Short Path Research Articles

A Solar Evaporator Based on Polypyrrole Coated 3D Carbon Nanotube Materials for Efficient Solar-Driven Vapor Generation.

Highly porous light absorbers are fabricated based on polypyrrole (PPy)-coated carbon nanotube (CNT). Carbon nanotube sponge (CNTS) or carbon nanotube array (CNTA) with three-dimensional (3D) network structure is the framework of porous light absorbers. Both PPy@CNTS and PPy@CNTA composites exhibit excellent light absorption of the full solar spectrum. The CNTS and CNTA with porous structures have extremely large effective surface area for light absorption and for water evaporation that has great practical benefit to the solar-driven vapor generation. The PPy layer on CNT sidewalls significantly improves the hydrophilicity of porous CNTS and CNTA. The good wettability of water on CNT sidewalls makes water transport in porous CNT materials highly efficient. The PPy@CNTS and PPy@CNTA light absorbers achieve high water evaporation rates of 3.35 and 3.41kg m-2 h-1 , respectively, under 1-sun radiation. The orientation of nano channels in CNTA-based light absorbers also plays an important role in the solar-driven vapor generation. The water transport and vapor escape are more efficient in CNTA-based light absorbers as compared to the CNTS-based light absorbers due to the relatively short path for the water transport and the vapor escape in CNTA-based light absorbers.

Lattice Rotation and Deformation Mechanisms under Tensile Loading in a Single-Crystal Superalloy with [001] Misorientation.

This study investigates how deviation angles close to the [001] orientation affect the tensile properties and deformation behavior of a nickel-based single-crystal superalloy at room temperature. The research focuses on samples with deviation angles of 3°, 8°, and 13° from the [001] orientation and examines their strength and ductility. We employed scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM) to explore the deformation micro-mechanisms at varying angles. Findings reveal that strength decreases and ductility increases as the deviation angle widens within the [001] vicinity. The study emphasizes that <110> octahedral slip-driven crystal slip and rotation are crucial for understanding tensile deformation. The deformation differences in samples at varying angles are attributed to the differential engagement of mechanisms. Specifically, at lower angles, reduced ductility and increased strength are due to short lattice rotation paths and work hardening causing superlattice stacking faults (SSFs) to slip in two directions on the {111} plane within the γ' phase. As the angles increase, the lattice rotation paths extend, and Shockley partial dislocations (a/6<112>) accumulate in γ channels. This process, involving SSFs moving in a single direction within the γ' phase, results in higher ductility and reduced strength.

Effect of blood oxygen-level-dependent signal data trimming on functional connectivity metrics

In the big data era, with a lack of comparable functional neuroimaging data, researchers try to combine heterogeneous data of different lengths, trimming those to the same number of timepoints (NTPs). However, the effects of trimming blood-oxygen-level dependent (BOLD) signal data on functional connectivity (FC) are still poorly understood.Resting-state functional magnetic resonance imaging data from thirty healthy subjects were pre-processed for five different NTPs, from which FC matrices were computed. These BOLD signal correlation matrices were binarized for several thresholds, excluding weak correlations. Graph metrics were computed to study FC differences between different NTPs. The study included node degree analysis for each brain region and assessment of small-worldness coefficients (σ and ω), whereas in small-world networks, characteristic values are σ > 1 and ω≈ 0, indicating a balance between high clustering coefficients and short characteristic path lengths.A tendency of decreasing global network degrees for higher NTPs was observed, translating the loss of stronger correlations with longer BOLD signals. Trimming such data affects brain regions differently, probably due to brain network dynamics. Regarding small-worldness, we observed that σ was greater than 1 for all the different NTPs, showing an increasing trend for higher NTPs (median value: σBRAIN= 3.05). In addition, ω consistently remained greater than 0 for all NTPs, gradually approaching 0 as the NTPs increased (median value ωBRAIN= 0.20). As such, the results suggest a tendency for an increase of small-world properties for increasing NTPs. Nonetheless, the overall properties of brain networks almost remain constant. In conclusion, trimming BOLD signal data leads to small differences in FC.

MOR nanosheets with tunable c-axis thickness and their catalytic performance in DME carbonylation

Controlling the anisotropic growth of crystals to achieve desired morphology is a challenge in zeolite crystallization, which often requires the use of bulky organic surfactants or additional crystal growth modifiers. Here, MOR crystals with tunable c-axis thickness (12-MR channel direction) were readily synthesized with commercial tetraethylammonium hydroxide (TEAOH) as an organic-structure directing agent (OSDA). It is revealed that the relative growth rates of different crystal faces of MOR zeolite can be tuned by the crystallization temperature and TEAOH amount in the developed gel system. Higher temperature and lower TEAOH concentration can effectively retard the growth of MOR crystals along the c-axis, yielding MOR nanosheets with short c-axis thickness (ca. 40 nm). Investigation on the crystallization process demonstrates that the crystal growth follows a particle attachment mechanism. Theoretical calculation was further employed to elucidate the c-axis thickness variation of MOR zeolite under different conditions. A kilogram-scale synthesis of MOR nanosheets has been realized with a 10 L autoclave, achieving high solid yield of 92 %. The MOR nanosheets, offering short 12-MR diffusion path, exhibit substantially enhanced catalytic activity and stability in the dimethyl ether (DME) carbonylation to methyl acetate reaction.

A multi-function integrated PVDF transducer for fault detection and speed measurement of cylindrical roller bearings

Monitoring the condition of bearings in rotating machinery is crucial to ensure reliability, safety, and efficiency. Recently, integrated sensors have become more popular than traditional accelerometers in bearing condition monitoring because of their compact design, cost-effectiveness, and improved efficiency in fault detection through a short transmission path. This study presents a new approach to bearing condition monitoring by developing a bearing with an integrated Polyvinylidene Fluoride transducer. This polymer-based transducer, known as PVDF, has a piezoelectric effect which generates electric charge in response to mechanical excitation. The PVDF transducer was selected for its high sensitivity, flexibility, and thin structure. The developed bearing with the integrated PVDF transducer can detect faults under constant and variable speeds, and the damage size can be estimated with an accuracy of 10%. It outperformed a commercial accelerometer in noisy environments with artificial impacts from an air motor, making it a highly reliable option for bearing condition monitoring in noisy industrial settings. The PVDF transducer can also be used as a low-cost speed sensor with an accuracy of 5.2%, offering a versatile solution for machine monitoring. By simultaneously recording rotational speed and vibration, the developed integrated transducer provides a comprehensive view of machine health and performance as a multi-function transducer, enabling more accurate and efficient maintenance scheduling.

Hierarchical network-like Ni-Mn-S/NiMn-LDH nanostructure as efficient electrode material for high-rate and long cycle life hybrid supercapacitors

In the present work, we have developed a facile binder-free approach to design a hierarchical network-like nanostructure electrode onto the nickel foam (NF) using the combination of hydrothermal synthesis followed by an electrochemical deposition route. Based on the physicochemical properties and the electrochemical measurements, the integrated Ni-Mn-S/NiMn-LDH electrode delivers an extremely good specific capacitance of 2611.8F/g at 1 A/g and superior cyclic stability with 90.7 % capacitance retention after 10,000 cycles, along with 98.9 % coulomb efficiency. Accordantly, benefiting from the combination of structural and compositional advantages along with the multivalent state of Ni and Mn elements provide more active sites, prominent synergy, and short ion transport paths, which impressively improved the electrochemical performance of Ni-Mn-S/NiMn-LDH. Likewise, the assembled Ni-Mn-S/NiMn-LDH/NF//AC asymmetric device displays an excellent electrochemical behavior with a high energy density of 60.9 Wh kg−1 at a significant power density of 800 W kg−1 alongside the superior life-stability. Furthermore, nine blue LED indicators can be lit up for 1500 s when two ASCs connected in parallel. These results render an optimistic prospect of the Ni-Mn-S/NiMn-LDH in electrode materials for practical application in developing energy storage systems.

Application of calibration-free wavelength modulated spectral absorption technique in temperature measurement under ultra-short optical path

The measurement of gas temperature parameters is of great significance in scientific research and industrial production. Wavelength modulation technology, as a non-contact optical detection means, has the characteristics of strong anti-interference ability and is widely used in various complex and harsh environments. The accuracy of temperature measurement is affected by short optical paths and weak absorption. In this paper, a calibration-free wavelength modulated ultra-short optical path measurement system is established, and the selection rules of spectral lines under the ultra-short optical path and weak absorption are proposed. The measurement results of wavelength modulation without calibration are in good agreement with those of thermocouple temperature measurement, and the relative error is less than 10%.

Recent preclinical and clinical advances in radioimmunotherapy for non-Hodgkin's lymphoma.

Radioimmunotherapy (RIT) is a therapy that combines a radioactive nucleotide with a monoclonal antibody (mAb). RIT enhances the therapeutic effect of mAb and reduces toxicity compared with conventional treatment. The purpose of this review is to summarize the current progress of RIT for treating non-Hodgkin's lymphoma (NHL) based on recent preclinical and clinical studies. The efficacy of RIT targeting the B-lymphocyte antigen cluster of differentiation 20 (CD20) has been demonstrated in clinical trials. Two radioimmunoconjugates targeting CD20, yttrium-90 (90Y)-ibritumomab-tiuxetan (Zevalin) and iodine-131 (131I)-tositumomab (Bexxar), have been approved in the USA Food and Drug Administration (FDA) for treating relapsed/refractory indolent or transformed NHL in 2002 and 2003, respectively. Although these two radioimmunoconjugates are effective and least toxic, they have not achieved popularity due to increasing access to novel therapies and the complexity of their delivery process. RIT is constantly evolving with the identification of novel targets and novel therapeutic strategies using newer radionuclides such as alpha-particle isotopes. Alpha-particles show very short path lengths and high linear energy transfer. These characteristics provide increased tumor cell-killing activities and reduced non-specific bystander responses on normal tissue. This review also discusses reviewed pre-targeted RIT (PRIT) and immuno-positron emission tomography (PET). PRIT potentially increases the dose of radionuclide delivered to tumors while toxicities to normal tissues are limited. Immuno-PET is a molecular imaging tracer that combines the high sensitivity of PET with the specific targeting capability of mAb. Immuno-PET strategies targeting CD20 and other antigens are currently being developed. The theragnostic approach by immuno-PET will be useful in monitoring the treatment response.

Overcoming Uncertainty in Novel Technologies: The Role of Venture Capital Syndication Networks in Artificial Intelligence (AI) Startup Investments in Korea and Japan

This paper investigates how historical inter-firm syndication networks influence venture capitalists’ (VCs) propensity to invest in startups pursuing novel, uncertain technologies, with a focus on artificial intelligence (AI). We theorize that VCs’ positional attributes within cumulative syndication networks determine their access to external expertise and intelligence that aid AI investment decisions amidst informational opacity. Specifically, reachability to prior AI investors provides referrals and insights transmitted across short network paths to reduce ambiguity. Additionally, VC brokerage between disconnected industry clusters furnishes expansive, non-redundant information that is pivotal for discovering and assessing AI opportunities. Through hypotheses grounded in social network theory, we posit network-based mechanisms that equip VCs to navigate uncertainty when engaging with ambiguous innovations like AI. We test our framework, utilizing comprehensive historical records of global venture capital investments. Analyzing the location information of VC firms in this database, we uncovered a history of 14,751 investments made by Korean and Japanese firms. Using these data, we assembled an imbalanced panel dataset from 1984 to 2022 spanning 230 Korean and 413 Japanese VCs, with 4508 firm-year observations. Negative binomial regression analysis of this dataset reveals how historical relational patterns among venture capital firms foster readiness to evaluate unfamiliar innovations.

Air-gap-assisted solvothermal process to synthesize unprecedented graphene-like two-dimensional TiO2 nanosheets for Na+ electrosorption/desalination

Designing a high-performance capacitive deionization setup is limited due to the slow salt removal and charge storage capacities. Efforts are being made to replace traditional electrodes with advanced 2D materials. We introduce a simple method for synthesizing two-dimensional titanium dioxide graphene-like nanosheets via a unique air-gap-assisted solvothermal method. Crystalline 2D graphene-like anatase-TiO2 sheets of unprecedented quality were obtained by tuning the air gap in the solvothermal reactor. The 2D TiO2 synthesized by air-gap-assisted solvothermal process has shown an exceptionally high surface area of 934.5 m2/g compared to the pristine TiO2 (249.5 m2/g). The sheets were used as Faradaic electrodes in ion-electrosorption and their capacitive deionization capabilities were evaluated. The electrochemical conductivity was examined via an in situ investigation of Na+-ion migration and storage. The adsorption capacity of 2D TiO2 sheets increased with higher applied potential while keeping the adsorption time constant at 15 min. At adsorption potentials of –0.8 V, –1.0 V, and –1.2 V, desalting rates of 2.09, 2.18, and 2.20 mg g−1 min−1 resulted in adsorption capacities of 31.33, 32.73, and 33.023 mg g–1, respectively. The 2D TiO2 electrode demonstrated high electron-transfer rates, a large desalination capacity, and a rapid average desalting rate. The specific capacity of the 2D-layered TiO2 electrode was found to be about 45.68 F g−1. These results can be attributed to the large specific surface area, short ionic diffusion paths, numerous active adsorption sites, surface defects, and pseudocapacitance. This air-gap-assisted solvothermal method is expected to open new avenues for the synthesis of high-quality 2D materials.

Using Memristor Element to Improve the Reliability of Digital Circuits

Memristor has been used as a filter stage to improve The reliability of digital circuits has been improved by using memristor. This element works as a filter stage to waive most of the glitches generated in prior stages. The proposed technique is applied to three different circuits to improve their reliability. Those circuits are: a chain of inverters represents a long path topology, c432 benchmark represents a short path circuit, c1908 benchmark represents a long path circuit. The memristor stage is connected between the last two stages of each output path of the circuit. The memristance of the memristor is changed using a certain parameter (x0), higher memristance means longer propagation delay and more glitches are attenuated. The experiment is run at different values of the memristance and the error probability is calculated at each value. The effect of this stage is studied by calculating the energy consumption and performance of the circuits with and without this stage. The Reliability-Energy-Performance trade-off relationship is found and introduced for each circuit, the results show that the reliability of the circuit is improved to the highest levels, when

Impacts of the Middle Route of China's South-to-North Water Diversion Project on the water network structure in the receiving basin.

The Middle Route of South-to-North Water Diversion Project (MRSNWD) is the main skeleton of China's National Water Network, its construction has changed the structure of the original water network, and analyzing the topological change of the water network in context with MRSNWD is significant for water network planning and management. In this study, the overall network characteristics of the water network in 2010 and 2020 were analyzed based on the small-world and scale-free characteristics of complex network theory. The topological changes of the water network from a node perspective were examined using three network centrality indexes: degree centrality (DC), closeness centrality (CC), and betweenness centrality (BC), while assessing the important nodes of the water network and recognizing functional areas of cold-hot spots. The results show that the water network's centrality in the study area improved after the project construction, with the average degree of the water network increasing from 2.39 to 2.42 and the average path length decreasing from 111.81 to 97.08. The propagation efficiency and network stability also increased, with a rise in important node proportion from 9.8 to 14.4%. The nodes in the DC hotspot zone along the project route have increased by 1.5%, implying an increase in the connectivity of the water network, while MRSNWD optimizes its north-south hub propagation path. "Small-worldness" indicates that most nodes of a network can be accessed and connected over shorter paths. The water network has a significant "small-worldness" and has been enhanced by the MRSNWD's construction. Approximating the water network as a scale-free network can impact its security by identifying critical nodes. The results of this research can provide the necessary technical support and reference significance for China's National Water Network.

Developing a model for unmanned aerial vehicle with fixed-wing using 3D-map exploring rapidly random tree technique

While the motion planning algorithms consider the obstacles that were known in the map, it is possible to use obstacle avoidance algorithms to take over and send commands to theunmanned aerial vehicle (UAV), when there is an unknown obstacle on the way. The rapidly random tree (RRT) algorithm is used to plan paths for a quad-copter or a fixed-wing UAV. This work develops a model for UAV with fixed-wing using a 3D map exploring the RRT technique. The first step is to obtain a 3D occupancy map from the map data stored in the UAV city to provide a map with some pre-generated obstacles. The contribution of this work is to use RRT planning for 3D state space, where the motion segment or motion primitive connecting the two consecutive states should be defined in a 3D space while satisfying the motion constraints of a UAV. The simulation includes setting up a 3D map, providing the starting and destination pose, planning a way using RRT and 3D Dubins moving primitives, smoothing the acquired trajectory, and simulating the UAV flight. The results obtained demonstrate that the smoothed-generated waypoints significantly improved tracking in general with shorter paths.

Radiopharmaceuticals for Cancer Diagnosis and Therapy: New Targets, New Therapies-Alpha-Emitters, Novel Targets.

Radiopharmaceutical therapy has emerged as a promising approach for the treatment of various cancers. The exploration of novel targets such as tumor-specific antigens, overexpressed receptors, and intracellular biomolecules using antibodies, peptides, or small molecules has expanded the scope of radiopharmaceutical therapy, enabling precise and effective cancer treatment for an increasing number of tumor types. Alpha emitters, characterized by their high linear energy transfer and short path length, offer unique advantages in targeted therapy due to their potent cytotoxicity against cancer cells while sparing healthy tissues. This article reviews recent advancements in identifying novel targets for radiopharmaceutical therapy and applications in utilizing α-emitters for targeted treatment.

Self-adaptive learning particle swarm optimization-based path planning of mobile robot using 2D Lidar environment

AbstractThe loading and unloading operations of smart logistic application robots depend largely on their perception system. However, there is a paucity of study on the evaluation of Lidar maps and their SLAM algorithms in complex environment navigation system. In the proposed work, the Lidar information is finetuned using binary occupancy grid approach and implemented Improved Self-Adaptive Learning Particle Swarm Optimization (ISALPSO) algorithm for path prediction. The approach makes use of 2D Lidar mapping to determine the most efficient route for a mobile robot in logistical applications. The Hector SLAM method is used in the Robot Operating System (ROS) platform to implement mobile robot real-time location and map building, which is subsequently transformed into a binary occupancy grid. To show the path navigation findings of the proposed methodologies, a navigational model has been created in the MATLAB 2D virtual environment using 2D Lidar mapping point data. The ISALPSO algorithm adapts its parameters inertia weight, acceleration coefficients, learning coefficients, mutation factor, and swarm size, based on the performance of the generated path. In comparison to the other five PSO variants, the ISALPSO algorithm has a considerably shorter path, a quick convergence rate, and requires less time to compute the distance between the locations of transporting and unloading environments, based on the simulation results that was generated and its validation using a 2D Lidar environment. The efficiency and effectiveness of path planning for mobile robots in logistic applications are validated using Quanser hardware interfaced with 2D Lidar and operated in environment 3 using proposed algorithm for production of optimal path.

Unlocking the Mechanisms behind Austenite Formation of Cold‐Rolled Ferrite–Martensite Dual‐Phase Steels: The Role of Ferrite Recrystallization

In this study, the austenite formation behavior is investigated for the ferrite–pearlite initial microstructure, considering the influence of ferrite recrystallization and cementite distribution. Special attention is also given to the effect of recrystallization state on cementite distribution for varied heating routes. Austenite nucleation for varied recrystallization state is elucidated in terms of activation energy evaluation and post microstructural characterization, and the austenite transformation kinetics are modeled and experimentally validated. In the uncrystallized state, austenite forms on the original pearlite colonies quickly due to the short carbon diffusion path. The high activation energy leads to the exceptionally difficult nucleation at the ferrite–cementite interface inside ferrite matrix. Once recrystallization occurs partially, priority of austenite nucleation is on those ferrite boundaries (both recrystallized and unrecrystallized boundaries) decorated by cementite. With complete recrystallization, preferential nucleation sites are found to be junctions of ferrite–cementite interface on recrystallized ferrite boundaries. Austenite transformation kinetics is well predicted by considering the varied nucleation density due to different recrystallization state, showing a good agreement with experimental data. It is demonstrated directly by experimental evidence that proceeding of recrystallization postpones the austenite transformation kinetics, while getting rid of the interference of heating rate and nucleation location.

Chiral zeolite beta used as stationary phase for enantioseparation in miniaturized open tubular capillary electrochromatography with amperometric detection

BackgroundWith the rapid growth of the demand for optically pure compounds in the fields of biology, medicine and stereospecific synthesis, it is of great importance to develop efficient, economical, simple enantioseparation and analysis methods. Open tubular capillary electrochromatography (OT-CEC) has attracted much attention in the field of chiral separation, but its column capacity and the sensitivity of common-used optical detection are relatively low. Zeolite beta nanomaterial is both enantioselective and size-selective, providing suitable chiral microenvironment for chiral recognition, and amperometric detection (AD) avoids the low sensitivity caused by the short optical path in optical detection to some extent. ResultsZeolite beta nanomaterials with different particle sizes (25, 50 and 200 nm) were synthesized, and the morphology and structure were characterized by scanning electron microscopy and X-ray diffraction. Then, a novel chiral OT column was prepared by one-step method using zeolite beta nanomaterial as chiral stationary phase, and its separation performance was characterized by miniaturized CEC with AD (mini-CEC-AD) device. Under the optimum conditions, six groups of chiral drugs achieved baseline separation. Norepinephrine enantiomers were used for evaluating the inter-day, intra-day and inter-column reproducibility of the prepared open-tubular column. The relative standard deviations of migration time, peak area, resolution and selectivity factor were within 8.7 %. The limits of detection for norepinephrine enantiomers were 0.18 μg mL−1 (S/N = 3), and the average recoveries were in range of 96.7–105.0 %. This developed method has been successfully applied to the analysis of impurity enantiomer in potassium dichromate (+)-norepinephrine injection sample. SignificanceZeolite beta nanomaterial was used as the stationary phase to prepare chiral OT columns for the first time, and this one-step preparation method is simple and easy. The introduction of zeolite beta enriches the types of chiral stationary phase materials in electrochromatographic columns, and mini-OT-CEC-AD system provides an alternative for fast enantioseparation of chiral compounds.

Constructing Co[sbnd]N[sbnd]C coordination in Co9S8 embedded N,S-codoped carbon nanotube as an advanced electrode for supercapacitor and Na-ion battery

Yolk-shell-structured transition metal sulfides (TMSs)/carbon nanocomposites are highly desirable in advanced energy storage system, such as sodium-ion batteries (SIBs) and supercapacitors (SCs). Nevertheless, practical applications are still prevented by the loose attachment of TMSs with carbon caused by conversion stress, the aggregation of TMSs nanoparticles and the sluggish ion transport caused by high crystallinity of carbon. Here, the disperse hollow Co9S8 nanoparticles encapsulated into N,S-codoped carbon nanotubes (CNTs) with poor crystallinity through CoNC bond was synthesized (CS-NSCNT) to overcome the above obstacles. The designed CS-NSCNT can provide the short diffusion path and prevent the huge volume expansion of conversion reaction. Moreover, the established CoNC bond endows the strong interaction and regulates the electronic structure thus promote the stability and rate performance effectively. The CS-NSCNT SCs’s electrode delivers a high specific capacitance of 1150 F g−1 at 1 A g−1, with a high cycling life stability and rate performance. For SIBs, the CS-NSCNT cathode demonstrates an initial reversible capacity of 475 mAh g−1 at 0.1 A g−1 and an excellent rate performance with a capacity retention of 53 % at 10 A g−1. This work may satisfy the long-stability, high-capacitance/capacity, high-power/energy density application requirements of future applications.

Surface sulfurization of liner and ruthenium metallization to reduce interface scattering for Low-Resistance interconnect

Ruthenium with a low resistivity, high melting temperature and short electron mean free path has been considered to replace copper as the next-generation interconnect metallization. However, its ascending resistivity with linewidth scaling because of the diffuse scattering of electrons at the interface with dielectrics or liners is a concern. Thus, in this study, sulfurization was applied on the surface of titanium-tantalum nitride and ruthenium films to form an ultrathin sulfide layer to reduce interface scattering. The microstructure, chemical composition, bonding configuration, and stability of the layer were characterized, and the resistivity scaling of the ruthenium films was examined. Microscopic observations suggested a crystalline TiTaSx layer formed on the titanium-tantalum nitride films while RuS2 formed on the ruthenium films, both of which changed the binding state/energy of the metals. With the surface sulfurization, the interface scattering of electrons for the ruthenium films was effectively reduced to elevate the specularity parameter from 0.2 to 0.9 and lessen the resistivity scaling for at least 40 % at a thickness of below 10 nm, without a marked loss of interfacial adhesion. However, an increase in contact resistance of molybdenum to the surface-sulfurized ruthenium films needs to be considered.

Research on eVTOL Air Route Network Planning Based on Improved A* Algorithm

With the continuous opening of low-altitude airspace and the development of aircraft such as electric vertical takeoff and landing (eVTOL) vehicles, urban air traffic has become a sustainable and green development direction for future transportation. Air route networks, as a mainstream design scheme for air traffic, are able to provide prerequisites for eVTOL and other green aircraft to enter urban airspace for safe operation, among which air route planning is a fundamental component of air route network design. Currently, most of the research on aircraft path planning is performed in free airspace, lacking the analysis and processing for the complex operation environment, which has led to the high risk and large operation cost of path planning results, failing to meet the demand for safe and efficient development in the future. Aiming at the above problems, eVTOL-oriented air route planning research was carried out. Firstly, the urban low-altitude airspace structure was planned, and the operational levels of eVTOL were clarified; this was followed by introducing the urban dynamic air–ground risk factors and constructing a dynamic risk assessment model containing risk level information; finally, the improved A* algorithm based on the risk cost was employed to plan the eVTOL air route network, which finally realized the purpose of short path length and low total risk. The simulation results showed that the route generated by the improved A* algorithm could reduce the risk cost by at least 30% with a relatively small path cost, which ensured the operation efficiency and safety of eVTOLs and laid the foundation for the further sustainable and green development of urban airspace in the future.