyses reveal that the accelerated of H+ kinetics in the VO2−δ lattice occurs because immobile oxygen vacancies reduce the energy barrier to H+ migration. In an electronic synapse, this facile H+ migration in VO2−δ lattices renders “inscribed” memory by positioning the H+ neurotransmitter far from the electrolyte/VO2−δ interface. This discovery suggests a strategy to improve the learning and memory processes of artificial synaptic devices by controlling the density of intrinsic defects in the lattice framework to achieve efficient ion exchange.

Low-Order Method for Prediction of Separation and Stall on Unswept Wings

A low-order method is presented for aerodynamic prediction of wings operating at near-stall and post-stall flight conditions. The method is intended for use in design, modeling, and simulation. In this method, the flow separation due to stall is modeled in a vortex lattice framework as an effective reduction in the camber, or “decambering.” For each section of the wing, a parabolic decambering flap, hinged at the separation location of the section, is calculated through iteration to ensure that the lift and moment coefficients of the section match with the values from the two-dimensional viscous input curves for the effective angle of attack of the section. As an improvement from earlier low-order methods, this method also predicts the separation pattern on the wing. Results from the method, presented for unswept wings having various airfoils, aspect ratios, taper ratios, and small, quasi-steady roll rates, are shown to agree well with experimental results in the literature, and computational solutions obtained as part of the current work.

LiMnO2 cathode stabilized by interfacial orbital ordering for sustainable lithium-ion batteries

Global lithium-ion battery deployments stand poised to grow substantially in the coming years, but it will be necessary to include sustainability considerations in the design of electrode materials. The current cathode chemistry relies heavily on cobalt, which, due to its scarcity and the environmental abuse and violation of human rights during its mining, must be replaced by abundant and environmentally friendly elements such as redox-active manganese. LiMnO2 is a strong contender for sustainable cathodes but cycles poorly because the Jahn–Teller distorted Mn3+ ions destabilize the lattice framework. Here, we report a LiMnO2 cathode design with interwoven spinel and layered domains. At the interface between these two domains, the Mn dz2 orbitals are oriented perpendicular to each other, giving rise to interfacial orbital ordering, which suppresses the otherwise cooperative Jahn–Teller distortion and Mn dissolution. As a result, the heterostructured cathode delivers enhanced structural and electrochemical cycling stability. This work provides a new strategy for interface engineering, possibly stimulating more research on Mn-rich cathode materials for sustainable lithium-ion batteries. The field of battery chemistry must embrace abundant elements such as Mn for improved sustainability. Here the authors engineer the orientation of Mn 3d orbitals, resulting in excellent performance in LiMnO2 cathodes.

Dissolving Vanadium into Titanium Nitride Lattice Framework for Rational Polysulfide Regulation in Li–S Batteries

AbstractRational regulation of host–guest interactive chemistry is of great significance but has not yet effectively been applied in lithium–sulfur (Li–S) batteries. Herein, a unique titanium vanadium nitride (TVN) solid solution fabric is developed as an ideal platform for fine structure modulation towards efficient and durable sulfur electrochemistry. The dissolution of V into the TiN lattice framework is shown to subtly tailor the coordinative and electronic structures of Ti and V, tuning their respective chemical affinity to sulfur species. Consequently, the optimized Ti–V interplay renders the highest overall polysulfide adsorpabiltiy, and contributes to strong sulfur immobilization and fast reaction kinetics. The resultant Li–S cells realize an outstanding cyclability with high capacity retention of 97.7% after 400 cycles. Moreover, reversible areal capacity over 6.11 mAh cm−2 can be sustained under a high sulfur loading of 6.0 mg cm−2 and a limited electrolyte concentration of 6.5 mL g−1. This work provides a novel strategic perspective for the rational regulation of fine structure towards superior Li–S batteries and beyond.

Amorphous NaVOPO 4 as a High-Rate and Ultrastable Cathode Material for Sodium-Ion Batteries

The low cost and profusion of sodium resources make sodium-ion batteries (SIBs) a potential alternative to lithium-ion batteries for grid-scale energy storage applications. However, the use of conv...

Room temperature fluoride ion conductivity in defective β-KSb1-δF4-3δ polycrystals

For a room temperature operation of fluoride ion secondary batteries, it is strongly demanded for a development of fast fluoride ion conductors. Potassium tetrafluoroantimonate (KSbF4) is an air stable crystalline F− ion conductor that can be synthesized by a liquid phase method. Taking account for the effects of lattice defects in ion conductive crystals, we elucidate and propose that a heat treatment just below the melting temperature (550 K) introduces significant amounts of lattice defects in β-KSb1-δF4-3δ (δ = 0.54), which drastically increases the F− ion conductivity. The F− ion conductivity of the material is now reached into the order of 10−4 S cm−1 at room temperature and 10−2 S cm−1 at 420 K, which are two orders of magnitude higher than those in the sintering at 490 K. Spectroscopic analyses revealed that, during the heat treatment, SbF3 evaporates from the bulk with retaining the lattice framework, suggesting that a number of vacancies at Sb (54%) and F (41%) atomic sites remarkably promote the F− ion diffusivity in β-KSb1-δF4-3δ polycrystals. The present heat treatment method just below the melting point should be applicable to improve the F− ion conductivity of complex salt fluorides.

Coupling of organic cation and inorganic lattice in methylammonium lead halide perovskites: Insights into a pressure-induced isostructural phase transition

Organic-inorganic hybrid metal-halide perovskite (OIHP) materials provide a tunable platform for engineering their optoelectronic properties. Although several high-pressure studies have been conducted from the OIHP family of single crystals and films, the exact nature of the dynamic coupling of the $\mathrm{C}{\mathrm{H}}_{3}\mathrm{N}{\mathrm{H}}_{3}$ (MA) cation with the octahedral lattice framework and the mechanisms responsible for the structural phase transformation under pressure are not well captured. By combined photoluminescence (PL), synchrotron-based x-ray diffraction, and Raman-scattering studies as a function of pressure from methylammonium lead bromide ($\mathrm{M}\mathrm{A}\mathrm{Pb}{\mathrm{Br}}_{3}$), we shed light on an isostructural phase transition due to the coupling of the MA cation and the $\mathrm{Pb}{\mathrm{Br}}_{6}$ lattice through hydrogen bonding. The sharp discontinuities at $\ensuremath{\sim}$ 1 GPa and $\ensuremath{\sim}$ 3 GPa in the PL peak positions correlate with the structural changes observed in high-pressure XRD and Raman-scattering studies. The electronic band edge as a function of pressure is calculated within density-functional theory. The PL peak position, intensity and width of the excitonic peak show significant changes at 2 GPa, which corroborate the changes observed in high-pressure Raman-scattering studies. The frequencies of the lattice modes and the C--H/N--H bending and stretching modes of the MA cation show anomalous changes and other nuances at 2 GPa. The suppression of rotational and orientational disorder of the organic moiety is initiated at 2 GPa and the ordering is completed by 3.0 GPa, leading to an order-disorder type cubic II ($Im\overline{3}$) to orthorhombic ($Pnma$) phase transition. Along with the revelation of an isostructural transformation at 2 GPa, this paper highlights the impact of molecular vibrations on the electronic properties of $\mathrm{M}\mathrm{A}\mathrm{Pb}{\mathrm{Br}}_{3}$ under pressure.

Applying set optimization to weak efficiency

Set-valued extensions of vector-valued functions are used to investigate the relations between weak efficiency and variational inequalities (both Stampacchia and Minty type) which allows to apply the complete lattice framework from set optimization. Since the seminal work of Giannessi, it has been a challenge to generalize scalar results to the vector case. In this effort, some notions of generalized derivatives for vector-valued functions have been introduced, either in the form of set-valued functions or introducing appropriate notions of infinite elements in vector spaces. Switching the focus to set optimization in conlinear spaces, we propose a Dini-type derivative, that keeps the same set-valued form of the optimization problem.

Complementary Resistive Switching and Synaptic-Like Memory Behavior in an Epitaxial SrFeO2.5 Thin Film through Oriented Oxygen-Vacancy Channels.

Oxygen-vacancy-ordered brownmillerite oxides offer a reversible topotactic phase transition by significantly varying the oxygen stoichiometry of the material without losing its lattice framework. This phase transition leads to substantial changes in the physical and chemical properties of brownmillerite oxides, including electrical and ion conductivity, magnetic state, and oxygen diffusivity. In this study, the variations in the resistive switching mode of the epitaxial brownmillerite SrFeO2.5 thin film in the device were studied by systematically controlling the oxygen concentration, which could be varied by changing the compliance current during the first electroforming step. Depending on the compliance current, the SrFeO2.5 devices exhibited either low-power bipolar resistive switching or complementary resistive switching behaviors. A physical model based on the internal redistribution of oxygen ions between the interfaces with the top and the bottom electrodes was developed to explain the complementary resistive switching behavior. This model was experimentally validated using impedance spectroscopy. Finally, the gradual conductance variation in the brownmillerite SrFeO2.5 thin films was exploited to realize synaptic learning.

High-order lattice Boltzmann framework and its adaptive mesh refinement in the neutron transport SP3 solutions

Due to the relatively simpler form and the higher accuracy, the neutron transport SP3 equation is regarded as a compromising governing equation between the neutron transport and diffusion equations, and its numerical calculation is considered to be a promising alternative technique for the advanced nuclear reactor physics computation. To improve the accuracy of the SP3 calculation without increasing the calculation complexity, this work establishes a high-order lattice Boltzmann method (LBM) framework to solve the multi-group neutron transport SP3 equations with both the uniform mesh and the adaptive non-uniform mesh configurations. The coupling double-distribution function (DDF) based LBM model is proposed for the SP3 calculation, and the relationship between the high-order LBM equations and the macroscopic SP3 equations is established via the high-order Chapman-Enskog expansion. To promote the computational efficiency without reducing the computational accuracy, the streaming-based block-structured adaptive-mesh-refinement (SSAMR) technique is applied to the proposed high-order LBM for SP3 solving, in which the mesh configuration of SP3 calculation is adaptively adjusted based on the neutron distribution. The simulation results show that the proposed high-order LBM and the SSAMR technique can be used to efficiently reduce the computational cost with higher accuracy, and the SSAMR based mesh configuration can accurately and flexibly capture the areas with steep neutron distribution. For further research, this work can provide a unified LBM numerical framework for solving the multi-scale neutron transport process and some perspectives to the reactor multi-physics calculation.

Effect of tungsten doping on strontium ferrite electrode for symmetrical solid oxide electrochemical cell

Tungsten-doped strontium ferrite (SrFe1-xWxO3-δ, SFW) is prepared and characterized as the electrode materials for symmetrical solid oxide electrochemical cell. X-ray diffraction refinement reveals the symmetrical structure transform from cubic (pm3¯m) for x = 0.1 to tetragonal (I4/m) when x = 0.2. According to the analysis including electrical conductivity, Hydrogen temperature-programmed reduction (H2-TPR), thermal expansion and X-ray photoelectron spectra (XPS), it suggests that the decrease in conductivity, content of Fe2+ and oxygen vacancy concentration with the increase of W content is attributed to the stronger lattice framework. The oxygen vacancy can be dramatically activated around 600 °C. Using SrFe0.8W0.2O3-δ as the electrodes, symmetrical single cells supported on doped ceria electrolytes can achieve acceptable power density (0.19 W cm−2 at 750 °C) and considerable stability. Meanwhile symmetrical cells with La0.9Sr0.1Ga0.8Mg0.2O3-δ (LSGM) electrolyte substrates can achieve 0.75 A cm−2 at 800 °C under the voltage of OCV (open circuit voltage) +0.5 V when it is operated in electrolysis mode. SrFe0.8W0.2O3-δ can gain a considerable stability and electrochemical activity under both oxide and reductive atmospheres. Oxygen vacancy formation energy (Evac) and electron density distribution are computed to verify the enhancement on crystal structure stability by doping W. The Evac critically depends on the distance from the W atom.

Dynamic construction of lattice of cuboids in data warehouse

In the field of Business Intelligence we require quick and efficient analysis of multidimensional data. Data warehouse (DW) and Online analytical processing (OLAP) approaches have been developed for this purpose which represents data in the form of cuboids. Lattice structures have been developed which consists of data cubes or cuboids. In the Lattice framework base cuboid contains all N - dimensions and moving up to the hierarchy we reach to 0 - Dimensional cuboid called apex cuboid. New cuboid may be generated by roll-up through dimension reduction. Dimension of cuboid may be reduced and increase according to business requirement. In this paper an algorithm is proposed for constructing cuboid dynamically. Cuboid are need to select in all ways for materialization purpose. Dynamic construction of cuboid enables materialization in fast and efficient way.

Terahertz Vibrational Motions Mediate Gas Uptake in Organic Clathrates

Clathrates, supramolecular materials that contain guest molecules trapped within a framework of a host lattice, are important in many areas of science and technology. However, despite much research, fundamental questions concerning the mechanism and kinetics associated with the enclathration process remain unanswered. Here, through a combination of terahertz spectroscopy, density functional theory, and molecular dynamics simulations, we demonstrate that the gas-capture process is mediated by a single terahertz vibrational mode and then use this mode to track the uptake of gas. This result provides a critical molecular-level understanding of this key kinetic process in clathrate science.

Discrete softening-damage model for fracture process representation with embedded strong discontinuities

A damage softening model is implemented into a discrete lattice framework with embedded strong discontinuities for the discontinuous representation of fracture. Such a model fits heterogeneous framework and allows capturing the complex fracture mechanisms in quasi-brittle materials under various quasi-static and dynamic loading conditions. Finite element implementation of damage softening constitutive model provides a very powerful computational tool for a description of material degradation processes which happen during monotonic loading, as well as unloading and reloading on the damaged material. In particular, the proposed model can capture the processes such as reduction of material stiffness, crack opening-closing mechanisms and reloading that follows the inverse of compliance modulus. Numerical examples are performed to demonstrate the effectiveness and robustness of the model fracture capabilities. The two examples deal with quasi-static fracture mechanisms of a heterogeneous material. The fragmentation of a cylinder in dynamics framework subjected to internal pressure and inertial forces is given as well. The plots of all components of internal energy (the dissipated fracture energy, elastic strain and kinetic energy) in dynamic fracture process are provided. The model of this kind can simulate multiple cracks formation, coalescence, propagation and mesh independent results.

Materialized View Selection Using Self-Adaptive Perturbation Operator-Based Particle Swarm Optimization

A data warehouse is a central repository of time-variant and non-volatile data integrated from disparate data sources with the purpose of transforming data to information to support data analysis. Decision support applications access data warehouses to derive information using online analytical processing. The response time of analytical queries against speedily growing size of the data warehouse is substantially large. View materialization is an effective approach to decrease the response time for analytical queries and expedite the decision-making process in relational implementations of data warehouses. Selecting a suitable subset of views that deceases the response time of analytical queries and also fit within available storage space for materialization is a crucial research concern in the context of a data warehouse design. This problem, referred to as view selection, is shown to be NP-Hard. Swarm intelligence have been widely and successfully used to solve such problems. In this paper, a discrete variant of particle swarm optimization algorithm, i.e. self-adaptive perturbation operator based particle swarm optimization (SPOPSO), has been adapted to solve the view selection problem. Accordingly, SPOPSO-based view selection algorithm (SPOPSOVSA) is proposed. SPOPSOVSA selects the Top-K views in a multidimensional lattice framework. Further, the proposed algorithm is shown to perform better than the view selection algorithm HRUA.

Design and Analysis of Hybrid Energy Storage System in DC Microgrid

A microgrid is a restricted gathering of power sources and loads that typically work associated with and coordinated with the conventional wide region simultaneous network (macrogrid), as the quantity of DC-creating sustainable power sources is higher when contrasted with air conditioning producing sources, lesser converter units are required. This builds the general proficiency of DC microgrid. A DC small scale lattice framework is utilizing a force organize that empowers the presentation of a lot of sun oriented vitality utilizing circulated photovoltaic age units. This paper manages the plan and execution examination of a DC microgrid with battery-supercapacitor vitality stockpiling framework under factor supercapacitor working voltage. MATLAB 9.4 is utilizing to execute the model and investigation.

Novel cage-like nanoporous ZnO polymorphs with cubic lattice frameworks

Two cage-like nanoporous polymorphs composed of spheroidal cages (ZnO)24 as building block in high symmetrical cubic lattice frameworks are proposed. By using this cluster, instead of atom, as primary building block we studied various scheme of its assembling via bottom up cluster-cluster coalescence schemes. First principles and density-functional tight binding (DFTB+) calculations confirm that the new polymorphs are energetically, dynamically, and mechanically stable. The two newly found nanoporous phases possess an intrinsic wide direct band gap preserving from wurtzite tetragonal-based bonding. The high cubic symmetry wide bandgap semiconductor and its derivatives are expected to have broad applications in photocatalysis, and biomedicine.