An efficient ontology-based topic-specific article recommendation model for best-fit reviewers

Scientometrics - In general peer review is accredited as the vital and utmost cornerstone of the scientific publishing and research developments. Undeniably, the reviewers play a decisive role in...     

Ultrafast Sodium/Potassium‐Ion Intercalation into Hierarchically Porous Thin Carbon Shells

The large‐scale application of sodium/potassium‐ion batteries is severely limited by the low and slow charge storage dynamics of electrode materials. The crystalline carbons exhibit poor insertion capability of large Na⁺/K⁺ ions, which limits the storage capability of Na/K batteries. Herein, porous S and N co‐doped thin carbon (S/N@C) with shell‐like (shell size ≈20–30 nm, shell wall ≈8–10 nm) morphology for enhanced Na⁺/K⁺ storage is presented. Thanks to the hollow structure and thin shell‐wall, S/N@C exhibits an excellent Na⁺/K⁺ storage capability with fast mass transport at higher current densities, leading to limited compromise over charge storage at high charge/discharge rates. The S/N@C delivers a high reversible capacity of 448 mAh g^‐1 for Na battery, at the current density of 100 mA g^‐1 and maintains a discharge capacity up to 337 mAh g^‐1 at 1000 mA g^‐1. Owing to shortened diffusion pathways, S/N@C delivers an unprecedented discharge capacity of 204 and 169 mAh g^‐1 at extremely high current densities of 16 000 and 32 000 mA g^‐1, respectively, with excellent reversible capacity for 4500 cycles. Moreover, S/N@C exhibits high K⁺ storage capability (320 mAh g^‐1 at current density of 50 mA g^‐1) and excellent cyclic life.     

Autonomous Magnetic Microrobots by Navigating Gates for Multiple Biomolecules Delivery

The precise delivery of biofunctionalized matters is of great interest from the fundamental and applied viewpoints. In spite of significant progress achieved during the last decade, a parallel and automated isolation and manipulation of rare analyte, and their simultaneous on‐chip separation and trapping, still remain challenging. Here, a universal micromagnet junction for self‐navigating gates of microrobotic particles to deliver the biomolecules to specific sites using a remote magnetic field is described. In the proposed concept, the nonmagnetic gap between the lithographically defined donor and acceptor micromagnets creates a crucial energy barrier to restrict particle gating. It is shown that by carefully designing the geometry of the junctions, it becomes possible to deliver multiple protein‐functionalized carriers in high resolution, as well as MCF‐7 and THP‐1 cells from the mixture, with high fidelity and trap them in individual apartments. Integration of such junctions with magnetophoretic circuitry elements could lead to novel platforms without retrieving for the synchronous digital manipulation of particles/biomolecules in microfluidic multiplex arrays for next‐generation biochips.     

Flexible Zinc‐Ion Hybrid Fiber Capacitors with Ultrahigh Energy Density and Long Cycling Life for Wearable Electronics

Emerging wearable electronics require flexible energy storage devices with high volumetric energy and power densities. Fiber‐shaped capacitors (FCs) offer high power densities and excellent flexibility but low energy densities. Zn‐ion capacitors have high energy density and other advantages, such as low cost, nontoxicity, reversible Faradaic reaction, and broad operating voltage windows. However, Zn‐ion capacitors have not been applied in wearable electronics due to the use of liquid electrolytes. Here, the first quasisolid‐state Zn‐ion hybrid FC (ZnFC) based on three rationally designed components is demonstrated. First, hydrothermally assembled high surface area and conductive reduced graphene oxide/carbon nanotube composite fibers serve as capacitor‐type positive electrodes. Second, graphite fibers coated with a uniform Zn layer work as battery‐type negative electrodes. Third, a new neutral ZnSO₄‐filled polyacrylic acid hydrogel act as the quasisolid‐state electrolyte, which offers high ionic conductivity and excellent stretchability. The assembled ZnFC delivers a high energy density of 48.5 mWh cm^?3 at a power density of 179.9 mW cm^?3. Further, Zn dendrite formation that commonly happens under high current density is efficiently suppressed on the fiber electrode, leading to superior cycling stability. Multiple ZnFCs are integrated as flexible energy storage units to power wearable devices under different deformation conditions.     

Study of Half-Metallic Ferromagnetism in Be0.75Ti0.25Y (Y = S,Se, and Te) Using Ab Initio Calculations: Potential Candidate for Spintronic Devices

The structural, elastic, electronic, and magnetic properties of Be_0.75Ti_0.25Y (Y = S, Se, and Te) have been investigated to understand their potential applications in spintonic devices. Crystals of BeS, BeSe, and BeTe, individually doped with Ti with a dopant concentration of x = 0.25, have been evaluated by using full-potential linearized augmented plane-wave plus local orbital method within the framework of density functional theory. We employed the Wu–Cohen generalized gradient approximation for optimizing the crystal structure and evaluating elastic properties. In order improve bandgap values and optical parameters, the modified Becke and Johnson (mBJ) potential has been employed. The theoretical investigation of band structure and density of states confirms the half-metallic ferromagnetic nature of these compounds. The elastic constants are calculated by the charpin method which shows that the compounds under consideration are brittle and anisotropic. Moreover, it is noted that tetrahedral crystal field splits the 3d state of Ti into triple degenerate t_2g and double degenerate e_g states. The exchange splitting energies Δ _x (d) and Δ _x (pd) and exchange constants (N ₀ α) and (N ₀ β) are predicted from triple degenerate t_2g states, and negative values of N ₀ β justify that the nature of effective potential is more attractive in spin down case rather than that in the spin up case. We also find the crystal field splitting (ΔE _crystal = E _t2g?E _eg) energy and reduction of the local magnetic moment of Ti from its free space charge value and creation of small local magnetic moments on the non-magnetic Be, S, Se, and Te sites by p–d hybridization.     

Catalase-imprinted Fe<Subscript>3</Subscript>O<Subscript>4</Subscript>/Fe@fibrous SiO<Subscript>2</Subscript>/polydopamine nanoparticles: An integrated nanoplatform of magnetic targeting,magnetic resonance imaging,and dual-mode cancer therapy

Recent advances in the research on the molecular mechanism of cell death and methods for preparation of nanomaterials make the integration of various therapeutic approaches,targeting,and imaging modes into a single nanoscale complex a new trend for the development of future nanotherapeutics.Hence,a novel ellipsoidal composite nanoplatform composed of a magnetic Fe3O4/Fe nanorod core (～120 nm) enwrapped by a catalase (CAT)-imprinted fibrous SiO2/ polydopamine (F-SiO2/PDA) shell with thickness 70 nm was prepared in this work.In vitro experiments showed that the Fe3O4/Fe@F-SiO2/PDA nanoparticles can selectively inhibit the bioactivity of CAT in tumor cells by the molecular imprinting technique.As a result,the H2O2 level in tumor cells was elevated dramatically.At the same time,the Fe3O4/Fe core released Fe ions to catalyze the conversion of H2O2 to ·OH in tumor cells.Eventually,the concentration of ·OH in tumor cells rapidly rose to a lethal level thus triggering apoptosis.Combined with the remarkable near-infrared light (NIR) photothermal effect of the CATimprinted PDA layer,the Fe3O4/Fe@F-SiO2/PDA nanoparticles can effectively kill MCF-7,HeLa,and 293T tumor cells but are not toxic to nontumor cells.Furthermore,these nanoparticles show good capacity for magnetic targeting and suitability for magnetic resonance imaging (MRI).Therefore,the integrated multifunctional nanoplatform opens up new possibilities for high-efficiency visual targeted nonchemo therapy for cancer.     

Data assimilation in large time-varying multidimensional fields

In the physical sciences, e.g., meteorology and oceanography, combining measurements with the dynamics of the underlying models is usually referred to as data assimilation. Data assimilation improves the reconstruction of the image fields of interest. Assimilating data with algorithms like the Kalman-Bucy filter (KBf) is challenging due to their computational cost which for two-dimensional (2-D) fields is of O(I(6)) where I is the linear dimension of the domain. In this paper, we combine the block structure of the underlying dynamical models and the sparseness of the measurements (e.g., satellite scans) to develop four efficient implementations of the KBf that reduce its computational cost to O(I(5)) in the case of the block KBf and the scalar KBf, and to O(I(4)) in the case of the local block KBf (lbKBf) and the local scalar KBf (lsKBf). We illustrate the application of the IbKBf to assimilate altimetry satellite data in a Pacific equatorial basin.     

Self-developing fuzzy expert system: a novel learning approach,fitting for manufacturing domain

The foremost challenge faced by expert systems, for their applicability to real world problems, is their inherent deficiency of dynamism. For an expert system to be more pragmatic and applicable, the whole structure of an expert system—including rule-base, fuzzy sets, and even user-interface—needs to be upgraded continuously. This continuous up gradation demands full-time, repetitive, and cumbersome involvement of knowledge engineers. Machine learning is an answer to this problem, but unfortunately, the solutions that have been provided are limited in scope. For example, most of the researchers put forward techniques of either generating just rules from data, or self-expanding and self-correcting knowledge-base only. The innovative approach presented in this paper is broader in scope. It enhances the efficacy and viability of expert systems to be more capable of coping with dynamic and ever-changing industrial environments. The objective is facilitated by rendering, concurrently, the self-learning, self-correcting, and self-expanding abilities to the expert system, without requiring knowledge engineering skills of the developers. This means that the user needs just to feed data in form of the values of input/output variables and the complete development of expert system is done automatically. The superiority of the proposed expert system, regarding its continuous self-development, has been explained with the help of three examples related to prediction and optimization of milling and welding processes.     

High-feed turning of AISI D2 tool steel using multi-radii tool inserts: Tool life,material removed,and workpiece surface integrity evaluation

Multi-radii tool inserts offer novel configuration that comprises of multiple radii at tool nose. A review of the available literature indicates that there exists a need for experimental investigation on certain key machining characteristics of such tools. This paper reports on tool wear/life, material removed, and workpiece surface roughness when multi-radii mixed alumina TiN coated tool inserts are employed for turning D2 steel. Inserts of three different nose radii (0.40, 0.80, 1.20?mm) at six levels of feed rates (ranging from 0.157 to 0.562?mm/rev) are used. Results show that flank wear is the dominant wear mode with catastrophic tool failure occurring at highest nose radius (1.20?mm) and feed rate (0.562?mm/rev) combination. Also, there is ～59% reduction in tool life accompanied by ～62% increase in quantity of material removed as the feed rate increases from 0.157 to 0.562?mm/rev at maximum nose radius (1.20?mm). Feed rate is found to be statistically significant factor for all three responses considered herein at 95% confidence level. Surface integrity assessment at maximum feed rate reveals presence of a strain hardened layer extending to the depth of 150?µm below the machined surface without any observance of white layer for all the tool conditions and nose radius.