Reduced Thermal Conductivity in SnSe Moiré Superlattices.

Two-dimensional (2D) materials with inherently low thermal conductivity offer significant advantages for thermal management due to constrained phonon transport. The introduction of rotational degrees of freedom in layered 2D materials to form Moiré superlattices enables precise modulation of material properties, including electronic band gaps and phonon scattering mechanisms. While simulations have demonstrated that twisted multilayer Moiré structures can significantly reduce thermal conductivity through enhanced scattering and localized phonon modes, experimental progress has been limited due to challenges in synthesizing multilayer superlattices.

Superpixel guided spectral-spatial feature extraction and weighted feature fusion for hyperspectral image classification with limited training samples.

Deep learning is a double-edged sword. The powerful feature learning ability of deep models can effectively improve classification accuracy. Still, when the training samples for each class are limited, it will not only face the problem of overfitting but also significantly affect the classification result.

Overweight and glucose/lipid metabolism abnormality associated with SSRIs: a pharmacovigilance study based on the FDA adverse event reporting system.

Background: In the past few decades, selective serotonin reuptake inhibitors (SSRIs) became widely used antidepressants worldwide. Therefore, the adverse reactions of patients after SSRI administration became a public and clinical concern. In this study, we conducted a pharmacovigilance study using the Adverse Event Reporting System (FAERS) database of the US Food and Drug Administration.

Phase Coexistence Induced Giant Dielectric Tunability and Electromechanical Response in PbZrO Epitaxial Thin Films.

PbZrO (PZO) thin films, as a classic antiferroelectric material, have attracted tremendous attention for their excellent dielectric, electromechanical, and thermal switching performances. However, several fundamental questions remain unresolved, particularly the existence of an intermediate phase during the transition from the antiferroelectric (AFE) to ferroelectric (FE) state. Here, a phase coexistence configuration of an orthorhombic AFE phase and a tetragonal-like (T-like) phase is reported in epitaxial antiferroelectric PZO thin films, with thickness ranging from 16 to 110 nm.

Deformation-Induced Electromagnetic Reconfigurable Square Ring Kirigami Metasurfaces.

The continuous expansion of wireless communication application scenarios demands the active tuning of electromagnetic (EM) metamaterials, which is essential for their flexible adaptation to complex EM environments. However, EM reconfigurable systems based on intricate designs and smart materials often exhibit limited flexibility and incur high manufacturing costs. Inspired by mechanical metastructures capable of switching between multistable configurations under repeated deformation, we propose a planar kirigami frequency selective surface (FSS) that enables mechanical control of its resonant frequency.

Polar vortex hidden in twisted bilayers of paraelectric SrTiO.

Polar topologies, such as vortex and skyrmion, have attracted significant interest due to their unique physical properties and promising applications in high-density memory devices. To date, all known polar vortices are present in or induced by ferroelectric materials. In this study, we find polar vortex arrays in paraelectric SrTiO.

Inverse Size-Scaling Ferroelectricity in Centrosymmetric Insulating Perovskite Oxide DyScO.

The breaking of inversion symmetry dictates the emergence of electric polarization, whose topological states in superlattices and bulks have received tremendous attention for their intriguing physics brought for novel device design. However, as for substrate oxides such as LaAlO, KTaO, RScO (R = rare earth element), their centrosymmetric trivial attributes make their functionality poorly explored. Here, the discovery of nanoscale thickness gradient-induced nonpolar-to-polar phase transition in band insulator DyScO is reported by using atomic resolution transmission electron microscopy.

A Multi-Objective Optimization Framework That Incorporates Interpretable CatBoost and Modified Slime Mould Algorithm to Resolve Boiler Combustion Optimization Problem.

The combustion optimization problem of the circulation fluidized bed boiler is regarded as a difficult multi-objective optimization problem that requires simultaneously improving the boiler thermal efficiency and reducing the NOx emissions concentration. In order to solve the above-mentioned problem, a new multi-objective optimization framework that incorporates an interpretable CatBoost model and modified slime mould algorithm is proposed. Firstly, the interpretable CatBoost model combined with TreeSHAP is applied to model the boiler thermal efficiency and NOx emissions concentration.

A Reinforced Whale Optimization Algorithm for Solving Mathematical Optimization Problems.

The whale optimization algorithm has several advantages, such as simple operation, few control parameters, and a strong ability to jump out of the local optimum, and has been used to solve various practical optimization problems. In order to improve its convergence speed and solution quality, a reinforced whale optimization algorithm (RWOA) was designed. Firstly, an opposition-based learning strategy is used to generate other optima based on the best optimal solution found during the algorithm's iteration, which can increase the diversity of the optimal solution and accelerate the convergence speed.

Carrier-phonon decoupling in perovskite thermoelectrics via entropy engineering.

Thermoelectrics converting heat and electricity directly attract broad attentions. To enhance the thermoelectric figure of merit, zT, one of the key points is to decouple the carrier-phonon transport. Here, we propose an entropy engineering strategy to realize the carrier-phonon decoupling in the typical SrTiO-based perovskite thermoelectrics.

Janus Doping of Sulfur into Platinum Diselenide Ribbons.

2D platinum diselenide (PtSe), a novel member of the transition metal dichalcogenides (TMDCs) family, possesses many excellent properties, including a layer-dependent bandgap, high carrier mobility, and broadband response, making it promise for applications in technologies like field-effect transistors and room-temperature photodetectors. Doping represents an effective method to modify the electrical properties of 2D TMDCs and to bestow upon them additional functions. However, to date, little research has been conducted on the successful doping of 2D PtSe for modification.

Interrelationships among College Students' Perceptions of Smart Classroom Environments, Perceived Usefulness of Mobile Technology, Achievement Emotions, and Cognitive Engagement.

Cognitive engagement is a crucial factor that shapes successful learning outcomes, but our understanding of the factors that influence such engagement in the smart classroom context remains limited. This study aims to narrow this research gap by exploring the relationships among college students' perceptions of the smart learning environment, perceived usefulness of mobile technology, achievement emotions, and cognitive engagement. A total of 1293 college students completed an online questionnaire survey, and 1076 valid responses were received.

Partitioning polar-slush strategy in relaxors leads to large energy-storage capability.

Relaxor ferroelectric (RFE) films are promising energy-storage candidates for miniaturizing high-power electronic systems, which is credited to their high energy density () and efficiency. However, advancing their beyond 200 joules per cubic centimeter is challenging, limiting their potential for next-generation energy-storage devices. We implemented a partitioning polar-slush strategy in RFEs to push the boundary of .

In situ copper photocatalysts triggering halide atom transfer of unactivated alkyl halides for general C(sp3)-N couplings.

Direct reduction of unactivated alkyl halides for C(sp3)-N couplings under mild conditions presents a significant challenge in organic synthesis due to their low reduction potential. Herein, we introduce an in situ formed pyridyl-carbene-ligated copper (I) catalyst that is capable of abstracting halide atom and generating alkyl radicals for general C(sp3)-N couplings under visible light. Control experiments confirmed that the mono-pyridyl-carbene-ligated copper complex is the active species responsible for catalysis.

Transparent and Ultra-Thin Flexible Checkerboard Metasurface for Radar-Infrared Bi-Stealth.

This paper proposed a single-layer checkerboard metasurface with simultaneous wideband radar cross-section (RCS) reduction characteristics and low infrared (IR) emissivity. The metasurface consists of an indium tin oxide (ITO)-patterned film, a polyethylene terephthalate (PET) substrate and an ITO backplane from the top downwards, with a total ultra-thin thickness of 1.6 mm.

Achieving widely distributed feature matches using flattened-affine-SIFT algorithm for fisheye images.

Performing correction first is the most common methods to address feature matching issues for fisheye images, but corrections often result in significant loss of scene details or stretching of images, leaving peripheral regions without matches. In this paper, we propose a novel approach, named flattened-affine-SIFT, to find widely distributed feature matches between stereo fisheye images. Firstly, we establish a new imaging model that integrates a scalable model and a hemisphere model.

A review of rigid point cloud registration based on deep learning.

With the development of 3D scanning devices, point cloud registration is gradually being applied in various fields. Traditional point cloud registration methods face challenges in noise, low overlap, uneven density, and large data scale, which limits the further application of point cloud registration in actual scenes. With the above deficiency, point cloud registration methods based on deep learning technology gradually emerged.

Research on the spatial patterns and evolution trends of the coupling coordination between digital finance and sustainable economic development in the Yellow River Basin, China.

In the current global context, digital finance (DF) and sustainable economic development (SED) are important topics. The synergies between DF and SED have already been proven. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of DF and SED have not received sufficient attention to date.

Endovascular repair versus best medical treatment for uncomplicated acute type B acute aorta dissection: a meta-analysis.

Introduction: In acute type B aortic dissection (TBAD) patients, thoracic endovascular aorta repair (TEVAR) and best medical treatment (BMT) have both been employed for the clinical management of this condition. The relative efficacy of TEVAR and BMT when used to manage cases of acute uncomplicated TBAD, however, remains to be clarified.

Aim: To conduct a pooled meta-analysis comparing acute uncomplicated TBAD patient outcomes associated with primary TEVAR or BMT treatment.

An Optically Transparent Metamaterial Absorber with Tunable Absorption Bandwidth and Low Infrared Emissivity.

A transparent metamaterial absorber (MMA) with both tunable absorption bandwidth and low infrared (IR) emissivity is proposed in this paper. The MMA is hierarchical, which consists of an infrared shielding layer (IRSL), two radar-absorption layers (RALs), an air/water layer, and an indium-tin-oxide (ITO) backplane from the top downwards. The IRSL and the RALs are made of ITO patterns etched on polyethylene terephthalate (PET) substrates.

Optimizing boiler combustion parameters based on evolution teaching-learning-based optimization algorithm for reducing NO emission concentration.

How to reduce a boiler's NO emission concentration is an urgent problem for thermal power plants. Therefore, in this paper, we combine an evolution teaching-learning-based optimization algorithm with extreme learning machine to optimize a boiler's combustion parameters for reducing NO emission concentration. Evolution teaching-learning-based optimization algorithm (ETLBO) is a variant of conventional teaching-learning-based optimization algorithm, which uses a chaotic mapping function to initialize individuals' positions and employs the idea of genetic evolution into the learner phase.

Effects of urea solution concentration on soil hydraulic properties and water infiltration capacity.

Elucidating the effect of fertigation on soil hydraulic parameters and water-solute transportation is fundamental to the design of farmland irrigation systems and their sustainable utilization. Few studies have focused on soil hydraulic parameters or water infiltration characteristics or how they are influenced by urea solution concentration. In this study, the clay loam and sandy loam in Yangling District of Shaanxi Province, China, were used as test soil, and experiments involving seven urea solution concentrations (0.

Photoinduced Homolysis of the Ni-P Bond via Ligand to Metal Charge Transfer for C-P Bond Formation in Nickel Catalysis.

Photoinduced homolysis of Ni-carbon and -heteroatom bonds has been well studied for carbon-heteroatom couplings, but homolysis of the Ni-P bond is still undisclosed. Herein, we describe the homolysis of Ni-P bonds via ligand to metal charge transfer to access active nickel(I) complexes and phosphorus-centered radicals under visible-light irradiation for C-P couplings of diaryl phosphine oxides with aryl bromides. Experimental studies demonstrated that visible light enabled homolysis of the Ni-P bond and the Ni/Ni self-sustained cycle was involved in C-P bond formation.

LiDAR-assisted accuracy improvement strategy for binocular visual measurement.

The measurement model of binocular vision is inaccurate when the measurement distance is much different from the calibration distance, which affects its practicality. To tackle this challenge, we proposed what we believe to be a novel LiDAR-assisted accuracy improvement strategy for binocular visual measurement. First, the 3D points cloud and 2D images were aligned by the Perspective-n-Point (PNP) algorithm to realize calibration between LiDAR and binocular camera.

Modified Marine Predators Algorithm hybridized with teaching-learning mechanism for solving optimization problems.

Marine Predators Algorithm (MPA) is a newly nature-inspired meta-heuristic algorithm, which is proposed based on the Lévy flight and Brownian motion of ocean predators. Since the MPA was proposed, it has been successfully applied in many fields. However, it includes several shortcomings, such as falling into local optimum easily and precocious convergence.