A Stable High-Performance Zn-Ion Batteries Enabled by Highly Compatible Polar Co-Solvent.

Uncontrollable growth of Zn dendrites, irreversible dissolution of cathode material and solidification of aqueous electrolyte at low temperatures severely restrict the development of aqueous Zn-ion batteries. In this work, 2,2,2-trifluoroethanol (TFEA) with a volume fraction of 50% as a highly compatible polar-solvent is introduced to 1.3 M Zn(CF3SO3)2 aqueous electrolyte, achieving stable high-performance Zn-ion batteries. Massive theoretical calculations and characterization analysis demonstrate that TFEA weakens the tip effect of Zn anode and restrains the growth of Zn dendrites due to electrostatic adsorption and coordinate with H2O to disrupt the hydrogen bonding network in water. Furthermore, TFEA increases the wettability of the cathode and alleviates the dissolution of V2O5, thus improving the capacity of the full battery. Based on those positive effects of TFEA on Zn anode, V2O5 cathode, and aqueous electrolyte, the Zn//Zn symmetric cell delivers a long cycle-life of 782 h at 5 mA cm-2 and 2 mA h cm-2. The full battery still declares an initial capacity of 116.78 mA h g-1, and persists 87.73% capacity in 2000 cycles at -25 °C. This work presents an effective strategy for fully compatible co-solvent to promote the stability of Zn anode, V2O5 cathode and aqueous electrolyte for high-performance Zn-ion batteries.

Structural optimization using a genetic algorithm aiming for the minimum mass of vertical axis wind turbines using composite materials.

A wind turbine comprises multiple components constructed from diverse materials. This complexity introduces challenges in designing the blade structure. In this study, we developed a structural optimization framework for Vertical Axis Wind Turbines (VAWT). This framework integrates a parametric Finite Element Analysis (FEA) model, which simulates the structure's global behavior, with a Genetic Algorithm (GA) optimization technique that navigates the design domain to identify optimal parameters. The goal is to minimize the mass of VAWT structures while adhering to a suite of complex constraints. This framework quantifies the mass reduction impact attributable to material selection and structural designs. The optimization cases indicate that blades made from Carbon Fiber Reinforced Plastics (CFRP) materials are 47.1 % lighter than those made from Glass Fiber Reinforced Plastics (GFRP), while the structural parts are 44.8 % lighter. This work also provides further recommendations regarding the scale and design of the structures. With the materials and structural design established, future studies can expand to include more load cases and detailed designs of specific components.

Molybdenum-Doped Cobalt-Free Cathode Realizing the Electrochemical Stability by Enhanced Covalent Bonding.

The doping strategy effectively enhances the capacity and cycling stability of cobalt-free nickel-rich cathodes. Understanding the intrinsic contributions of dopants is of great importance to optimize the performances of cathodes. This study investigates the correlation between the structure modification and their performances of Mo-doped LiNi0.8Mn0.2O2 (NM82) cathode. The role of doped Mo's valence state has been proved functional in both lattice structural modification and electronic state adjustment. Although the high-valence of Mo at the cathode surface inevitably reduces Ni valence for electronic neutrality and thus causes ion mixing, the original Mo valence will influence its diffusion depth. Structural analyses reveal Mo doping leads to a mixed layer on the surface, where high-valence Mo forms a slender cation mixing layer, enhancing structural stability and Li-ion transport. In addition, it is found that the high-valence dopant of Mo6+ ions partially occupies the unfilled 4d orbitals, which may strengthen the Mo─O bond through increased covalency and therefore reduce the oxygen mobility. This results in an impressive capacity retention (90.0% after 200 cycles) for Mo-NM82 cathodes with a high Mo valence state. These findings underscore the valence effect of doping on layered oxide cathode performance, offering guidance for next-generation cathode development.

Enhancing Binding Affinity to CGG/CGG Triad: Optimizing Naphthyridine Carbamate Dimer Derivatives with Varied Linker Lengths.

This study examines the binding properties of six naphthyridine carbamate dimer (NCD) derivatives with varying linker lengths to the CGG/CGG triad, a non-canonical DNA structure linked to repeat expansion disorders. By altering the linker length from 2 to 4 methylene groups, we found changes in thermal stability of the ligand-bound complexes while maintaining a consistent 2:1 binding stoichiometry. Among the derivatives, CC23 showed superior binding affinity compared to the parent molecule CC33 (NCD). Spectroscopic analyses revealed that linker length influences the conformational equilibrium of NCD derivatives. Thermal melting temperature measurements demonstrated CC23's enhanced thermal stability over CC33. These findings underscore the potential of optimized NCD derivatives, like CC23, as tools to modulate CGG repeat structures, offering insights for therapeutic strategies targeting repeat expansion disorders.

Novel Coumarins Derivatives for A. baumannii Lung Infection Developed by High-Throughput Screening and Reinforcement Learning.

With the increasing resistance of Acinetobacter baumannii (A. baumannii) to antibiotics, researchers have turned their attention to the development of new antimicrobial agents. Among them, coumarin-based heterocycles have attracted much attention due to their unique biological activities, especially in the field of antibacterial infection. In this study, a series of coumarin derivatives were synthesized and screened for their bactericidal activities (Ren et al. 2018; Salehian et al. 2021). The inhibitory activities of these compounds on bacterial strains were evaluated, and the related mechanism of the new compounds was explored. Firstly, the MIC values and bacterial growth curves were measured after compound treatment to evaluate the antibacterial activity in vitro. Then, the in vivo antibacterial activities of the new compounds were assessed on A. baumannii-infected mice by determining the mice survival rates, counting bacterial CFU numbers, measuring inflammatory cytokine levels, and histopathology analysis. In addition, the ROS levels in the bacterial cells were measured with DCFH-DA detection kit. Furthermore, the potential target and detailed mechanism of the new compounds during infection disease therapy were predicted and evidenced with molecular docking. After that, ADMET characteristic prediction was completed, and novel, synthesizable, drug-effective molecules were optimized with reinforcement learning study based on the probed compound as a training template. The interaction between the selected structures and target proteins was further evidenced with molecular docking. This series of innovative studies provides important theoretical and experimental data for the development of new anti-A. baumannii infection drugs.

A review of flow field characteristics in submerged hollow fiber membrane bioreactor: Micro-interface, module and reactor.

As an important part of the membrane field, hollow fiber membranes (HFM) have been widely concerned by scholars. HFM fouling in the industrial application results in a reduction in its lifespan and an increase in cost. In recent years, various explorations on the HFM fouling control strategies have been carried out. In the current work, we critically review the influence of flow field characteristics in HFM-based bioreactor on membrane fouling control. The flow field characteristics mainly refer to the spatial and temporal variation of the related physical parameters. In the HFM field, the physical parameter mainly refers to the variation characteristics of the shear force, flow velocity and turbulence caused by hydraulics. The factors affecting the flow field characteristics will be discussed from three levels: the micro-flow field near the interface of membrane (micro-interface), the flow field around the membrane module and the reactor design related to flow field, which involves surface morphology, crossflow, aeration, fiber packing density, membrane vibration, structural design and other related parameters. The study of flow field characteristics and influencing factors in the HFM separation process will help to improve the performance of HFM in full-scale water treatment plants.

Design and optimization of heat pump with infrared drying for Glycyrrhiza uralensis (Licorice) processing.

A new dryer, integrating infrared and heat pump drying technologies, was designed to enhance licorice processing standardization, aiming at improved drying efficiency and product quality. Numerical simulation using COMSOL software validated the air distribution model through prototype data comparison. To address uneven air distribution, a spoiler was strategically placed based on CFD simulation to optimize its size and position using the velocity deviation ratio and non-uniformity coefficient as indices. Post-optimization, the average velocity deviation ratio decreased from 0.5124 to 0.2565%, and the non-uniformity coefficient dropped from 0.5913 to 0.3152, achieving a more uniform flow field in the drying chamber. Testing the optimized dryer on licorice demonstrated significant improvements in flow field uniformity, reducing licorice drying time by 23.8%. Additionally, optimized drying enhanced licorice color (higher L* value) and increased retention rates of total phenol, total flavone, and vitamin C. This research holds substantial importance for advancing licorice primary processing, fostering efficiency, and improving product quality.

Structure-optimized and microenvironment-inspired nanocomposite biomaterials in bone tissue engineering.

Critical-sized bone defects represent a significant clinical challenge due to their inability to undergo spontaneous regeneration, necessitating graft interventions for effective treatment. The development of tissue-engineered scaffolds and regenerative medicine has made bone tissue engineering a highly viable treatment for bone defects. The physical and biological properties of nanocomposite biomaterials, which have optimized structures and the ability to simulate the regenerative microenvironment of bone, are promising for application in the field of tissue engineering. These biomaterials offer distinct advantages over traditional materials by facilitating cellular adhesion and proliferation, maintaining excellent osteoconductivity and biocompatibility, enabling precise control of degradation rates, and enhancing mechanical properties. Importantly, they can simulate the natural structure of bone tissue, including the specific microenvironment, which is crucial for promoting the repair and regeneration of bone defects. This manuscript provides a comprehensive review of the recent research developments and applications of structure-optimized and microenvironment-inspired nanocomposite biomaterials in bone tissue engineering. This review focuses on the properties and advantages these materials offer for bone repair and tissue regeneration, summarizing the latest progress in the application of nanocomposite biomaterials for bone tissue engineering and highlighting the challenges and future perspectives in the field. Through this analysis, the paper aims to underscore the promising potential of nanocomposite biomaterials in bone tissue engineering, contributing to the informed design and strategic planning of next-generation biomaterials for regenerative medicine.

Synthesis of 2-phenylnaphthalenoid amide derivatives and their topoisomerase IIα inhibitory and antiproliferative activities.

Topoisomerases are highly associated with cell proliferation, becoming an important target for the development of antitumor drugs. 2-Phenylnaphthalenoids (2PNs) have been identified as human DNA topoisomerase IIα (TopoIIα) inhibitors. In this study, based on the 2PN scaffold, 20 amide derivatives (J1-J10, K1-K10) were synthesized. Among them, K10 showed high TopoIIα inhibitory activity and stronger antiproliferation activity against HepG-2 and MDA-MB-231 cells (IC50 0.33 and 0.63 µM, respectively) than the positive control VP-16 (IC50 9.19 and 10.86 µM) and the lead F2 (IC50 0.64 and 1.51 µM). Meanwhile, K10 could also inhibit migration and promote apoptosis of HepG-2 and MDA-MB-231 cells. Therefore, K10 can be developed into a potent TopoIIα inhibitor as an antitumor agent. The structure-activity relationship was also discussed.

Decoding the impact of fiscal decentralization on urban pollution intensity in China: A spatial econometric analysis.

Utilizing city-level data from China, the paper employs a spatial econometric analysis to investigate the impact of fiscal decentralization on urban pollution. Empirical evidence indicates: (1) In the context of the emphasis of ecological civilization construction in China, an increase of fiscal autonomy for local governments is conducive to mitigating urban pollution intensity. Specifically, fiscal decentralization in one city not only promotes a reduction in local pollution intensity but alleviates environmental pollution problems in adjacent cities through spatial spillover effects. (2) Industrial structure upgrading and green technology progress become crucial measures for local governments to realize pollution reduction targets through fiscal expenditure. (3) Heterogeneity analysis reveals that the positive significance of decentralization is most prominent in the eastern China, while local governments with fiscal autonomy in central region tend to transfer pollution to neighboring cities. (4) There is a threshold characteristic for fiscal decentralization to promote a reduction in urban pollution intensity, and its marginal effect becomes more significant accompanied by continuous introduction of sophisticated foreign direct investment. Finally, the paper summarizes the potential significance of fiscal decentralization among Chinese local governments against the background of "Chinese-style decentralization" and proposes corresponding policy recommendations.

Does digital infrastructure construction impact urban carbon emission reduction? Evidence from China's smart city construction.

As the cornerstone of the digital economy, the construction of digital infrastructure plays a crucial role in promoting China's high-quality economic growth.. Against the backdrop of the "dual-carbon" goals, the development of digital infrastructure will provide new momentum for carbon emissions reduction in urban areas. This study utilizes unbalanced panel data from 277 prefecture-level cities in China between 2008 and 2019, treating the smart city construction as a quasi-natural experiment, to systematically evaluate the impact of the pilot construction of smart city on urban carbon emissions intensity. The research findings reveal that the construction of the smart city has significantly contributed to the reduction of urban carbon emissions intensity, indicating that digital infrastructure contributes to urban carbon emission reduction. The reduction of carbon emissions resulting from smart city construction is particularly significant in the East and Central regions., as well as regions with high financial development levels, regions with high human capital levels and non resource-based cities. The construction of the smart city primarily achieves the reduction of urban carbon emissions intensity through two main pathways: improving the penetration rate of digital infrastructure and enhancing technological innovation capability. Therefore, this study recommends that local governments strengthen the integration and penetration of digital infrastructure with traditional industries, foster urban innovation vitality, and accelerate the transformation towards green and low-carbon cities.

Interfacial Optimization for AlN/Diamond Heterostructures via Machine Learning Potential Molecular Dynamics Investigation of the Mechanical Properties.

AlN/diamond heterostructures hold tremendous promise for the development of next-generation high-power electronic devices due to their ultrawide band gaps and other exceptional properties. However, the poor adhesion at the AlN/diamond interface is a significant challenge that will lead to film delamination and device performance degradation. In this study, the uniaxial tensile failure of the AlN/diamond heterogeneous interfaces was investigated by molecular dynamics simulations based on a neuroevolutionary machine learning potential (NEP) model. The interatomic interactions can be successfully described by trained NEP, the reliability of which has been demonstrated by the prediction of the cleavage planes of AlN and diamond. It can be revealed that the annealing treatment can reduce the total potential energy by enhancing the binding of the C and N atoms at interfaces. The strain engineering of AlN also has an important impact on the mechanical properties of the interface. Furthermore, the influence of the surface roughness and interfacial nanostructures on the AlN/diamond heterostructures has been considered. It can be indicated that the combination of surface roughness reduction, AlN strain engineering, and annealing treatment can effectively result in superior and more stable interfacial mechanical properties, which can provide a promising solution to the optimization of mechanical properties, of ultrawide band gap semiconductor heterostructures.

The road to evolution of ProTx2: how to be a subtype-specific inhibition of human Nav1.7.

The human voltage-gated sodium channel Nav1.7 is a widely proven target for analgesic drug studies. ProTx2, a 30-residue polypeptide from Peruvian green tarantula venom, shows high specificity to activity against human Nav1.7, suggesting its potential to become a non-addictive analgesic. However, its high sensitivity to human Nav1.4 raises concerns about muscle side effects. Here, we engineered three mutants (R13A, R13D, and K27Y) of ProTx2 to evaluate their pharmacological activities toward Nav1.7 and Nav1.4. It is demonstrated that the mutant R13D maintained the analgesic effect in mice while dramatically reducing its muscle toxicity compared with ProTx2. The main reason is the formation of a strong electrostatic interaction between R13D and the negatively charged amino acid residues in DII/S3-S4 of Nav1.7, which is absent in Nav1.4. This study advances our understanding and insights on peptide toxins, paving the way for safer, effective non-addictive analgesic development.

Study on curve optimization and structural safety effect of south roof of solar greenhouse in China.

To maximize the use of solar energy and increase the building area of solar greenhouses in China, a light radiation model for solar greenhouses is established. This model integrates previous research results with the solar motion principle, meteorological data and the optical properties of materials. The results indicate that optimizing the structural curve of the south roof of the greenhouse improves both internal land utilization and solar capture. After optimization, the internal land utilization rate of the solar greenhouse increased by 42 m2, with a respective 15.2 and 0.78% increase in lighting on the southern roof and ground. The light interception by the back wall of the greenhouse was reduced by 0.67%, while the total light interception increased by 2.22%. The research results identify the optimal shoulder height (0.7 m) and overall height (2 m) for the second-generation solar greenhouse in Liaoshen. The optimal curve functions Y 1 and Y 2 for the south roofs of greenhouses are calculated according to the actual construction requirements. This article verifies the structural safety of the solar greenhouse after renovation and shows that optimizing the shoulder height increases the structural stability and safety of the greenhouse.

Does business environment optimization improve carbon emission efficiency? Evidence from provincial panel data in China.

Previous research has yielded mixed conclusions regarding whether business environment (BE) optimization can enhance carbon emission efficiency (CEE). This study delves into the impact of the BE on CEE using panel data from 30 provinces in China, employing fixed effect, quantile, and mediated effect models. It innovates in three key areas: research perspective, mechanism of action, and heterogeneity analysis. The research found that the BE optimization enhances CEE. Meanwhile, the influence of the BE on CEE exhibits marginal decreasing characteristics. The mechanism analysis reveals that the BE enhances CEE through the industrial structure optimization effect and the progress of green technology, while it diminishes efficiency through the energy rebound effect. Heterogeneity analysis indicates that BE optimization has a stronger impact on improving CEE in provinces with robust government governance, younger governors, and highly educated officials. The policy implication suggests that local governments should continually optimize the BE, enhance government governance capacity, and prioritize the appointment of young and highly educated officials.

Design, Optimization, and Modeling of a Hydraulic Soft Robot for Chronic Total Occlusions.

Chronic total occlusion (CTO) is one of the most severe and sophisticated vascular stenosis because of complete blockage, greater operation difficulty, and lower procedural success rate. This study proposes a hydraulic-driven soft robot imitating the earthworm's locomotion to assist doctors or operators in actively opening thrombi in coronary or peripheral artery vessels. Firstly, a three-actuator bionic soft robot is developed based on earthworms' physiological structure. The soft robot's locomotion gait inspired by the earthworm's mechanism is designed. Secondly, the influence of structure parameters on actuator deformation, stress, and strain is explored, which can help us determine the soft actuators' optimal structure parameters. Thirdly, the relationship between hydraulic pressure and actuator deformation is investigated by performing finite element analysis using the bidirectional fluid-structure interaction (FSI) method. The kinematic models of the soft actuators are established to provide a valuable reference for the soft actuators' motion control.

Optimizing energy efficiency in induction skull melting process: investigating the crucial impact of melting system structure.

Induction skull melting (ISM) technology could melt metals with avoiding contamination from crucible. A long-standing problem of ISM is that the low charge energy utilization and inhomogeneous fields have obstructed its application in many critical metal materials and manufacturing processes. The present work investigated the problem through the structure optimization strategy and established a numerical electromagnetic-field model to evaluate components' eddy current loss. Based on the model, the effect of crucible and inductor structure on charge energy utilization, etc. was studied. Furtherly, the charge energy utilization was increased from 27.1 to 45.89% by adjusting the system structure. Moreover, structure modifications are proposed for enhancing electromagnetic intensity and uniformity, charge soft contact and uniform heating. The work constructed a basis for framing new solutions to the problem through ISM device structure optimization.

Suppression of Railway Catenary Galloping Based on Structural Parameters' Optimization.

Railway catenary galloping, induced by aerodynamic instability, poses a significant threat by disrupting the electric current connection through sliding contact with the contact wire. This disruption leads to prolonged rail service interruptions and damage to the catenary's suspension components. This paper delves into the exploration of optimizing the catenary system's structure to alleviate galloping responses, addressing crucial parameters such as span length, stagger dropper distribution, and tension levels. Employing a finite element model, the study conducts simulations to analyze the dynamic response of catenary galloping, manipulating structural parameters within specified ranges. To ensure accurate and comprehensive exploration, the Sobol sequence is utilized to generate low-discrepancy, quasi-random, and super-uniform distribution sequences for the high-dimensional parameter inputs. Subsequent to the simulation phase, a genetic algorithm based on neural networks is employed to identify optimal parameter settings for suppressing catenary galloping, taking into account various constraints. The results gleaned from this investigation affirm that adjusting structural parameters can effectively diminish the galloping amplitude of the railway catenary. The most impactful strategy involves augmenting tension and reducing span length. Moreover, even when tension and span length are fixed, adjusting other parameters demonstrates efficacy in reducing galloping amplitudes. The adjustment of messenger-wire tension, dropper distribution, and stagger can achieve a 22.69% reduction in the maximum vertical galloping amplitude. Notably, maintaining a moderate stagger value and a short steady arm-dropper distance is recommended to achieve the minimum galloping amplitude. This research contributes valuable insights into the optimization of railway catenary systems, offering practical solutions to mitigate galloping-related challenges and enhance overall system reliability.

Can industrial structure optimization and industrial structure transition both lead to carbon lock-in mitigation? The case of China.

The optimization and transition of the industrial structure help improve the quality of the economy, moving it toward low-carbon development. By using the Instrumental Variable Generalized Method of Moments model and a city-level dataset covering the period 2006-2019, this paper explores the carbon lock-in mitigation effects of industrial structure optimization and industrial structure transition, respectively. The heterogeneity and the synthetic industrial structure adjustment effect are detected, and the potential impact mechanism is also explored. Some findings have been generated. (1) Both industrial structure optimization and industrial structure transition realize carbon lock-in eradication. (2) Industrial structure optimization and transition are more effective in inhibiting carbon lock-in in cities with a higher level of economic background. (3) By generating an interaction term of industrial structure optimization and transition and examining the impact of the interaction term on carbon lock-in, this paper detects that industrial structure optimization and transition have a synthetic impact on carbon lock-in, showing a "1 + 1 > 2" effect. (4) Industrial structure optimization and transition both affect carbon lock-in by improving technological innovation level, which is the impact mechanism. Some policy implications, such as sectoral diversification and promoting research and development, are put forward for better industrial structure development and carbon unlocking.

Electronic Perturbation of Isolated Fe Coordination Structure for Enhanced Nitrogen Fixation.

Modulation of the local electronic structure of isolated coordination structures plays a critical role in electrocatalysis yet remains a grand challenge. Herein, we have achieved electron perturbation for the isolated iron coordination structure via tuning the iron spin state from a high spin state (FeN4) to a medium state (FeN2B2). The transition of spin polarization facilitates electron penetration into the antibonding π orbitals of nitrogen and effectively activates nitrogen molecules, thereby achieving an ammonia yield of 115 µg h-1 mg-1cat. and a Faradaic efficiency of 24.8%. In situ spectroscopic studies and theoretical calculations indicate that boron coordinate sites, as electron acceptors, can regulate the adsorption energy of NxHy intermediates on the Fe center. FeN2B2 sites favor the NNH* intermediate formation and reduce the energy barrier of rate-determining steps, thus accounting for excellent nitrogen fixation performance. Our strategy provides an effective approach for designing efficient electrocatalysts via precise electronic perturbation.