Cation Migration-Induced Lattice Oxygen Oxidation in Spinel Oxide for Superior Oxygen Evolution Reaction.

Activating the lattice oxygen can significantly improve the kinetics of oxygen evolution reaction (OER), however, it often results in reduced stability due to the bulk structure degradation. Here, we develop a spinel FeCoCrO with active lattice oxygen by high-throughput methods, achieving high OER activity and stability, superior to the benchmark IrO. The oxide exhibits an ultralow overpotential (190 mV at 10 mA cm) with outstanding stability for over 170 h at 100 mA cm.

Facile preparation of zirconium(IV) immobilized carboxymethyl cellulose/multiwalled carbon nanotubes gels by radiation technique and its selective fluoride removal.

Removal of excessive fluorine in the waterbody environment and the Zn hydrometallurgical system is an urgent problem. In this paper, zirconium oxychloride immobilized carboxymethyl cellulose/carboxymethyl multiwalled carbon nanotube (CMC+MWCCNT-ZrOCl) gels are facilely prepared by radiation technique. The addition of MWCCNT endows the CMC-ZrOCl gel a typical nanotubes/fiber structure, also increase the gel fraction of the gel.

Selective denoising autoencoder for classification of noisy gas mixtures using 2D transition metal dichalcogenides.

Electronic nose (E-nose) technology, which is composed of an array of chemical sensors and pattern recognition, has been widely utilized for the quantitative classification of gas mixtures. However, for the practical use of E-nose in real-industry, advanced algorithms are necessary to handle the noise in sensing data caused by various environmental variables. In order to achieve precise measurements even in real-world environments, it is necessary to denoise and classify noisy sensing data.

Method for Extracting Optical Element Information Using Optical Coherence Tomography.

This study examines the measurement of film thickness, curvature, and defects on the surface or inside of an optical element using a highly accurate and efficient method. This is essential to ensure their quality and performance. Existing methods are unable to simultaneously extract the three types of information: thickness, curvature, and defects.

A Static Sign Language Recognition Method Enhanced with Self-Attention Mechanisms.

For the current wearable devices in the application of cross-diversified user groups, it is common to face the technical difficulties of static sign language recognition accuracy attenuation, weak anti-noise ability, and insufficient system robustness due to the differences in the use of users. This paper proposes a novel static sign language recognition method enhanced by a self-attention mechanism. The key features of sign language gesture classification are highlighted by the weight function, and then the self-attention mechanism is combined to pay more attention to the key features, and the convolutional neural network is used to extract the features and classify them, which realizes the accurate recognition of different types of static sign language under standard gestures and non-standard gestures.

A Non-Contacted Height Measurement Method in Two-Dimensional Space.

Height is an important health parameter employed across domains, including healthcare, aesthetics, and athletics. Numerous non-contact methods for height measurement exist; however, most are limited to assessing height in an upright posture. This study presents a non-contact approach for measuring human height in 2D space across different postures.

Impact of quantum information encoding and metallic leads on dynamical multipartite correlation formation in semiconductor quantum dot arrays.

This study investigates quantum information scrambling (QIS) in a semiconductor quantum dot array. Starting with the 1D Transverse Field Ising model, we expand to more relevant quasi-2D frameworks such as the Heisenberg chain, super-extended Fermi-Hubbard (FH) and hardcore FH models. Assessing their relevance to semiconductor spin-qubit quantum computers, simulations of multipartite correlation formation examine qubit encoding strategies' fidelity, stability, and robustness, revealing trade-offs among these aspects.

Multivariable analysis for predicting lower limb muscular strength with a hip-joint exoskeleton.

Introduction: Advancements in exercise science have highlighted the importance of accurate muscular strength assessments for optimizing performance and preventing injuries.

Methods: We propose a novel approach to measuring muscular strength in young, healthy individuals using Bot Fit, a hip-joint exoskeleton, during resistance exercises. In this study, we introduced performance metrics to evaluate exercise performance during both short and extended durations of three resistance exercises: squats, knee-ups, and reverse lunges.

Bismuth and Fluorine Dual-Doping of Lithium Argyrodite toward High-Performance All-Solid-State Lithium Metal Batteries.

Chlorine-rich lithium argyrodite is considered as a promising superionic conductor electrolyte, but its practical application is limited due to poor air stability and instability toward lithium metal. In this work, BiF is proposed as a multi-functional dopant for electrolyte modification, and the effects on the ionic conductivity, air stability, critical current density, and electrolyte/Li metal interfacial stability are studied. The results show that the doped electrolyte LiPBiSClF (LPBiSClF) still maintains a relatively high ionic conductivity of 5.

Radiation synthesis of high conductivity hydrogel based on tragacanth gum/poly (ionic liquids) for multimodal sensors and supercapacitor.

Natural polymer-based hydrogels have found extensive use in flexible sensing, energy storage, and other fields because of their environmental sustainability and biocompatibility. Nonetheless, numerous challenges persist in the development of hydrogels with outstanding conductivity solely from natural polymers. Herein, we have successfully synthesized hydrogels based on natural polymer (tragacanth gum) and ionic liquids (1-vinyl-3-ethylimidazolium bromide) using a convenient and efficient one-step ionizing radiation method (TG/PIL hydrogels).

Erratum: Functionalized MoS Nanosheets as Multi-Gene Delivery Vehicles for Pancreatic Cancer Therapy: Erratum.

[This corrects the article DOI: 10.7150/ntno.27308.

Dielectric Metasurfaces for Broadband Phase-Contrast Relief-Like Imaging.

The visualization of transparent specimens in traditional light microscopy is impeded by insufficient intrinsic contrast, prompting the development of advanced contrast-enhancement methodologies to transmute minute phase discrepancies into detectable amplitude alterations. While existing methods excel in either phase-contrast imaging (contrast-enhanced image of whole objects) or relief-like imaging (deceptive three-dimensional images), it would be of great significance to seamlessly integrate both capabilities in the same device. Here, we propose a novel metasurface-assisted half-side phase-contrast technique capable of simultaneous phase-contrast and relief-like imaging across the visible spectrum, which is realized by introducing a ±π/2 phase shift to a half-side diffracted wave emitted by the objects.

Morphological analysis of Pd/C nanoparticles using SEM imaging and advanced deep learning.

In this study, we present a comprehensive approach for the morphological analysis of palladium on carbon (Pd/C) nanoparticles utilizing scanning electron microscopy (SEM) imaging and advanced deep learning techniques. A deep learning detection model based on an attention mechanism was implemented to accurately identify and delineate small nanoparticles within unlabeled SEM images. Following detection, a graph-based network was employed to analyze the structural characteristics of the nanoparticles, while density-based spatial clustering of applications with noise was utilized to cluster the detected nanoparticles, identifying meaningful patterns and distributions.

Nuclei instance segmentation using a transformer-based graph convolutional network and contextual information augmentation.

Nucleus instance segmentation is an important task in medical image analysis involving cell-level pathological analysis and is of great significance for many biomedical applications, such as disease diagnosis and drug screening. However, the high-density and tight-contact between cells is a common feature of most cell images, which poses a great technical challenge for nuclei instance segmentation. The latest research focuses on CNN-based methods for nuclei instance segmentation, which typically rely on bounding box regression and non-maximum suppression to locate nuclei.

Improved Thermal Dissipation in a MoS Field-Effect Transistor by Hybrid High- Dielectric Layers.

Transition metal dichalcogenides like MoS have been considered as crucial channel materials beyond silicon to continuously advance transistor scaling down owing to their two-dimensional structure and exceptional electrical properties. However, the undesirable interface morphology and vibrational phonon frequency mismatch between MoS and the dielectric layer induce low thermal boundary conductance, resulting in overheating issues and impeding electrical performance improvement in the MoS field-effect transistors. Here, we employed hybrid high- dielectric layers of AlO/HfO to simultaneously reduce the interfacial thermal resistance and improve device electrical performance.

Crystal Modulation of Mn-Based Layered Oxide toward Long-Enduring Anionic Redox with Fast Kinetics for Sodium-Ion Batteries.

Mn-based layered oxide cathodes for sodium-ion batteries with anionic redox reactions hold great potential for energy storage applications due to their ultra-high capacity and cost effectiveness. However, achieving high capacity requires overcoming challenges such as oxygen-redox failure, sluggish kinetics, and structural degradation. Herein, we employ an innovative crystal modulation strategy, using Mn-based NaLiMnO as a representative cathode material, which shows that the highly exposed {010} active facets enable an enhanced rate capability (119.

Spatially-coded Fourier ptychography: flexible and detachable coded thin films for quantitative phase imaging with uniform phase transfer characteristics.

Fourier ptychography (FP) is an enabling imaging technique that produces high-resolution complex-valued images with extended field coverages. However, when FP images a phase object with any specific spatial frequency, the captured images contain only constant values, rendering the recovery of the corresponding linear phase ramp impossible. This challenge is not unique to FP but also affects other common microscopy techniques -- a rather counterintuitive outcome given their widespread use in phase imaging.

Significantly Enhanced Output Performance of Triboelectric Nanogenerators via Charge Storage and Release Strategy.

As a novel energy harvesting technology, bettering the output performance of triboelectric nanogenerators (TENGs) is vital. Although quite a number methods to increase charge density have been proposed, challenges such as high impedance matching and low output current persist, severely limit the energy utilization efficiency of TENGs. Here, a new power management circuit (PMC) is proposed that through charge storage and release strategy.

Exploring 1T/2H MoS quantum dots modified 2D CoP nanosheets for efficient electrocatalytic hydrogen evolution reaction.

The exploration of multiphases and 0D/2D heterojunction in transition metal phosphides (TMPs) and transition metal sulfides (TMDs) is of major interest for hydrogen evolution reaction (HER). Herein, a novel combination route where 0D mixed-phased 1T/2H molybdenum sulfide quantum dots (MoS QDs) are uniformly anchored on the 2D CoP nanosheets is developed. MoS QDs and CoP were prepared via hydrothermal method and mixed with different ratios (Mo:Co ratios of 2:1, 1:1, and 1:2) and annealed under different temperatures to modulate their application in acidic HER processes.

4D-printed intelligent reflecting surface with improved beam resolution via both phase modulation and space modulation.

Recently, intelligent reflecting surfaces (IRSs) have emerged as potential candidates for overcoming the line-of-sight issue in 5 G/6 G wireless communication. These IRSs can manipulate the direction of reflected beams, enabling efficient beam steering to enhance the performance of wireless communication. Each unit cell (or unit structure) of an IRS commonly consists of electrical elements for phase modulation.

Enhancing the performance of a resonance-based sensor network for soft robots using binary excitation.

Embedded, flexible, multi-sensor sensing networks have shown the potential to provide soft robots with reliable feedback while navigating unstructured environments. Time delay associated with extracting information from these sensing networks and the complexity of constructing them are significant obstacles to their development. This paper presents a novel enhancement to an existing class of embedded sensor network with the potential to overcome these challenges.

A conformable fractional finite difference method for modified mathematical modeling of SAR-CoV-2 (COVID-19) disease.

In this research, the ongoing COVID-19 disease by considering the vaccination strategies into mathematical models is discussed. A modified and comprehensive mathematical model that captures the complex relationships between various population compartments, including susceptible (Sα), exposed (Eα), infected (Uα), quarantined (Qα), vaccinated (Vα), and recovered (Rα) individuals. Using conformable derivatives, a system of equations that precisely captures the complex interconnections inside the COVID-19 transmission.

Distributed leader-following bipartite consensus for one-sided Lipschitz multi-agent systems via dual-terminal event-triggered mechanism.

This article analyses leader-following bipartite consensus for one-sided Lipschitz multi-agent systems by dual-terminal event-triggered output feedback control approach. A distributed observer is designed to estimate unknown system states by employing relative output information at triggering time instants, and then an event-triggered output feedback controller is proposed. Dual-terminal dynamic event-triggered mechanisms are proposed in sensor-observer channel and controller-actuator channel, which can save communication resources to a great extent, and the Zeno behavior is ruled out.