3D Surface Research Articles

A Universal Target Plate Design Scheme for Stellarators: theoretical basis and its application to heat load control

Abstract This study introduces a novel divertor target design scheme for stellarators, grounded in mathematical treatments and tailored to control toroidal heat load distributions. Initially, a differential equation characterizing toroidally uniform heat load distribution has been established in a two-dimensional (2D) slab configuration, and its analytic solution has been obtained. Subsequently, a numerical scheme has been developed to adapt the analytic solution into the 3D surface shape of stellarator target. The effectiveness of this design scheme has been validated through simulations of the Chinese First Quasi-axisymmetric Stellarator (CFQS) using a suite of codes including HINT, FLARE and EMC3-EIRENE, where a toroidally uniform heat load distribution has been achieved with an island configuration. Further, the effects of input parameters on the target shape and heat load distribution have been studied. The robustness of the designed target has been investigated by simulation results with varying magnetic island configurations, confirming that the toroidal uniformity of heat load distribution is insensitive to changes in island configurations. Moreover, the designed target has been assessed with gas puffing of neon, which shows that neon injections effectively reduce the heat loads without altering the toroidal uniformity of heat load distributions. The proposed scheme highlights the importance of theoretical and mathematical foundations of target design, offering an advantageous alternative/complement to the traditional numerical schemes.

Low-Cost and Contactless Survey Technique for Rapid Pavement Texture Assessment Using Mobile Phone Imagery

Collecting pavement texture information is crucial to understand the characteristics of a road surface and to have essential data to support road maintenance. Traditional texture assessment techniques often require expensive equipment and complex operations. To ensure cost sustainability and reduce traffic closure times, this study proposes a rapid, cost-effective, and non-invasive surface texture assessment technique. This technology consists of capturing a set of images of a road surface with a mobile phone; then, the images are used to reconstruct the 3D surface with photogrammetric processing and derive the roughness parameters to assess the pavement texture. The results indicate that pavement images taken by a mobile phone can reconstruct the 3D surface and extract texture features with accuracy, meeting the requirements of a time-effective documentation. To validate the effectiveness of this technique, the surface structure of the pavement was analyzed in situ using a 3D structured light projection scanner and rigorous photogrammetry with a high-end reflex camera. The results demonstrated that increasing the point cloud density can enhance the detail level of the real surface 3D representation, but it leads to variations in road surface roughness parameters. Therefore, appropriate density should be chosen when performing three-dimensional reconstruction using mobile phone images. Mobile phone photogrammetry technology performs well in detecting shallow road surface textures but has certain limitations in capturing deeper textures. The texture parameters and the Abbott curve obtained using all three methods are comparable and fall within the same range of acceptability. This finding demonstrates the feasibility of using a mobile phone for pavement texture assessments with appropriate settings.

3D 3,44T19 Type Carbon Allotrope (3,44T19‐CA): An Ideal Candidate with Phononic Stiefel–Whitney Topology and Multi–Dimensional Boundary Vibrational Modes

The Stiefel–Whitney (SW) insulator, which lacks spin‐orbit coupling and has space–time inversion () symmetry, has attracted significant interest due to its fragile topological state and unconventional bulk‐boundary correspondence. Previously, the identification of SW insulators has been widely proposed for 2D phononic systems, but it has received little attention for 3D phononic systems. Herein, it is recognized that the 3D 3,44T19 type carbon allotrope (3,44T19‐CA) possesses the possibility to attain the nontrivial phononic SW topology characterized by a nontrivial second SW number, specifically w2 = 1. In addition, the 3D 3,44T19‐CA has 2D surface vibrational modes and 1D hinge vibrational modes, providing an excellent platform for multi–dimensional topological phononic boundaries research.

3D Uncertain Implicit Surface Mapping Using GMM and GP

3D Uncertain Implicit Surface Mapping Using GMM and GP

Fast Building Instance Proxy Reconstruction for Large Urban Scenes.

Digitalization of large-scale urban scenes (in particular buildings) has been a long-standing open problem, which attributes to the challenges in data acquisition, such as incomplete scene coverage, lack of semantics, low efficiency, and low reliability in path planning. In this paper, we address these challenges in urban building reconstruction from aerial images, and we propose an effective workflow and a few novel algorithms for efficient 3D building instance proxy reconstruction for large urban scenes. Specifically, we propose a novel learning-based approach to instance segmentation of urban buildings from aerial images followed by a voting-based algorithm to fuse the multi-view instance information to a sparse point cloud (reconstructed using a standard Structure from Motion pipeline). Our method enables effective instance segmentation of the building instances from the point cloud. We also introduce a layer-based surface reconstruction method dedicated to the 3D reconstruction of building proxies from extremely sparse point clouds. Extensive experiments on both synthetic and real-world aerial images of large urban scenes have demonstrated the effectiveness of our approach. The generated scene proxy models can already provide a promising 3D surface representation of the buildings in large urban scenes, and when applied to aerial path planning, the instance-enhanced building proxy models can significantly improve data completeness and accuracy, yielding highly detailed 3D building models.

A Three-Dimensional Surface-Adaptive Stretchable Sensor for Online Monitoring of Composite Materials Curing.

Recently, rigid sensors have been commonly applied to online monitoring of the core curing processes of composite materials to prevent both overcuring and under-curing. However, conventional rigid sensors are prone to causing cracks and bubbles in composite materials during the curing process, thereby affecting both the mechanical performance and the overall reliability of the materials. Herein, stretchable interdigital dielectric sensors with flexible substrates and electrodes are designed to conform to complex 3D surfaces, thus enabling embedded nondestructive monitoring of composite curing processes. The sensors obtained can endure 1000 cycles of bending from 0° to 180° and 1000 cycles of stretching at 30% strain while still conforming perfectly to complex 3D surfaces, thus overcoming the inability of traditional curing monitoring sensors to bend. Additionally, sensor integration with an electronic circuit enables real-time data collection and transmission, which makes the device more portable, compact, and lightweight. Moreover, after atmospheric exposure for 5 months, the unit sensitivity of the sensor decreased by only 0.1%, thus demonstrating its excellent reliability and stability. Furthermore, during curing monitoring of the complex three-dimensional surfaces of the Fendouzhe deep-sea submersible, the unit's sensitivity is close to that of conventional planar monitoring equipment, decreasing by only 0.4%. The proposed online nondestructive monitoring technology demonstrates high sensitivity, high monitoring accuracy, and high reliability during surface monitoring, thus enabling long-term curing monitoring under complex nonplanar conditions.

Neural Surfel Reconstruction: Addressing Loop Closure Challenges in Large-Scale 3D Neural Scene Mapping

Efficiently reconstructing complex and intricate surfaces at scale remains a significant challenge in 3D surface reconstruction. Recently, implicit neural representations have become a popular topic in 3D surface reconstruction. However, how to handle loop closure and bundle adjustment is a tricky problem for neural methods, because they learn the neural parameters globally. We present an algorithm that leverages the concept of surfels and expands relevant definitions to address such challenges. By integrating neural descriptors with surfels and framing surfel association as a deformation graph optimization problem, our method is able to effectively perform loop closure detection and loop correction in challenging scenarios. Furthermore, the surfel-level representation simplifies the complexity of 3D neural reconstruction. Meanwhile, the binding of neural descriptors to corresponding surfels produces a dense volumetric signed distance function (SDF), enabling the mesh reconstruction. Our approach demonstrates a significant improvement in reconstruction accuracy, reducing the average error by 16.9% compared to previous methods, while also generating modeling files that are up to 90% smaller than those produced by traditional methods.

Impact of adjacent thoracic structures in negative left atrial remodelling in atrial fibrillation

Abstract Background Previous work has suggested that compression from external structures can promote negative atrial remodelling in atrial fibrillation (AF) [1]. This is mechanistically plausible, with many recognised risk factors in developing AF (age, hypertension, obesity, obstructive sleep apnoea, etc.) related through activation of the autonomic nervous system with an associated increase in atrial pressure and chronic elevation in wall stress [2,3]. Such negative remodelling contributes to the existence of arrhythmogenic atrial substrate [4]. This is highly significant when we consider catheter ablation of extrapulmonary vein targets. Purpose This study aims to investigate the relationship between abnormal conduction patterns indicative of potential AF drivers and their proximity to structures adjacent to the left atrium (LA). Methods Eight patients with paroxysmal or persistent AF, scheduled for an elective catheter ablation procedure using a charge density mapping (CDM) system [5] underwent pre-procedural cardiac MRI. 3D surface mesh reconstructions of individuals’ LA and adjacent structures (ascending aorta [AoA], descending aorta [AoD], and spine) were produced from 2D MRI slices using a proprietary graphical interface tool developed in MATLAB (Figure 1A & B) [6]. MRI derived LA geometries were registered with their CDM counterparts by the Iterative Closest Point algorithm (Figure 1C); this enabled integration of MRI LA geometries into the CDM system. Subsequently, non-contact intrachamber voltage measurements from individuals’ procedures were used to derive cardiac activation directly onto MRI LA geometries. Abnormal conduction patterns representing possible AF drivers (focal firing, rotational propagation, and pivoting propagation) [5] were quantified as occurrences per second at each vertex of MRI LA geometries (Figure 1D). These conduction patterns could then be visualised and assessed in the context of adjacent structures (Figure 1E), with the Euclidean distance between each vertex of the MRI LA geometries and the closest point to their adjacent structures being calculated. Results Mean age was 65±9 years; 4 patients (50%) were male; AF was paroxysmal in 3 (37%) and persistent in 5 (63%); median time since AF diagnosis was 1 (1-3.8) years; ablation type was de novo in 5 (63%) and retreatment in 3 (38%). Frequencies of pivoting and rotational propagation were notably higher in regions of the LA closer to the AoA, and lower near the AoD and spine (Figure 2A & B). Conversely, focal firing showed a less prominent trend, being more frequent in LA regions nearer the AoD and distant from the AoA (Figure 2C). Conclusions Compression from the ascending aorta may promote anterior LA remodelling in AF, leading to increased pivoting and rotational AF drivers. Clinically, this suggests a potential target for ablation therapy with an anterior seatbelt line connecting the right superior pulmonary vein to the mitral annulus.

Neural fields for rapid aircraft aerodynamics simulations

This paper presents a methodology to learn surrogate models of steady state fluid dynamics simulations on meshed domains, based on Implicit Neural Representations (INRs). The proposed models can be applied directly to unstructured domains for different flow conditions, handle non-parametric 3D geometric variations, and generalize to unseen shapes at test time. The coordinate-based formulation naturally leads to robustness with respect to discretization, allowing an excellent trade-off between computational cost (memory footprint and training time) and accuracy. The method is demonstrated on two industrially relevant applications: a RANS dataset of the two-dimensional compressible flow over a transonic airfoil and a dataset of the surface pressure distribution over 3D wings, including shape, inflow condition, and control surface deflection variations. On the considered test cases, our approach achieves a more than three times lower test error and significantly improves generalization error on unseen geometries compared to state-of-the-art Graph Neural Network architectures. Remarkably, the method can drastically accelerate high fidelity numerical solver, achieving a five order of magnitude speedup on the RANS transonic airfoil dataset.

Characterization of Interface Transition Zone in Asphalt Mixture Using Mechanical and Microscopic Methods

An enormous surge in the pavement sector requires the evaluation of interface bonding in asphalt composite, since the assessment of bonding brings considerable cost savings. Microscopic and mechanical analyses were performed to study the status of the interface transition zone of four groups of asphalt mixtures, using thin-slice preparation to obtain asphalt mixture slices with a flat surface for microscopic analysis. The interface transition zones were characterized using good knowledge of blending or diffusion phenomena by conducting tests both at the micro and macro levels to determine mixture quality. Asphalt mixture components were observed using fluorescence microscopy imaging and evaluated by the gray value change law. Asphalt mixture groups, (virgin, recycled of 30% aged and 70% unaged, 6%, and 4% rejuvenator dosage mixtures) under the same process parameters, which are a mixing time of 270 s and a mixing temperature of 150 °C, been considered optimum for component fusion in a hot asphalt mixture were used. This study relied on the influence of morphology law, assessed through rutting tests for high temperature performance, semi-circular bending tests for low temperature performance, and pull-off tests for interface bonding strength. The relationship between interface transition zones and macro performance was studied. The self-developed pull-off method was a research innovation which can be used as an alternative to study interface transition zones in asphalt mixtures, and provides the necessary data needed with 3D surface failure mode calculations. The device measured the bonding strength of a single aggregate in distinct positions using the bitumen penetration test method. The main goals were to determine a correction factor, identify the appropriate alteration, and compute the actual fracture surface area. Using scanning electron microscopy for interface characterization and micro-morphologies of mortar transition zone, our analysis provides adequate knowledge about interface position and the components present. The applied approaches to characterize asphalt mixture interfaces proved workable and reliable, as all methods have similar trends with useful information to determine asphalt pavement quality.

Enhancing Ketoprofen Solubility: A Strategic Approach Using Solid Dispersion and Response Surface Methodology.

In the pharmaceutical sciences, the solubility profile of therapeutic molecules is crucial for identifying and formulating drugs and evaluating their quality across the drug discovery pipeline based on factors like oral bioavailability, metabolic transformation, biodistribution kinetics, and potential toxicological implications. The investigation aims to enhance the solubility parameters of ketoprofen (BCS-II class), which exhibits low solubility and high permeability. In this method, hydrotrope blends of aromatic sodium benzoate and electrolyte sodium acetate were employed to enhance the solubility parameter of ketoprofen. Several batches of solid dispersion of ketoprofen were made using a solvent evaporation method, and the response surface method 3² factorial design was used to find the best one. The optimised formulation, KSD9, underwent in-vitro drug dissolution, DSC, pXRD, and SEM studies. The optimized batch demonstrated substantial improvement in ketoprofen solubility, attributed to mixed hydrotropy. The results indicated that both solubility and %CDR improved when hydrotropes were employed, suggesting a direct proportionality between the rise in solubility and %CDR. Formulations KSD1-KSD9 exhibited solubility enhancements ranging from 2.23 to 5.77-fold, along with an elevation in %CDR from 72.28% to 94.76%. This implies that the %CDR was modulated by the hydrotropes, specifically influenced by the concentration levels of the independent variables. An increase in hydrotrope levels corresponded to an increase in %CDR. The positive coefficients in the quadratic equation for %CDR underscored the significant role of these independent variables in augmenting the in-vitro release of Ketoprofen. Similarly, during a comparative dissolution investigation, the optimized KSD9 formulation exhibited remarkable solubility and drug content compared to conventional Ketoprofen dispersible tablets. The synergistic effect of combining two hydrotropic agents significantly increased the solubility of ketoprofen by up to 58 times. The results indicated that the independent variables exerted a positive influence on solubility and %CDR. Furthermore, the responses were contingent on the specific hydrotropes selected, which functioned as the independent variables. Analyzing the r² and ANOVA results suggested that the dependent variables aligned well with the chosen model. Visual representations, such as the 3D response surface plot and contour plot, demonstrated the impact of each hydrotrope individually and when combined. Overall, employing hydrotropes led to improved solubility and %CDR, highlighting a direct proportionality between the rise in solubility and %CDR. Mixed hydrotropic lessens the toxicity associated with individual hydrotrope concentrations while also offering a sustainable and eco-friendly alternative. This study paves the way for future research aiming to improve the solubility of low- solubility drugs, broadening their clinical applications.

Fringe photometric stereo

In fringe projection profilometry (FPP), a high spatial frequency of fringe typically indicates powerful error suppression capability; however, it complicates phase unwrapping, necessitating a greater number of patterns and thus compromising the real-time performance of scanning. In this letter, we report a fringe photometric stereo (FPS) to completely bypass phase unwrapping for recovering the continuous 3D surface. We reveal the linear mapping relationship between the phase gradient and depth gradient, thereby facilitating the computation of depth gradients from phase gradients. Thus, we can employ depth gradients to reconstruct high-quality 3D profiles. Experimental results demonstrate that our FPS surpasses traditional phase-shifting profilometry in mitigating Gaussian noise. Our approach enables high-quality and unambiguous 3D reconstruction using single-frequency fringe patterns, relying solely on a camera and a projector without the need for dual, multiple, or light field cameras, thereby paving a path to high-speed and precision 3D imaging.

TaNSR:Efficient 3D Reconstruction with Tetrahedral Difference and Feature Aggregation

AbstractNeural surface reconstruction methods have demonstrated their ability to recover 3D surfaces from multiple images. However, current approaches struggle to rapidly achieve high‐fidelity surface reconstructions. In this work, we propose TaNSR, which inherits the speed advantages of multi‐resolution hash encodings and extends its representation capabilities. To reduce training time, we propose an efficient numerical gradient computation method that significantly reduces additional memory access overhead. To further improve reconstruction quality and expedite training, we propose a feature aggregation strategy in volume rendering. Building on this, we introduce an adaptively weighted aggregation function to ensure the network can accurately reconstruct the surface of objects and recover more geometric details. Experiments on multiple datasets indicate that TaNSR significantly reduces training time while achieving better reconstruction accuracy compared to state‐of‐the‐art nerual implicit methods.

Dual frequency composite pattern temporal phase unwrapping for 3D surface measurement

Phase shifting profilometry (PSP) is widely used in three-dimensional (3D) optical metrology applications such as mechanical engineering, industrial monitoring, computer vision, and biomedicine because of its high measurement accuracy. In PSP, multi-frequency temporal phase unwrapping (TPU) plays a dominant role due to its high-accuracy measurement of surfaces with discontinuities and isolated objects. However, it requires a large number of fringe patterns. To reduce the number of required patterns, a new dual-frequency composite-pattern TPU method is developed, which needs only three patterns. The new method combines two fringe patterns of different frequencies into three composite fringe patterns, reconstructs rough 3D points by demodulating the low-frequency fringe pattern using geometric constraints, and reprojects it to obtain a rough low-frequency absolute phase, which is then refined to correct edge errors. Finally, the high-frequency wrapped phase is unwrapped under the guidance of the refined low-frequency phase, thereby the accurate 3D points are reconstructed based on stereo-vision technology. Experimental results demonstrated that the proposed method can achieve 3D surface measurement with only three images, which greatly improves the measurement efficiency. The proposed method has great application potential for the rapid 3D measurement of discontinuous surfaces and isolated objects.

High-precision 3D Modeling of Construction Waste Pile Bodies by Integrating Multi-source Data

Abstract. The instability of construction waste pile bodies, as an increasingly concerning disaster, poses significant risks to the safety of people's lives and property. Currently, there is limited research on high-precision 3D modeling techniques for construction waste pile bodies, which significantly hinders the accuracy and reliability of early detection and risk assessment of pile body instability. Therefore, constructing high-precision 3D models of construction waste pile bodies using multi-source data plays a crucial role in improving the accuracy and timeliness of early warning systems for pile body instability, offering significant theoretical research and practical application value. Building 3D models of construction waste pile bodies solely based on unmanned aerial vehicle (UAV) oblique photography data faces challenges, such as various degrees of data voids and insufficient model completeness, and few methods currently address the construction of 3D models of construction waste pile bodies through the fusion of multi-source data. This paper attempts to use the Iterative Closest Point (ICP) algorithm, combining SLAM laser point cloud data with UAV oblique photography data to fill data voids, and utilizes the fused point cloud to reconstruct the triangulation network, achieving the transformation from 3D point cloud models to 3D surface models. On the basis of texture mapping, a high-precision 3D model of the construction waste pile body is constructed. The research results show that the 3D model of the construction waste pile body, integrated with multi-source data, has a planar error of 0.0187m and an elevation error of 0.0368m, meeting the corresponding model accuracy requirements. It can more realistically restore the fine 3D features of the construction waste pile body, effectively compensating for the shortcomings of single-source data in 3D modeling of construction waste pile bodies, providing a new method for the 3D model reconstruction of construction waste pile bodies, and offering effective data support for construction waste research.

Study on the deep deoxidation mechanism of titanium powder using Y/YOCl/YCl3 and Y/Y2O3 systems

Low-oxygen high-purity titanium (oxygen concentration ≤ 500 ppm) is a critical material for advanced semiconductor and biomedical applications. Current deoxidation methods limit oxygen concentration in titanium to approximately 1000–2000 ppm, failing to meet the demand for ultra-low oxygen levels in high-performance materials. This study investigated the preparation mechanism and conditions for low-oxygen high-purity titanium utilizing a molten salt thermochemical method, employing Y as the deoxidant with a theoretical deoxidation limit below 10 ppm. We experimentally explored the deoxidation mechanisms of titanium using Y/YOCl/YCl3 and Y/Y2O3 systems, successfully reducing the oxygen concentration in titanium to 200 ppm, and proving that the Y/YOCl/YCl3 system is more efficient than the Y/Y2O3 system. Additionally, the titanium samples were analyzed using SEM-EDS, XRD, XPS, and 3D surface profilometry before and after deoxidation. These analyses examined the impact of the deoxidation process using Y on the crystal structure, oxide film, and surface roughness of titanium specimens, which are useful for understanding the deoxidation mechanism. During the sintering process of titanium powder attached to Y, the deoxidation process will produce YOCl or Y2O3. The formation of these deoxidation products leads to local oxygen diffusion, and the crystals of YOCl or Y2O3 are gathered at grain boundaries, which will resolve during the subsequent acid etching process, thus reducing the oxidation concentration of the titanium. The above results provide further theoretical guidance and technical support for the production of ultra-high-purity titanium powder.

DSM Reconstruction from Uncalibrated Multi-View Satellite Stereo Images by RPC Estimation and Integration

In this paper, we propose a 3D Digital Surface Model (DSM) reconstruction method from uncalibrated Multi-view Satellite Stereo (MVSS) images, where Rational Polynomial Coefficient (RPC) sensor parameters are not available. While recent investigations have introduced several techniques to reconstruct high-precision and high-density DSMs from MVSS images, they inherently depend on the use of geo-corrected RPC sensor parameters. However, RPC parameters from satellite sensors are subject to being erroneous due to inaccurate sensor data. In addition, due to the increasing data availability from the internet, uncalibrated satellite images can be easily obtained without RPC parameters. This study proposes a novel method to reconstruct a 3D DSM from uncalibrated MVSS images by estimating and integrating RPC parameters. To do this, we first employ a structure from motion (SfM) and 3D homography-based geo-referencing method to reconstruct an initial DSM. Second, we sample 3D points from the initial DSM as references and reproject them to the 2D image space to determine 3D–2D correspondences. Using the correspondences, we directly calculate all RPC parameters. To overcome the memory shortage problem while running the large size of satellite images, we also propose an RPC integration method. Image space is partitioned to multiple tiles, and RPC estimation is performed independently in each tile. Then, all tiles’ RPCs are integrated into the final RPC to represent the geometry of the whole image space. Finally, the integrated RPC is used to run a true MVSS pipeline to obtain the 3D DSM. The experimental results show that the proposed method can achieve 1.455 m Mean Absolute Error (MAE) in the height map reconstruction from multi-view satellite benchmark datasets. We also show that the proposed method can be used to reconstruct a geo-referenced 3D DSM from uncalibrated and freely available Google Earth imagery.

Mutually Activated 2D Ti0.87O2/MXene Monolayers Through Electronic Compensation Effect as Highly Efficient Cathode Catalysts of Li–O2 Batteries

Abstract2D materials exhibit remarkable electrochemical performance as the cathode catalyst in lithium–oxygen batteries (LOBs). Their catalytic capability mainly derives from their 2D surface with tunable surface chemistry and unique electronic states. Herein, Ti0.87O2 and Ti3C2 MXene monolayers are applied to construct a face/face 2D heterostructure to enhance the catalytic performance in LOBs. It is demonstrated that electronic compensation from the O‐terminated MXene to Ti0.87O2 side is achieved through the built‐in electric field and the overlap of Ti 3d and O 2p orbitals between Ti0.87O2 and MXene units. As a result, the ORR/OER catalytic activity is improved in Ti0.87O2/MXene heterojunction due to the modulated p‐band center that optimizes the s–p coupling with the key intermediate LiO2. The Ti0.87O2/MXene cathode presents a structural stability and long‐term cycling life of 425 cycles (2534 h) at 200 mA g−1 and 407 cycles at 1000 mA g−1 with a fixed capacity of 600 mAh g−1, being nearly five and three times higher than that of pure Ti0.87O2 and MXene cathodes, respectively.

First-principles calculations of the elastic anisotropy, thermal conductivity, and optical properties of MAX-phase M2AlC (M = V, Nb, Ta) series carbides

Materials from the MAX phase, such as the M2AlC (M = V, Nb, Ta) series carbides, exhibit superior mechanical, electronic, and thermodynamic properties, making them highly promising for research. Density functional theory (DFT) has been employed to study the elastic anisotropy, thermal conductivity, electronic, and optical properties of these carbides. The results indicate that the formation enthalpies of the M2AlC (M = V, Nb, Ta) series are negative and the phonon spectra do not exhibit imaginary frequencies, confirming the thermodynamic and dynamic stability of these carbides. Additionally, the calculated Poisson's ratios and B/G ratios suggest that these materials are brittle and contain covalent and ionic bonds—a conclusion further corroborated by analyses of electronic structures. The elastic anisotropy is illustrated through anisotropy indices, three-dimensional (3D) surface configurations, and two-dimensional (2D) projections, with the sequence of anisotropy being: Nb2AlC > Ta2AlC > V2AlC. Further investigations into the sound velocities, Debye temperature, anisotropy of sound velocity, thermal conductivity, and optical properties of the M2AlC (M = V, Nb, Ta) series provide substantial theoretical support for the research on MAX phase M2AlC (M = V, Nb, Ta) series carbides.

3D-printed modular platform for path-customizable liquids transport

Spontaneous liquid transport is increasingly being applied in various fields such as microfluidics, fuel cells, phase change heat transfer, water harvesting, etc. However, long-distance spontaneous liquid transport with path-customizable motion trajectories is still challenging. Drawing multi-inspirations from the wedge-shaped structures of iris petals, the continuous structures of bamboo joints, and the microgroove structures of Nepenthes mouth edge, we fabricate a modular, pump-free biomimetic liquid transport platform by 3D printing and surface modification. The platform is composed of sequential wedge notches, and a crescent-shaped groove is designed at the joint of every two connected wedge structures. The platform is characterized by path-customizable liquid transport trajectories and can be used to achieve long-distance liquid transport without the need of external energy fields, and the multi-level nested structures along the depth significantly facilitates the liquid transport. Experimental study and theoretical force analysis show that the crescent-shaped grooves enable the liquid to overcome joint barriers by converting potential energy accumulated at joints into kinetic energy, achieving a maximum velocity of 18 mm/s. Taking advantage of the flexibility of 3D printing and long-distance transport capability, the modular structure of the platform enables customization of the transport distance and trajectory. By assembling 14 bamboo-like wedge-shaped units in series, we realized a transport distance up to 350 mm, which could be further increased by connecting more units. Furthermore, we develop various modular and multifunctional liquid transport platforms for anti-gravity transport, liquid diversion, and customized transport trajectories, which demonstrate that our design strategy could be an available solution for path-customizable liquids transport in fields like bio-sensing, fuel cells, etc.