Structural Diversity Research Articles

A unified moment tensor potential for silicon, oxygen, and silica

Si and its oxides have been extensively explored in theoretical research due to their technological importance. Simultaneously describing interatomic interactions within both Si and SiO2 without the use of ab initio methods is considered challenging, given the charge transfers involved. Herein, this challenge is overcome by developing a unified machine learning interatomic potentials describing the Si/SiO2/O system, based on the moment tensor potential (MTP) framework. This MTP is trained using a comprehensive database generated using density functional theory simulations, encompassing diverse crystal structures, point defects, extended defects, and disordered structure. Extensive testing of the MTP is performed, indicating it can describe static and dynamic features of very diverse Si, O, and SiO2 atomic structures with a degree of fidelity approaching that of DFT.

Entropy‐Assisted Anion‐Reinforced Solvation Structure for Fast‐Charging Sodium‐Ion Full Batteries

AbstractAnion‐reinforced solvation structure favors the formation of inorganic‐rich robust electrode‐electrolyte interface, which endows fast ion transport and high strength modulus to enable improved electrochemical performance. However, such a unique solvation structure inevitably injures the ionic conductivity of electrolytes and limits the fast‐charging performance. Herein, a trade‐off in tuning anion‐reinforced solvation structure and high ionic conductivity is realized by the entropy‐assisted hybrid ester‐ether electrolyte. Anion‐reinforced solvation sheath with more anions occupying the inner Na+ shell is constructed by introducing the weakly coordinated ether tetrahydrofuran into the commonly used ester‐based electrolyte, which merits the accelerated desolvation energy and gradient inorganic‐rich electrode‐electrolyte interface. The improved ionic conductivity is attributed to the weakly diverse solvation structures induced by entropy effect. These enable the enhanced rate performance and cycling stability of Prussian blue||hard carbon full cells with high electrode mass loading. More importantly, the practical application of the designed electrolyte was further demonstrated by industry‐level 18650 cylindrical cells.

A Review of Carbon Anode Materials for Sodium-Ion Batteries: Key Materials, Sodium-Storage Mechanisms, Applications, and Large-Scale Design Principles.

Sodium-ion batteries (SIBs) have been proposed as a potential substitute for commercial lithium-ion batteries due to their excellent storage performance and cost-effectiveness. However, due to the substantial radius of sodium ions, there is an urgent need to develop anode materials with exemplary electrochemical characteristics, thereby enabling the fabrication of sodium-ion batteries with high energy density and rapid dynamics. Carbon materials are highly valued in the energy-storage field due to their diverse structures, low cost, and high reliability. This review comprehensively summarizes the typical structure; energy-storage mechanisms; and current development status of various carbon-based anode materials for SIBs, such as hard carbon, soft carbon, graphite, graphene, carbon nanotubes (CNTs), and porous carbon materials. This review also provides an overview of the current status and future development of related companies for sodium-ion batteries. Furthermore, it offers a summary and outlook on the challenges and opportunities associated with the design principles and large-scale production of carbon materials with high-energy-density requirements. This review offers an avenue for exploring outstanding improvement strategies for carbon materials, which can provide guidance for future application and research.

Entropy-Assisted Anion-Reinforced Solvation Structure for Fast-Charging Sodium-Ion Full Batteries.

Anion-reinforced solvation structure favors the formation of inorganic-rich robust electrode-electrolyte interface, which endows fast ion transport and high strength modulus to enable improved electrochemical performance. However, such a unique solvation structure inevitably injures the ionic conductivity of electrolytes and limits the fast-charging performance. Herein, a trade-off in tuning anion-reinforced solvation structure and high ionic conductivity is realized by the entropy-assisted hybrid ester-ether electrolyte. Anion-reinforced solvation sheath with more anions occupying the inner Na+ shell is constructed by introducing the weakly coordinated ether tetrahydrofuran into the commonly used ester-based electrolyte, which merits the accelerated desolvation energy and gradient inorganic-rich electrode-electrolyte interface. The improved ionic conductivity is attributed to the weakly diverse solvation structures induced by entropy effect. These enable the enhanced rate performance and cycling stability of Prussian blue||hard carbon full cells with high electrode mass loading. More importantly, the practical application of the designed electrolyte was further demonstrated by industry-level 18650 cylindrical cells.

Rapid Targeted Screening and Identification of Active Ingredients in Herbal Extracts through Ligand-Detected NMR and Database Matching.

Herbal extracts are rich sources of active compounds that can be used for drug screening due to their diverse and unique chemical structures. However, traditional methods for screening these compounds are notably laborious and time-consuming. In this manuscript, we introduce a new high-throughput approach that combines nuclear magnetic resonance (NMR) spectroscopy with a tailored database and algorithm to rapidly identify bioactive components in herbal extracts. This method distinguishes characteristic signals and structural motifs of active constituents in the raw extracts through a relaxation-weighted technique, particularly utilizing the perfect echo Carr-Purcell-Meiboom-Gill (peCPMG) sequence, complemented by precise 2D spectroscopic strategies. The cornerstone of our approach is a customized database designed to filter potential compounds based on defined parameters, such as the presence of CHn segments and unique chemical shifts, thereby expediting the identification of promising compounds. This innovative technique was applied to identifying substances interacting with choline kinase α (ChoKα1), resulting in the discovery of four new inhibitors. Our findings demonstrate a powerful tool for unraveling the complex chemical landscape of herbal extracts, considerably facilitating the search for new pharmaceutical candidates. This approach offers an efficient alternative to traditional methods in the quest for drug discovery from natural sources.

Iran’s health insurance ecosystem: challenges and strategies

IntroductionIdentifying and exploiting stewardship and financing challenges in Iran’s health insurance system as an ecosystem is essential to achieving predetermined goals. This study aimed to determine the challenges and strategies in the Iranian health insurance ecosystem to provide relevant evidence to healthcare managers and policymakers to improve its functions and perform necessary reforms.MethodThis qualitative study was conducted at the national level in Iran. Data were collected using semi-structured interviews and analyzed using the directed content analysis method. The study participants included managers and experts in health insurance and faculty of universities of medical sciences, who were selected by purposive sampling.ResultsThe challenges and strategies expressed by participants were categorized into two functions: stewardship and financing. Four main themes, ten subthemes, 22 challenges, and 24 strategies were identified in the stewardship function, along with three main themes, 12 subthemes, 17 challenges, and 16 strategies in the financing function. The major challenge in the Iranian health insurance ecosystem was the complexity and conflict of interests between multiple actors with different roles, which led to fragmentation, diverse structures, and a gap between other functions and objectives, hindering the effective functioning of the ecosystem.ConclusionIn order to deal with the challenges of the health insurance ecosystem, it is suggested to create a coherent insurance system through a single utility system, and by paying more attention to health-oriented services, the health insurance ecosystem becomes a health-oriented system instead of being treatment-oriented. In addition, in order to strengthen the governance of the country’s health insurance ecosystem, the number of actors with multiple roles should be reduced and the roles of the actors should be clarified and separated in order to prevent conflicts of interest and structural corruption in this ecosystem.

A novel approach to crack modeling using extended finite element and substructures methods

In the present work, a combination of Extended Finite Element Method (XFEM) and substructures methods has been utilized for crack modeling. Structures are divided into several substructures, and XFEM is employed to model the presence of cracks within each substructure. In another method, crack modeling has been carried out without using the Extended Finite Element Method. Instead, cracks are modeled by eliminating boundary constraints from two substructures. The Krylov-Schur algorithm is utilized to accelerate the computation of structural modes by preparing stiffness and mass matrices for eigenvalue and eigenvector calculations related to the superstructure. For evaluating this method, four examples have been considered: In the first example, an experimental L-shaped steel structure comprising a beam and a column was examined. The second example involved an experimental steel beam with a box-shaped cross-section. In the third example, a steel beam with simple supports at both ends and a rectangular cross-section was proposed. In the fourth example, a real two-span bridge (Turtle Mountain Bridge) is also presented to evaluate the proposed method. The method was applied for modeling, and the obtained results were validated using experimental and analytical results. In this work, the Structural Similarity Index Method (SSIM) for mode shape similarity assessment has been employed for crack identification. Based on the results obtained from the modeling and crack identification evaluations, it can be concluded that the current method can model multiple cracks in structures with variable cross-sections, real concrete bridges, frame-shaped structures, and diverse structures by assembling substructures. Despite simplifying the problems, it maintains an acceptable level of accuracy in validation. This advantage enables the identification of cracks through a straightforward comparison of mode shapes.

A Comparative Study of Maze Generation Algorithms in a Game-Based Mobile Learning Application for Learning Basic Programming Concepts

This study evaluates several maze generation algorithms applied to generate mazes in a game-based Android mobile application designed to support children in learning basic programming concepts and computational thinking. Each algorithm is assessed for its ability to generate solvable and educationally effective mazes, varying in complexity and size. Key findings indicate that Wilson’s and Aldous–Broder algorithms were identified as the most time inefficient. In comparison, Sidewinder and Binary Tree algorithms perform best for smaller mazes due to their straightforward traversal methods. The Hunt-and-Kill and Recursive backtracker algorithms maintain higher ratios of longest paths, making them suitable for the more complex maze generation required for advanced game levels. Additionally, the study explores various maze-solving algorithms, highlighting the efficiency of the recursive algorithm for simpler mazes and the reliability of Dijkstra’s algorithm across diverse maze structures. This research underscores the importance of selecting appropriate maze generation and solving algorithms to balance generation speed, path complexity, and navigational characteristics. While the study demonstrates the practical applicability of these algorithms in a mobile educational application, it also identifies limitations and suggests directions for future research.

Recent Advances in the Application of 2-Aminobenzothiazole to the Multicomponent Synthesis of Heterocycles.

Heterocycles are a vital class of compounds in numerous fields, including drug discovery, agriculture, and materials science. Efficient methods for the synthesis of heterocycles remain critical for meeting the demands of these industries. Recent advances in multicomponent reactions (MCRs) utilizing 2-aminobenzothiazole (ABT) have shown promising results for the formation of heterocycles. The versatility of 2-aminobenzothiazole in this context has enabled the rapid and efficient construction of diverse heterocyclic structures. Various synthetic methodologies and reactions involving 2-aminobenzothiazole are discussed, highlighting its importance as a valuable building block in the synthesis of complex heterocycles. The potential applications of these heterocycles in drug discovery and material science are also explored. Overall, this review provides a comprehensive overview of the current state of research in the field and offers insights into the future directions of this promising area of study. We highlight the potential of ABT as a versatile and sustainable starting material in heterocyclic synthesis via MCRs, with significant implications for the chemical industry.

Multimodal Molecular Imaging Reveals a Novel Membrane Component in Sporangia of the Rare Actinomycete Actinoplanes missouriensis.

The bacterium Actinoplanes missouriensis belongs to the genus Actinoplanes, a prolific source of useful natural products. This microbe forms globular structures called sporangia, which contain many dormant spores. Recent studies using transmission electron microscopy have shown that the A. missouriensis sporangium membrane has an unprecedented three-layer structure, but its molecular components remain unclear. Here, we present multimodal (spontaneous Raman scattering, coherent anti-Stokes Raman scattering, second harmonic generation, sum frequency generation, and third-order sum frequency generation) label-free molecular imaging of intact A. missouriensis sporangia. Spontaneous Raman imaging assisted with multivariate curve resolution-alternating least-squares analysis revealed a novel component in the sporangium membrane that exhibits unique Raman bands at 1550 and 1615 cm-1 in addition to those characteristic of lipids. A plausible candidate for this component is an unsaturated carbonyl compound with an aliphatic moiety derived from fatty acid. Furthermore, second harmonic generation imaging revealed that a layer(s) of the sporangium membrane containing this unknown component has an ordered, noncentrosymmetric structure like fibrillar proteins and amylopectin. Our results suggest that the sporangium membrane is a new type of biological membrane, not only in terms of architecture but also in terms of components. We demonstrate that multimodal molecular imaging with Raman scattering as the core technology will provide a promising platform for interrogating the chemical components, whether known or unknown, of diverse biological structures produced by microbes.

Advanced Organic–Inorganic Hybrid Materials for Optoelectronic Applications

AbstractResearch on organic–inorganic hybrid materials (OIHMs) has experienced explosive growth in the past decades. The diversity of organic components allows for the introduction of various spatial scales, functional groups, and polarities, while inorganic components provide higher hardness, heat resistance, and stability, their flexible combination facilitates the formation of diverse structures. Furthermore, simple and cost‐effective synthesis methods, such as room temperature solution processes and mechanochemical techniques, enable precise control over the materials' properties at different scales, thus achieving adjustable structure–performance relationships. This review will discuss the recent research progress of OIHMs within the field of optoelectronics and related optoelectronic device applications. According to the dimension of inorganic components and the nature of organic–inorganic interface, this review divides OIHMs into four structural categories. The ongoing research has revealed diverse applications for OIHMs in the fields of solar cells, light‐emitting devices, detectors, and memristors. As an outlook, the potential of perovskite and 0D metal halide materials, which are currently the most studied, for enhancing optoelectronic performance and stability is discussed.

A review on the development of metals-doped Vanadium oxides for zinc-ion battery

Rechargeable zinc-ion batteries (ZIBs) are emerging as promising energy storage devices for various applications, including large-scale energy storage, due to their environmental friendliness, enhanced safety, and low cost. A key challenge in ZIB development is creating cathode materials that reduce the solubility of active materials in aqueous electrolytes, increase electrical conductivity, and extend life cycles for high performance. Vanadium-based compounds, with their diverse structures and multiple oxidation states (+2, +3, +4, and +5), have been extensively studied as effective cathodes for ZIBs. This mini review highlights recent research on doping transition metals into vanadium oxide materials to achieve superior electrochemical performance compared to electrodes prepared via solid-phase synthesis and hydrothermal methods. Additionally, it offers guidance for the future development of vanadium-based materials.

Synthesis of linear low-density polyethylene waxes through chain-walking benzocycloalkyl nickel-catalyzed ethylene polymerization

Polyethylene wax is a highly useful material, and its diverse topological structures may have a significant impact on its applications. In this study, we have devised and synthesized a series of unilateral benzocycloalkyl α-diimine nickel catalysts. These nickel catalysts exhibited very high activities (1.06 to 10.25 × 106 g mol-1·h-1) and yielded branched (37–97/1000 C) polyethylene waxes with low molecular weights (Mn = 0.49 to 2.01 kg mol-1) and variable molecular weight distributions (1.79–35.05) in ethylene polymerization. Polymerization conditions such as pressure and temperature and catalyst structure such as backbone and axial substituents have an important influence on the polymerization activity and the properties of the resulting polyethylene waxes. High-temperature NMR reveals that these branched polyethylenes primarily feature short-chain branches, such as the methyl group, and exhibit a topology resembling that of low-molecular-weight linear low-density polyethylene (LLDPE).

Modeling heat‐mass transport for MHD bio‐convection Carreau nanofluid with Joule heating containing both gyrotactic microbes and nanoparticles diffusion

AbstractThe study of a bio‐convection is a natural progression that happens as microbes transport unsystematically in single‐celled or colony‐like environments; as they live ubiquitously, individuals, as in rodents, and plant forms. They're so much denser than liquid, owing to which, microbes develop a basis of bio‐convection. Gyrotactic microbes are individuals that dip up‐stream in contradiction of gravity in motionless liquid, producing the higher portion of the deferment to be thicker than the lesser part. Bioconvection's significance can be realized in a diversity of bio‐microsystems, for instance, bio‐tech allied to mass transport, biofuels, enzyme biosensors and fraternization. Together with nanofluids, a mixture of bioconvective is working to progress the structure's thermal enactment which has uses in diverse scientific structures. Recent study has related the progress of extrusion features, radiative heat progression and biofuel fabrication to the use of nanoparticles. The essential plans of the modern scrutinization are to examine the magneto bioconvection flow of nonlinear radiative Carreau fluid persuades by the nanofluid and Joule heating. Additionally, Convective conditions of heat, mass and motile microorganism with heat sink/source and chemical reaction have been explored. By means of similarity alteration to alter the nonlinear partial differential equations into nonlinear Ordinary differential equations (ODE). The solutions of subjected equations have been attained by exploiting the bvp4c algorithm. Homotopic algorithm has been also executed for comparison of bvp4c results and former studies. The impacts of relatable factors on diverse fields are sketched in graphic form. The study explores temperature field enhancement for thermo Biot and Brownian motion factors. Furthermore, the fluid concentration exaggerates for mass Biot and chemical reaction factor; however, declines for Brownian motion factor. The motile density field decays with the rising values for Peclet number and intensifies for motile density Biot factor. The comparison tables of current work and previous work also have been presented for the authentication of work with two different techniques.

Sn4+ Alloying and Chiral Incorporation into Tellurium Halides Triggering Tunable Luminescence Emission and Second-Harmonic Generation.

Recently, chiral organic-inorganic hybrid metal halides have attracted considerable interest as promising multifunctional materials, benefiting from their diverse structures and tunable photophysical properties. Herein, by introducing the chiral ligand methylbenzylamine (R-/S-MBA) and alloying Sn4+ cation, a series of tellurium-based halides R-/S-MBA2SnxTe1-xCl6 (x = 0, 0.125, 0.2, 0.365 and 0.54) with second-harmonic generation (SHG) effect and photoluminescence (PL) properties are successfully synthesized. Their optical bandgaps are determined to be 2.48-2.6 eV. Specifically, the introduction of chiral organic cations could break the structural symmetry and cause the tellurium halide to crystallize in the chiral space group. The incorporation of isovalent Sn4+ into the chiral host tellurium halides results in the increase in octahedral distortion, thereby promoting host intrinsic self-trapped emission that originates from the interconfigurational 3P0,1 → 1S0 transitions of Te4+. Consequently, the as-prepared Sn4+ doped halides, R-/S-MBA2SnxTe1-xCl6 (x = 0.365, 0.54), exhibit not only SHG response but also bright orange fluorescence. This study provides an effective strategy for designing chiral multifunctional materials.

A best-match approach for gene set analyses in embedding spaces.

Embedding methods have emerged as a valuable class of approaches for distilling essential information from complex high-dimensional data into more accessible lower-dimensional spaces. Applications of embedding methods to biological data have demonstrated that gene embeddings can effectively capture physical, structural, and functional relationships between genes. However, this utility has been primarily realized by using gene embeddings for downstream machine-learning tasks. Much less has been done to examine the embeddings directly, especially analyses of gene sets in embedding spaces. Here, we propose an Algorithm for Network Data Embedding and Similarity (ANDES), a novel best-match approach that can be used with existing gene embeddings to compare gene sets while reconciling gene set diversity. This intuitive method has important downstream implications for improving the utility of embedding spaces for various tasks. Specifically, we show how ANDES, when applied to different gene embeddings encoding protein-protein interactions, can be used as a novel overrepresentation- and rank-based gene set enrichment analysis method that achieves state-of-the-art performance. Additionally, ANDES can use multiorganism joint gene embeddings to facilitate functional knowledge transfer across organisms, allowing for phenotype mapping across model systems. Our flexible, straightforward best-match methodology can be extended to other embedding spaces with diverse community structures between set elements.

Tuning singlet oxygen generation with caged organic photosensitizers

Controlling the succession of chemical processes with high specificity in complex systems is advantageous for widespread applications, from biomedical research to drug manufacturing. Despite synthetic advances in bioorthogonal and photochemical methodologies, there is a need for generic chemical approaches that can universally modulate photodynamic reactivity in organic photosensitizers. Herein we present a strategy to fine-tune the production of singlet oxygen in multiple photosensitive scaffolds under the activation of bioresponsive and bioorthogonal stimuli. We demonstrate that the photocatalytic activity of nitrobenzoselenadiazoles can be fully blocked by site-selective incorporation of electron-withdrawing carbamate moieties and restored on demand upon uncaging with a wide range of molecular triggers, including abiotic transition-metal catalysts. We also prove that this strategy can be expanded to most photosensitizers, including diverse structures and spectral properties. Finally, we show that such advanced control of singlet oxygen generation can be broadly applied to the photodynamic ablation of human cells as well as to regulate the release of singlet oxygen in the semi-synthesis of natural product drugs.

Perturbation approaches to achieving diverse and competitive designs in topology optimisation

Utilising topology optimisation to generate diverse and competitive structures enables designers to create elegant and efficient designs according to their aesthetic intuition and functional needs. This study proposes load and support perturbation approaches based on the bi-directional evolutionary structural optimisation (BESO) method to achieve diverse designs. During the optimisation process, noise is introduced to the sensitivity calculations by randomly perturbing the load angles or material properties near the supports, leading to a variety of local optima. Numerical results demonstrate that the proposed approaches are capable of creating designs with similar stiffness but distinct geometries. In addition, the diversity of the obtained solutions can be controlled by utilising different perturbation functions. This work is of significant practical importance in both architecture and engineering, where multiple design options of high structural performance are in demand.

ConvMambaSR: Leveraging State-Space Models and CNNs in a Dual-Branch Architecture for Remote Sensing Imagery Super-Resolution

Deep learning-based super-resolution (SR) techniques play a crucial role in enhancing the spatial resolution of images. However, remote sensing images present substantial challenges due to their diverse features, complex structures, and significant size variations in ground objects. Moreover, recovering lost details from low-resolution remote sensing images with complex and unknown degradations, such as downsampling, noise, and compression, remains a critical issue. To address these challenges, we propose ConvMambaSR, a novel super-resolution framework that integrates state-space models (SSMs) and Convolutional Neural Networks (CNNs). This framework is specifically designed to handle heterogeneous and complex ground features, as well as unknown degradations in remote sensing imagery. ConvMambaSR leverages SSMs to model global dependencies, activating more pixels in the super-resolution task. Concurrently, it employs CNNs to extract local detail features, enhancing the model’s ability to capture image textures and edges. Furthermore, we have developed a global–detail reconstruction module (GDRM) to integrate diverse levels of global and local information efficiently. We rigorously validated the proposed method on two distinct datasets, RSSCN7 and RSSRD-KQ, and benchmarked its performance against state-of-the-art SR models. Experiments show that our method achieves SOTA PSNR values of 26.06 and 24.29 on these datasets, respectively, and is visually superior, effectively addressing a variety of scenarios and significantly outperforming existing methods.

In silico Approaches for Exploring the Pharmacological Activities of Benzimidazole Derivatives: A Comprehensive Review.

This article reviews computational research on benzimidazole derivatives. Cytotoxicity for all compounds against cancer cell lines was measured and the results revealed that many compounds exhibited high inhibitions. This research examines the varied pharmacological properties like anticancer, antibacterial, antioxidant, anti-inflammatory and anticonvulsant activities of benzimidazole derivatives. The suggested method summarises In silico research for each activity. This review examines benzimidazole derivative structure-activity relationships and pharmacological effects. In silico investigations can anticipate structural alterations and their effects on these derivative's pharmacological characteristics and efficacy through many computational methods. Molecular docking, molecular dynamics simulations and virtual screening help anticipate pharmacological effects and optimize chemical design. These trials will improve lead optimization, target selection, and ADMET property prediction in drug development. In silico benzimidazole derivative studies will be assessed for gaps and future research. Prospective studies might include empirical verification, pharmacodynamic analysis, and computational methodology improvement. This review discusses benzimidazole derivative In silico research to understand their specific pharmacological effects. This will help scientists design new drugs and guide future research. Latest, authentic and published reports on various benzimidazole derivatives and their activities are being thoroughly studied and analyzed. The overview of benzimidazole derivatives is more comprehensive, highlighting their structural diversity, synthetic strategies, mechanisms of action, and the computational tools used to study them. In silico studies help to understand the structure-activity relationship (SAR) of benzimidazole derivatives. Through meticulous alterations of substituents, ring modifications, and linker groups, this study identified the structural factors influencing the pharmacological activity of benzimidazole derivatives. These findings enable the rational design and optimization of more potent and selective compounds.